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Defining and measuring the love of learning

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Title:
Defining and measuring the love of learning
Creator:
McFarlane, Terry Ann
Publication Date:
Language:
English
Physical Description:
272 leaves : ; 28 cm

Thesis/Dissertation Information

Degree:
Doctorate ( Doctor of Philosophy)
Degree Grantor:
University of Colorado Denver
Degree Divisions:
School of Education and Human Development, CU Denver
Degree Disciplines:
Educational Leadership and Innovation
Committee Chair:
Stevens, Ellen A.
Committee Co-Chair:
Goodwin, Laura
Committee Members:
Goodwin, William
Marlow, Michael
Duran-Aydintug, Candan

Subjects

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Learning and scholarship -- Testing ( lcsh )
Motivation in education -- Testing ( lcsh )
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bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

Notes

Bibliography:
Includes bibliographical references (leaves 247-272).
General Note:
School of Education and Human Development
Statement of Responsibility:
by Terry Ann McFarlane.

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|University of Colorado Denver
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|Auraria Library
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All applicable rights reserved by the source institution and holding location.
Resource Identifier:
54523065 ( OCLC )
ocm54523065
Classification:
LD1190.E3 2003d M22 ( lcc )

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Full Text
DEFINING AND MEASURING THE LOVE OF LEARNING
by
Terry Ann McFarlane
B.A., California State University at Stanislaus, 1972
M.A., St. Marys University, 1981
A thesis submitted to the
University of Colorado at Denver
in partial fulfillment
of the requirements for the degree of
Doctor of Philosophy
Educational Leadership and Innovation


2003 by Terry Ann McFarlane
All rights reserved.


This thesis for the Doctor of Philosophy
degree by
Terry Ann McFarlane
has been approved
by
Ellen A. Stevens
William Goodwin
Michael Marlow
Candan Duran-Ayd:


Date


McFarlane, Terry Ann (Ph.D., Educational Leadership and Innovation)
Defining and Measuring the Love of Learning
Thesis directed by Associate Professor Ellen A. Stevens
ABSTRACT
The purposes of this study are to operationally define the construct, love of learning,
to develop an instrument to measure the construct, and to estimate the measures
reliability and validity. To define and measure the love of learning construct, a
comprehensive review of the research most closely related to love of learning was
undertaken and a love of learning instrument was developed. A 72-item pool for the
instrument was generated following a framework of operational definitions and a
table of specifications. Items were selected for the love of learning instrument using a
five-person modified Delphi method. Interrater agreement and reliability were
estimated for the item pool and instrument by three methods. Two of the three
showed good agreement and reliability, but the repeated measures ANOVAs showed
that most of the variance could be attributed to the rater or items by rater interaction
(error term). The 25-item instrument was administered to students attending eleven
institutions of higher education. Demographic mean differences were compared. Item
consistency reliability was estimated at .92. Correlation analyses among the
IV


subconstructs and exploratory factor analysis were conducted. Validity was examined
using correlational anlayses and a hybrid multitrait-multimethod matrix. Generally,
the literature review, results of the survey administration, and analysis of the
measurements psychometric properties suggest that the love of learning as a
theoretical construct exists and varies individually among young adults. Although
several problems emerged and the study had several methodological weaknesses,
most evidence supports the argument that the instrument measures the love of
learning construct.
This abstract accurately represents the content of the candidates thesis. I recommend
its publicati
Signed_____
Ellen A. Stevens


ACKNOWLEDGMENTS
To Dr. Ellen A. Stevens, a very great friend and advisor, I wish to express my
sincere gratitude and appreciation for her vision, wisdom, and guidance throughout
my years in the doctoral program and especially for her encouragement, unfailing
support, and deep commitment during the dissertation process. My gratitude and
appreciation are given to Dr. Laura Goodwin as well, whose wonderful
encouragement, insights, and expertise were especially empowering to me in the
measurement and analyses phases of the dissertation. I also wish to thank Drs.
William Goodwin, Michael Marlow, and Candan Duran-Aydintug for their advice
regarding this study.
I also wish to thank the members of my doctoral laboratory: Robert Davis,
Noel LeJeun, Kim Peterson, Ellen Stevens, and Heidi Strang for serving as experts
during the instrument development phase of the study, and to other members of the
doctoral laboratory for their support and feedback to me during the process. My
thanks also go to my running friends for supporting as well as distracting me during
this dissertation process. Last but not least, I would like to thank my coach, Laurie
Weiss, who having gone through this process at about the same time in her life and
with her experience in writing books, was able to give me special help and guidance
to encourage my writing.


I dedicate this dissertation to the members of my family because of the
various roles they play in my life. I dedicate this dissertation to my mom and dad for
their unconditional love and support. Mom thought I was a genius and dad told me I
could do anything I wanted to do. I dedicate this dissertation to my two beautiful
daughters, who encouraged me and had great faith in me. I suppose they always have!
And finally, I dedicate this dissertation to my spouse, Scott, who exercised patience
beyond belief and provided stability and occasional computer support while I was
engaged in this process.


CONTENTS
Figures.....................................................xiv
Tables .....................................................xv
CHAPTER
1. INTRODUCTION...............................................1
Purposes of the Study...................................1
The General Problem.....................................1
Background of the Problem...............................3
Conceptual Framework...................................11
Research Questions.....................................14
Methodology............................................16
Structure of the Dissertation..........................17
2. REVIEW OF THE LITERATURE..................................18
Historical Perspective.................................19
Ancient Philosophers.............................19
Early Educators and Psychologists................24
Contemporary Research on Constructs
Related to Love of Learning............................27
vm


Curiosity
27
First Wave Issues.............................28
Second Wave Measurement.......................34
Summary.......................................40
Intrinsic Motivation................................41
Definitions...................................42
Taxonomies....................................45
Research......................................49
Measures of Intrinsic Motivation..............55
Flow................................................59
Definition....................................60
Optimal Arousal...............................63
Research......................................65
Interest............................................67
Historical Background.........................68
Theoretical Definitions.......................69
Research......................................73
Relationship of Interest to Other
Love of Learning Constructs...................77
Summary.......................................80
IX


Self-concept in Terms of Competence,
Growth and Complexity, and Meaning and Purpose.....81
Self-concept.................................82
Self-concept in Terms of Competence..........84
Self-concept in Terms of Growth and
Complexity...................................92
Self-concept in Terms of Meaning and Purpose... 95
Summary.....................................101
3. METHODOLOGY..................................................104
Introduction.............................................104
Design...................................................106
Subjects and Sampling Procedures.........................107
Variables................................................108
Love of Learning Variables.........................108
Epistemic Curiosity.........................109
Intrinsic Motivation........................109
Interest....................................110
Flow........................................110
Self-concept in Terms of Competence.........Ill
Self-concept in Terms of Growth and
Complexity..................................Ill
x


Self-concept in Terms of Meaning and Purpose. 112
Positive Model Variables.............................112
Trait Curiosity...............................113
Intrinsic Enjoyment...........................113
Negative Model Variables.............................114
Anxiety.......................................115
Boredom.......................................115
Borderline Variable..................................116
Self-actualization............................116
Contrary Variable....................................117
Flexibility...................................117
Instrumentation..............................................118
Data Collection Procedures...................................121
Phase 1. Instrument Development......................121
Phase 2. Reliability and Instrument Structure Study..122
Phase 3. Construct Validity..........................122
Data Analysis Procedures.....................................122
Phase 1. Instrument Development......................122
Phase 2. Reliability and Instrument Structure Study..123
Phase 3. Construct Validity..........................123
xi


Limitations
124
Summary.....................................................126
4. RESULTS...................................................... 128
Introduction................................................128
Phase 1. Instrument Development.............................129
Developing a Framework...............................130
Table of Specifications..............................134
Generating an Item Pool..............................136
Selecting Items for the Survey.......................136
Interrater Reliability...............................143
Phase 2. Reliability and Instrument Structure Study.........149
Data Collection......................................149
Participants.........................................150
Results..............................................151
Means and Mean Comparisons....................151
Reliability and Item Analyses.................155
Factor Analysis...............................157
Phase 3. Construct Validity.................................165
Data Collection......................................166
Participants.........................................167
Xll


Results
169
Means, Standard Deviations, and Reliabilities.... 169
Correlational Analyses.......................169
Multitrait-multimethod.......................172
Summary...................................................175
5. DISCUSSIONS AND CONCLUSIONS...................................178
Summaries and Interpretations.............................179
Question 1........................................ 179
Question 2..........................................185
Question 3..........................................187
Question 4..........................................191
Question 5..........................................195
Limitations...............................................198
Theoretical Foundations, Implications for Practice, and
Further Research..........................................202
APPENDIX
A. Premises and Principles of the Learner-centered Model........210
B. Definitions of Curiosity, Intrinsic Motivation, and Interest.217
C. Psychometric Information about Various Curiosity Instruments.223
D. Contact and Consent Letters..................................228
xm


E. Love of Learning Items and Sources...............233
BIBLIOGRAPHY.............................................247
xiv


FIGURES
Figure
1.1 Conceptual framework for the love of learning.......................13
4.1 Scree Plot ........................................................158
5.1 Revised conceptual framework for the love of learning..............184
xv


TABLES
Table
4.1 Number and percentage of items in
initial pool and survey for each subconstruct.........................141
4.2 Love of learning survey items.........................................142
4.3 Interrater agreement by round for the 72-item pool....................145
4.4 Repeated measures ANOVAs for the 72-item pool.........................146
4.5 Interrater agreement by round for the 25-item survey..................147
4.6 Repeated measures ANOVAs by round for the 25-item survey..............148
4.7 Education level.......................................................151
4.8 Mean comparisons for demographic variables............................152
4.9 Tukey HSD multiple comparison post hoc test for
educational level.....................................................153
4.10 Tukey HSD multiple comparison post hoc test for
marital status.......................................................154
4.11 Reliability analysis Scale (alpha): Item-total statistics..........156
4.12 Tests for violations of the sphericity assumptions...................159
4.13 Factors and loadings comprising the
love of learning instrument..........................................161
4.14 Correlations among love of learning construct and
subconstructs .......................................................164
xvi


4.15 Education level .........................................................169
4.16 Means, standard deviations, and reliabilities of
validation scales ........................................................170
4.17 Correlations among the scales and instruments used
for construct validation..................................................171
4.18 Variation of the multitrait-multimethod matrix...........................173
xvii


CHAPTER 1
INTRODUCTION
Purposes of the Study
The purposes of this study are to operationally define the construct, love of
learning, to develop an instrument to measure the construct, and to estimate the
measures reliability and validity. This study is significant because it will add to the
measurement (psychometric) literature. The practical significance follows from the
theoretical significance. In knowing what a love of learning is, parents and educators
may develop ways to nurture it so that it becomes a way of life.
The General Problem
Bronzaft (1996) identified love of learning as the critical determinant in
distinguishing successful academically high achievers (AHAs) from others. She
interviewed 529 AHAs about their childhood experiences in the home and at school.
Although she identified several potential properties and processes related to love of
learning, she did not provide a specific definition. She did, however, draw a direct
connection between achievement and love of learning.
1


Berliner and Biddle (1995) drew a somewhat different connection. Their law
of student achievement specifically states that regardless of what anyone claims
about students and school characteristics, opportunity to learn is the single most
powerful predictor of student achievement (p. 55). Though one may decry the lack
of equitable opportunities in education, would anyone suggest that in any instance
there are absolutely no opportunities to learn? Probably not. Therefore, while
equitable opportunities to learn are important, creating and using existing
opportunities to learn are as important. According to Berliner and Biddle (1995),
more students are graduating from high school; more students are attending college;
and more students are earning college degrees than in previous decades. Apparently,
teachers and students are sufficiently creating and using educational opportunities. Or
are they?
The evidence that students in America are attaining higher levels of education
may not tell the whole story. Experts point out that children enter schools eager to
learn but lose that eagerness too soon. Wlodkowski and Jaynes (1990) suggested that
this decline is to be expected for several reasons: (a) learning in school occurs in
groups with formalized curriculum and grading system, (b) advanced learning
becomes increasingly complex, and (c) learning is hampered by many distractions in
the world. Massimini and Carli (1988) studied forty-seven 16- to 19-year-olds and
concluded that they derived enjoyment more from art, hobbies, and socializing than
2


academic pursuits. Fredricks, Alfeld-Liro, and Eccles (1999) studied self-reported
interest in sports, music, and math across the grades. They concluded that the passion
to learn is rare and that passion more frequently characterized non-academic
achievement activities. Indeed, students may be learning more and enjoying it less.
What may be needed more than increased and equitable opportunities to learn
is nurturing the eagerness to learn apparent in young students such that a disposition
towards a love of learning unfolds in young adults. Such a disposition would give
every student something more than economic self-sufficiency, essential as it is. Love
of learning would give students the key to self-fulfillment for the rest of their lives.
First, however, it is essential to define what is meant by a love of learning. When love
of learning is referenced, it is rarely defined.
Background of the Problem
The assertion that little research has been conducted specifically about the
love of learning needs to be qualified. For one, Bronzafts (1996) study of
academically high achievers (AFlAs) inferred a great deal about the love of learning.
Second, several measurement studies revealed a factor dubbed love of learning or
academic interest. Usually, this was in the context of validating a measure for some
kind of motivation, study attitudes, academic self-concept, etc. Third, much research
has been conducted in several conceptually related areas. For example, curiosity,
3


intrinsic motivation, flow, interest, and self-concept in terms of competence, growth,
and purpose have been studied extensively and may partially comprise what love of
learning is.
Bronzaft (1996) interviewed many AHAs. Her interviews revealed the
importance of home and family in the development of a love of learning. She
concluded that the love of learning lies in normal childhood curiosity. She suggested
that the following conditions were instrumental in fostering a love of learning: (a)
emphasis on reading, (b) parents who Value learning, (c) love of learning as a family
tradition, (d) teachers who foster love of learning by making a student feel proud and
worthwhile, (e) pleasure that comes from doing ones best rather than winning, and
(f) love of learning as a way of life. Though she clarified the conditions for fostering
a love of learning, Bronzaft never really defined what she meant by love of learning.
In attempting to measure such constructs as academic self-concept, study
attitudes and methods, and self-direction, researchers have repeatedly uncovered a
factor for which love of learning is an apt label. For example, Guglielmino (1977)
developed an instrument to assess self-directed learning readiness (SDLR) as part of
her doctoral dissertation. Using factor analysis, she identified eight factors and
labeled one of them love of learning.
In exploring school-related factors of self-concept, Michael, Smith, and
Michael (1984) developed a measure entitled Dimensions of Self-Concept (DOSC).
4


They uncovered five factors and labeled one of the factors Academic interest and
satisfaction. They defined this factor as the
sheer pleasure gained by students in studying and in doing academic
work, much like that experienced by the dedicated scholar who gains
great satisfaction in working in the library, in writing papers, and in
reading the great books an intrinsic motivation involving love of
learning for its own sake (p. 2).
Two years later, Michael, Denny, Ireland-Galman, and Michael (1986) conducted a
factorial validity study of the Studies Attitudes and Methods Scale (SAMS). They
labeled one of the six factors, Academic interests love of learning. The authors
defined this factor very similarly to the academic interest and satisfaction factor of the
DOSC. Academic interests love of learning is intrinsic motivation involving
learning for its own sake. Thus, there is some psychometric evidence for the existence
of a love of learning construct. Although factor analysis alone is insufficient, these
studies provide the beginning of a conceptual definition.
One infers by studying the descriptions of the factors described above and
examining the nature of the items comprising those factors, that love of learning
probably consists of curiosity, intrinsic motivation, a positive affective state (flow),
self-concept, and interest. Indeed, research literature on these constructs is replete
with implications that they are part of and relate to a joy of, love of, enthusiasm for,
eagerness for, and desire for learning.
5


Researchers of curiosity have reached a tentative consensus that curiosity is
composed of two factors. Several studies have demonstrated a two-factor solution
(Ainley, 1987; Langevin, 1971; Naylor, 1981; Spielberger & Starr, 1994; Starr,
1992). Usually, the two-factors solution forms an epistemic curiosity or information-
seeking component and a diversive curiosity or experience-seeking component
(Spielberger & Starr, 1994; Starr, 1992). Interestingly, Berlyne (1950) originally
conceived of curiosity as comprised of two such factors. The former factor is more
part of the love of learning because learning more often refers to knowledge
acquisition in academic subjects rather than sensational and novel experiences in life.
Some researchers have suggested that curiosity and intrinsic motivation are
the same thing (Starr, 1992; Lepper & Malone, 1987). They may draw this conclusion
in part because eventually Berlyne integrated many of his original ideas regarding
curiosity (Berlyne, 1950) with intrinsic motivation (Berlyne, 1971). Although the
research regarding intrinsic motivation and curiosity is curiously distinct, the two
constructs seem bound to the same dimension of human behavior (Harlow, 1953).
This may be because early theorists postulated that either construct was activated by
instinct or a drive mechanism and approached research from a behavioristic or
psychoanalytic tradition. Recently, however, researchers have taken a more
organismic approach (Deci, 1975).
Intrinsic motivation has been defined as human motives stimulated by the
6


inherent nature of the activity or its natural consequences (Lahey, 1998, p. 341).
Lepper and Malone (1987) greatly elaborated this definition by including in their
definition of intrinsic motivation the concepts of challenge, competence, effectance,
mastery orientation, curiosity, incongruity, discrepancy, control and self-
determination. Additionally, Malone and Lepper (1987) characterized intrinsic
motivation as fun, interesting, captivating, and enjoyable. Students usually experience
intrinsic motivation as fun. Lepper and Cordova (1992) found that students learned
more, retained more, and generalized (transferred) more of what they learned from
the educational activities they had rated as fun or had chosen to do. In that intrinsic
motivation is fun and involves all of the above mentioned components implies that
the love of learning inherently includes intrinsic motivation.
A key element in the definition of intrinsic motivation is that it includes an
affective component. Csikszentmihalyi (1988a) identified this affective component as
flow. He said scholars have found the concept of flow theoretically useful and that
flow has become a technical term in the field of intrinsic motivation (p. 3). He
contrasted more recent approaches to the study of intrinsic motivation from flow
research by pointing out that much intrinsic motivation research focuses on behavior.
Flow is subjective experience. It occurs when there is a balance of skills and the
challenge at hand (Csikszentmihalyi, 1990). This implies an optimal amount of
arousal. Scitovsky (1992) showed how human beings strive to maintain an optimal
7


amount of arousal by engaging in behaviors to reduce arousal when it is too high
(anxiety) and stimulate arousal when it is too low (boredom). People need change or
novelty to function, but not too much or too little. Thus, people need to maintain an
optimal amount of arousal. Csikszentmihalyi (1997) reported on many studies
comparing happiness, motivation, concentration, and flow with working, studying,
maintenance activities and leisure. Flow happens with work, driving, active sports
and hobbies, and socializing. Research on flow in learning has been descriptive and
limited. Several studies documented that, although flow occurs during learning, it is
the exception rather than the rule (Fredricks, Alfeld-Liro, & Eccles, 1999; Massimini
& Carli, 1988; Mayers, 1978; Nakamura, 1988). Csikszentmihalyi (1982) posited that
the flow experience may mean that intrinsically-motivated and self-rewarding
learning facilitates peak experiences (Maslow, 1968/1982). Csikszentmihalyi (1997)
argued that the happiness that follows flow is of our own making and leads to
increasing complexity and growth in consciousness.
Changes in complexity and growth in consciousness imply the involvement of
self. Indeed, several researchers have argued that personal causation (DeCharms,
1976), autonomy (Allport, 1955), competence (White, 1959), sense of mastery (Deci,
1980), and finding meaning and purpose (Suchman, 1971) are needs which ignite
intrinsic motivation. Thus far, research has shown relationships between these kinds
of needs and intrinsic motivation (Deci & Ryan, 1985b). A love of learning
disposition involves the agency of self, or rather the self as agency in that a
8


disposition expresses itself through personality. The love of learning is about the self
as more or less in charge of his or her life (Deci, 1995), as more or less competent in
various learning experiences (Deci, 1980), as growing and increasing in complexity
(Csikszentmihalyi, 1997) to a lesser or greater extent, and as having or creating a
meaningful or purposeful life (Suchman, 1971). The self becomes curiously engaged,
intrinsically motivated, and in effect, interested in either learning for its own sake or
in something to learn about.
Learning and the development Of the love of learning stems from ones
discovered interests. Research suggests that a general interest in learning may be an
important component in the love of learning (Bergin, 1999; Krapp, Hidi, &
Renninger, 1992). Most researchers acknowledge that interest originates from some
form of person-environment interaction. However, some researchers focus on the
former and others on the latter. The former is called individual interest (dispositional
interest or interest as a psychological state) whereas the latter is called situational
interest. Individual interest may be conceived of as a disposition or as a personality
trait. Dispositional interests are usually defined as relatively enduring preferences for
certain topics, subject areas, or activities (Renninger, 1990; Schiefele, 1990;
Scheifele, 1992). Recently, interest is conceived of as part of ones personality in
terms of orientations, valuations, and awareness of possibilities. Individual interests
have personal significance and thus are integrated into a value system and even
9


components of ones self-concept (Prenzel, 1992). Besides the positive feelings
associated with interest, or the cognitive value the person ascribes to the object of
interest, interest also has an intrinsic character. In other words learning about
something is undertaken for its own sake rather than an external reason. (Scheifele,
1992). The other side of the coin, situational interest, is identified by the
characteristics of a learning environment. Situational interest is considered an
emotional state aroused by situational stimuli or as an actualized state generated by
certain conditions and/or objects in the environment (Anderson, Shirey, Wilson, &
Fielding, 1987; Hidi, 1990; Krapp, Hidi, Renninger, 1992). Recently, researchers
have begun to explore the person-environmental interaction of individual and
situational interest. In the meantime, whereas situational interest may eventually be
considered an antecedent to the love of learning, it is dispositional, individual interest
that is a likely component of the love of learning.
Without specifically defining love of learning, several authors have suggested
how the love of learning may be nurtured. Factor analysis studies have uncovered a
factor best labeled as love of learning (Caracosta & Michael, 1986; Guglielmino,
1977; Michael, Denny, Ireland-Galman, & Michael, 1986). Research has been
conducted on what may be related concepts, such as curiosity, intrinsic motivation,
flow, and interest. Research regarding self as autonomous, competent, growing, and
purposeful provides guideposts to the conceptualization of the love of learning.
10


Defining love of learning involves examining how these diverse areas of investigation
converge. Bringing together the theoretical perspectives of several different research
areas to develop a definition for love of learning represents a new area of research.
With a definition of love of learning and a means to measure it, educators and
researchers may then develop better ways to nurture it.
Conceptual Framework
The theoretical framework is based on an integration of several motivation
theories and theories of learning. Love of learning seems to encompass a wide range
of concepts. Love of learning is like curiosity. Many have called curiosity an innate
drive to explore the unfamiliar. The unfamiliar may be cognitive, as in a problem to
be solved, or environmental, as in a novel or uncertain situation. Love of learning is
like intrinsic motivation in that a person enjoys learning for its own sake. One can
experience a positive feeling when intrinsically motivated and occasionally this
positive affect becomes flow and joy during learning. Love of learning may be
composed of a generalized interest in learning. Lastly, love of learning involves the
agency of self. The self experiences self-determination through a sense of autonomy,
competence, and mastery in learning. The self experiences growth and increasing
complexity in fulfilling its potential. Finally, the self seeks to find meaning and
purpose through learning. The theoretical framework in this study will include a
11


weaving together of the theories about curiosity, intrinsic motivation, flow, interest,
and the self-concept related to perceived autonomy, effectance, mastery, growth,
improvement, increasing complexity, meaning, and purpose.
Let us suppose for the purposes of this study that the love of learning exists as
a unifying disposition as part of a persons personality, or more specifically, self-
concept. Let us also suppose that this disposition is made up of a self-determining
desire for mastery or competence, to grow, improve, and increase in complexity thus
fulfilling ones potential, and to find purpose or to make meaning of ones life or
surroundings. Further, let us suppose that this disposition is composed of curiosity
that manifests as intrinsic motivation in selected areas of interest, tasks, or other such
undertakings, and that usually the affective experience is positive and sometimes flow
is achieved. From these suppositions a theoretical framework emerges.
The theoretical framework consists of three components. The three are
inherently interrelated but each provides a unique perspective. The first component is
the facet of the self-concept related to the desire to be self-determining, to achieve
mastery, to experience a sense of competence, to grow in complexity, and to find
purpose and/or create meaning. Deci (1995) referred to this facet as personal
autonomy. Knowles (1970) identified this aspect as self-direction. Maslow (1971)
referred to this facet as self-esteem and self-actualization. The second component is
curiosity, intrinsic motivation, and interest. These constructs are often conceived of as
12


the same thing (Berlyne, 1971; Starr, 1992) or as one subsuming the others (Lepper &
Malone, 1987). Curiosity is considered an inborn tendency (Wlodkowski & Jaynes,
1990) and intrinsic motivation is curiosity applied to a specific activity. Interest is
quite likely the selective persistence of curiosity (Prenzel, 1992) and preference to
engage in a domain of activities including learning. The third component is the
subjective and affective experience of intrinsic motivation, or flow. Figure 1.1
illustrates the combining of research areas into three categories and the
interrelationships among them.
Figure 1.1 Conceptual framework for love of learning
13


This framework provides the basis for defining love of learning and
developing an instrument to measure it. This framework aligns with Premise 5 and
five of the principles of the learner-centered psychological principles developed for
the American Psychological Association by the Presidential Task Force on
Psychology in Education (Lambert & McCombs, 1998). The premises and principles
are provided in Appendix A. However, in order to generate items to assess these
overlapping constructs, each construct needs to operationally defined. Operationally
defining each construct provides the dimension necessary for developing an adequate
measure for the love of learning construct.
Research Questions
The research questions of this study are:
1. What subconstructs comprise the overall construct of love of learning within the
young adult (18 to 25 years) age group?
2. What are the relationships among the subconstructs of the love of learning
construct within the young adult (18 to 25 years) age group?
3. What are the relationships between the love of learning construct and constructs
that likely should have strong correlations with the love of learning construct within
the young adult (18 to 25 years) age group?
14


Specifically, for positive model validity (Krathwohl, 1993), what is the
convergent relationship (Campbell & Fiske, 1959) between scores on the love of
learning measure and scores on a curiosity measure? And, what is the convergent
relationship (Campbell & Fiske, 1959) between scores on the love of learning and
scores on an intrinsic enjoyment measure?
Specifically, for negative model validity (Krathwohl, 1993), what is the
discriminant relationship (Campbell & Fiske, 1959) between scores on the love of
learning measure and scores on an anxiety measure? Also, what is the discriminant
relationship (Campbell & Fiske, 1959) between scores on the love of learning
measure and scores on a boredom measure?
4. What is the relationship between the love of learning construct and a construct that
likely should have an intermediate-size correlation with the love of learning construct
within the young adult (18 to 25 years) age group?
Specifically, for borderline validity (Krathwohl, 1993), what is the
relationship between scores on the love of learning measure and scores on a self-
actualization measure?
5. What is the relationship between the love of learning construct and a construct that
likely should have low or no correlation with the love of learning construct within the
young adult (18 to 25 years) age group?
15


Specifically, for contrary validity (Krathwohl, 1993), what is the relationship
between scores on the love of learning measure and scores on a flexible thinking
measure?
Methodology
To define love of learning required a synthesis of the literature from a number
of areas. From this synthesis operational definitions for each subconstruct were
developed. Once the subconstructs had been operationally defined, an item pool for
each subconstruct was generated and a self-report instrument to assess love of
learning was derived from the item pools. A group of experts in the areas of learning
and motivation assisted in the content validation of the instrument. The target age
group for the instrument is young adults from 18 to 25 years old. One sample was
used for the initial study of reliability and underlying relationships among
subconstructs of the instrument. A subset sample was used to examine further
evidence of construct validity. Students from several colleges were asked to
participate. Item analyses, internal consistency reliability, factor analyses, and
correlations among various subconstructs were conducted to examine the love of
learning construct and the reliability of the instrument. In addition to administering
the love of learning instrument, a battery of measures believed to correlate strongly,
weakly, or not at all with love of learning were administered to the subset sample.
Correlations with other measures were examined and a hybrid multitrait-multimethod
16


matrix was composed. In these ways, initial evidence regarding the validity of love of
learning was estimated and provided.
Structure of the Dissertation
This dissertation contains five chapters. The first chapter is an introduction to
the problem. Chapter two includes a review of the literature. Chapter three describes
the methodology. Chapter four provides the results of the study. Chapter five offers
discussion, implications, summary, and conclusion.
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CHAPTER 2
REVIEW OF THE LITERATURE
The idea of love of learning extends back through time. One could imagine,
for example, Solomon in 3500 B. C. standing before a great altar of the Lord asking
for wisdom above all (1 Kings 3:5-9, New International Version). Or perhaps one
could see Aristotle standing in the Lyceum at the Academy of Athens around 300 B.
C. and telling a group of students that wisdom is sweet and through wisdom,
happiness is gained. Although such examples suggest anecdotes that humankind has
valued the path of learning for thousands of years, we have not yet explored the
meaning of the love of learning. By extending our understanding in this direction, we
may be better able to influence children and students of all ages toward a love of
learning.
What background exists relevant to the love of learning? This chapter is
organized to present first a historical summary of philosophical thinking related to the
concept of love of learning. Second, in recent times, educators and psychologists have
investigated constructs closely related to the love of learning, such as curiosity,
intrinsic motivation, and interest. Research and findings in these areas that pertain to
18


the love of learning construct are summarized. Finally, implications are derived from
this review in terms of how the love of learning may be defined and measured.
Historical Perspective
Ancient Philosophers
Western European history provides a chronological stream of anecdotal
evidences that humankind has considered the love of learning and the achievement of
wisdom as pursuits of the highest purposes of life. The Biblical character of Solomon
desired wisdom more than 5000 years ago. Greek philosophers were preoccupied
with the desire to achieve excellence through continuous learning. Roman scholars
followed suit. And after a brief hiatus into the deep valuing of the love of God,
scientists, philosophers, and artists emerged during the Renaissance thirsting and
hungering for knowledge in a dramatic display of the love of learning. The following
summary captures some of that stream.
One of the earliest lovers of learning in western civilization was Solomon. He
pleased the Lord by asking for wisdom above all; he impressed the Queen of Sheba
with the extent of his understanding; and he taught his people of the value of wisdom
(1 Kings 3:5-9,1 Kings 10:6-8, Proverbs 19:8, Proverbs 22:17-18, Proverbs 24:14,
Ecclesiastes 7:12). Solomon declared that wisdom is pleasing to the soul (Proverbs
22:17-18).
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Much later the great Greek philosophers articulated the value of learning in
order to be happy. Sophocles (trans. 1998) ended his tragic play, Antigone, with the
chorus singing, The greatest part of happiness is wisdom (lines 1341-1342). Plato
(trans. 1989) lived in Athens during the Peloponnesian War, the destruction of the
Athenian empire, and the execution of Socrates. In a series of dialogs he reflected on
the teachings of Socrates. Repeatedly, he declared that the ultimate purpose of human
life is happiness and that happiness is achieved primarily through continuous
learning, or acquiring of wisdom. In Charmides, Plato demonstrated that a person will
be happy when he or she has knowledge (wisdom) (lines 174-176). In Euthydemus
Crito and Cleinias came to understand that happiness is experienced through the
acquisition of knowledge (line 282). In Symposium, Diotima described to Socrates
the search for true beauty, which ultimately leads to knowledge and bliss (lines 21-
212). In Meno Plato argued that wisdom generates happiness because through it
virtue is achieved (line 88c-d). In Apology, Plato showed how Socrates defended
himself to the Athenians as a seeker and lover of true wisdom and knowledge. In
Republic he indicated that the human souls calling is to seek wisdom, to hold to the
upward ways and pursue righteousness with wisdom always and ever (lines 61 le-
612c, 621b-d). Finally in Timaeus, he not only discerned two desires natural to
mankind, one for food and the other for knowledge (line 90a-c), but explicated that
the love of learning leads to happiness:
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But he who has been earnest in the love of knowledge and of true
wisdom, and has exercised his intellect more than any other part of
him, ..., will be singularly happy (line 90b-c).
Plato revered Socrates and characterized him as a philosopher and teacher who loved
to learn.
Plato also respected Aristotle, calling him the intellectual of the Academy at
Athens. Aristotle (trans. 1984/1952a), known as the Father of Logic, also connected
wisdom with happiness. However, for him, wisdom was derived from excellence in
functioning, self-sufficiency, and philosophic thought. In as much as philosophic
thought can be understood as learning, Aristotle concludes that learning is to be loved
for its own sake (Book X, 6-7, line 1177a). Aristotle (trans. 1984/1952b) also
declared that all men by nature desire to know (Book 1,1, line 980a). Greek
philosophers believed that happiness was achieved through continuous learning, and
that this learning process should be loved for its own sake.
For the most part the Roman scholars followed in the Greek philosophers
footsteps. They, too, were concerned with what was the highest good for man. Virgil
(trans. 1984/1952) portrayed the happy person as one who understands nature and,
therefore, controls his or her own fears (lines 490-493). Plutarch (trans. 1984/1952)
declared that those who do not use their inborn love of learning for bettering
themselves are not fulfilling their human purpose. Nicomachus (trans. 1984/1952)
stated that through learning, or the desire for wisdom, the ultimate goal of mankind,
21


which is happiness, is achieved (Chapter II, paragraph 3). Aurelius (trans. 1984/1952)
asked what could be more agreeable than learning because mankind depends on
learning for security and happiness (Book V, paragraph 9). Plotinus (trans.
1984/1952) agreed with Plato that wisdom begets happiness, but to have both requires
concentrating on what might be thought of as the highest good (Fourth Tractate,
paragraph 16). Roman scholars echoed Greek forerunners in their recognition of an
innate love for learning and their assumption that happiness is experienced through
learning.
Those threads were nearly lost when the rise of Christianity changed the
priorities of early philosophic thought in order to put the Divine Creator first. Virtue
and happiness were no longer valued in and of themselves, and so the role of learning
changed. St. Augustine (1984/400; 1984/413-426) thought little of learning but held
that happiness was obtained through knowing and revering God. Aquinas
(1984/1952) as well believed that happiness was experienced solely through
worshipful acknowledgement of the Heavenly Father. Neither believed that learning
fostered happiness. However, Dante (1984/1952) designed a synthesis for the
Christian religion and earlier philosophic thought by telling a personal story. Divine
Comedy told of enraptured learning by focusing on Infinite Goodness. His description
was not unlike Greek and Roman philosophy nor unlike early Christian faith.
While religion greatly influenced human thought in Western Europe,
commerce and governance remained influential as well. Acknowledgement of the
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love of learning is found in Chaucers (1984/1952) Canterbury Tales. Chaucer lived
in England and served Richard II and Henry IV. His travels to France and Italy during
the 100-year war with France contributed to his thinking. The Canterbury Tales
shows his ability to adopt multiple perspectives, and one of his most important voices
is that of the Clerk. Chaucer describes the clerk as one Whod turned to getting
knowledge, long ago... Pregnant of moral virtue was his speech; And gladly would he
learn and gladly teach (p. 164). The Clerk embodies the personality and voice of
people who loved to learn for the sake of learning.
As Western Europe emerged from the influence of religious dogma and
moved toward empirical reasoning and study, the disposition of the love of learning
was bom again. Controversial Hobbes exemplified one who loved learning during the
Renaissance. After his formal schooling, he avidly devoted himself to the study of
philosophy and mathematics. Although most of his published works represented
philosophical treatments of political problems and were source of controversy, in
Leviathan he created a classification scheme for passions, one of which is the desire
to know why, and how (p. 63). He identified this desire as curiosity and attributed it
solely to man.
Other Renaissance philosophers addressed the desire and pleasure of learning
as well. Hunt (1994) credited Locke as the first associationist because he argued that
we combine simple ideas to form complex ideas and that we learn by relating one
idea to another. Locke (1984/1952) also suggested that the increased complexity of
23


ideas by association provides pleasure. Hume (1738/1984) implied that curiosity is
innate and that the bringing of knowledge from obscurity to light (in other words,
learning) is enjoyable. In the Preface of his Critique of Pure Reason, Kant
(1781/1900) implied that reason (i.e. desire to know) is aroused by external stimuli:
Experience tells us what is, but not that it must be necessarily what it
is and not otherwise. It therefore never gives us any really general
truths; and our reason, which particularly anxious for this class of
knowledge, is aroused by it rather than satisfied (p. 2).
During the Renaissance, Europe was rediscovering the delights of learning.
This delight is reflected in several philosophers writings. Through these early
philosophers we find threads of thought that suggest a love of learning exists, that
curiosity is innate and aroused by external stimuli, and that learning is intrinsically
motivating, enjoyable in and of itself.
Early Educators and Psychologists
The arguments about human nature put forth by 18th century philosophers
became tested in practice by a number of 19th and 20th century educators and
psychologists. Educators frequently documented their observations that children
experienced joy in learning. For example, Pestalozzi (1915/1894) was concerned with
immediate perception. He found that by attending to the first beginnings for a long
time, students became aware of their own power to persist, succeed, and learn.
Through his attending Pestalozzi observed childrens joy of learning together and
24


teaching one another. As with Pestalozzi, Montessori (1964/1912) advocated for
education of the senses and also saw avid interest and great pleasure in learning
among children. Going beyond the immediate perceptions, Friedrich Froebel
(1974/1900) saw the joy children experience in their freshly experienced sense
impressions and in their newly acquired skills and believed that as children grow, so
does their natural desire to know:
Question upon question comes from the lips of the boy thirsting for
knowledge -- How? Why? When? What for? Of what? and every
somewhat satisfactory answer opens a new world to the boy ...
However, it is not alone the desire to try and use his power that
prompts the boy at this age to seek adventure ..; it is particularly the
peculiarity and need of his unfolding innermost life..., to comprehend
(the outer world) in its extent, its diversity, its integrity; it is the desire
to extend his scope step by step (p. 102-103).
However, he observed two kinds of desire for knowledge. He described the first as
the energetic, animating, uniting power and the second as the expansive,
productive, creative, modifying (extensive) power (p 133), noting that the second
increases with age as the first decreases.
Known as the founding father of American psychology (Hunt, 1994), William
James (James, 1890) was fascinated by learning, especially his own. He clearly stated
his opinion about the value of learning:
nothing is more congenial, from babyhood to the end of life, than to be
able to assimilate the new to the old, to meet each threatening violator
or burster of our well-known series of concepts, as it comes in, see
through its unwontedness, and ticket it off as an old friend in disguise.
This victorious assimilation of the new is in fact the type of all
intellectual pleasure. The lust for it is curiosity. The relations of the
25


new to the old, before the assimilation is performed, is wonder (pp.
524-525).
James believed that the love of learning is one of the best pleasures in life.
To summarize, from the Western European historical perspective, human love
of learning may be traced for thousands of years. The Biblical king Solomon sough
wisdom above all else. Greek philosophers held that achieving excellence through
continuous learning was the highest good. Roman philosophers concurred. Then,
emerging several hundred years later in Renaissance, a passion for learning was
demonstrated by scientists and reflected in the philosophical writings of that time.
Even educators through the late 19th century acknowledged in children as well as
themselves a joy or love of learning. In the early 20th century conceptual
underpinnings of the love of learning began to be studied more scientifically or
clinically, but not as love of learning per se. Rather, early scientists believed humans
had an instinct to learn. Usually, they referred to this instinct as curiosity.
26


Contemporary Research on Constructs
Related to Love of Learning
Curiosity
Curiosity is very likely a part of love of learning. Bronzaft (1996) drew this
connection when she stated that the source of love of learning lies in normal
childhood curiosity (p. 43). She believed that love of learning is rooted in curiosity
and that curiosity engenders learning. Implied in her belief is the notion that curiosity
is inborn. The belief that curiosity is innate has been a persistent thread in the
research literature for the past 50 years.
Voss and Kellers (1983) review traced the conceptualization of curiosity as
instinct, drive, intrinsically-motivated behavior, trait vs. state, and developmental
process. Spielberger & Starr (1994) focused particularly on Berlynes theory of
diversive and specific curiosity, research conducted to investigate the two constructs,
and how that research related to their theory of state-trait curiosity. Loewenstein
(1994), on the other hand, described curiosity research as occurring in two waves.
The first wave occurred in the 1960s and focused on three issues: what causes
curiosity, why people seek curious situations, and what are the situational
determinants. The second wave occurred in the 1970s and consisted mostly of
developing instruments for and measuring curiosity. Research on curiosity is vast and
rich, revealing fascinating results, overlapping and extending into other domains, and
fostering new fields for further study.
27


First Wave Issues
Before the first wave Loewenstein (1994) identified, early psychologists dealt
with the construct of curiosity. For example, James (1890) described two kinds of
curiosity. He emphasized the biological function of the first kind as an instinct-driven
behavior involved in approaching and exploring new objects. He stated that curiosity
and fear form a couple of antagonistic emotions liable to be awakened by the same
outward thing, and manifestly both useful to their possessor (p. 429). James defined
the second kind of curiosity scientific curiosity and metaphysical wonder with
which the practical instinctive root has probably nothing to do rather the
philosophic brain responds to an inconsistency or a gap in its knowledge (p. 430).
Jamess two kinds of curiosity coincide with Berlynes conceptualization and other
researchers studies of curiosity.
Another early psychologist who dealt with curiosity is McDougall.
McDougall (1912) defined instinct as an inherited or innate psycho-physical
disposition which determines its possessor to perceive, and to pay attention to, objects
of a certain class, to experience an emotional excitement of a particular quality upon
perceiving such an object and to act in regard to it in a particular manner, or, at least,
to experience an impulse to such action (p. 29). He identified curiosity as one of
eleven instincts and associated curiosity with the emotion of wonder. He thought that
curiosity was
28


the main source of intellectual energy and effort; to its impulse we
certainly owe most of the purely disinterested labours of the highest
types of intellect. It must be regarded as one of the principal roots of
both science and religion (p. 57).
McDougall believed there were individual differences in curiosity that increased or
decreased across the life span. McDougall did not distinguish two kinds of curiosity,
rather he saw intellectual curiosity as stemming from a curiosity instinct and
emotional wonder.
A third early psychologist who dealt with curiosity is Freud, who was actually
a psychiatrist with medical training. Freud did not specifically address curiosity.
Rather, he explained intellectual curiosity as stemming from scotophilia, sexual
curiosity, and sibling rivalry (Aronoff, 1962; Freud, 1959a, 1959b). Freud defined the
instinct for looking as scoptophilia, which causes a child to develop an intense
interest in sexual matters. Sexual curiosity starts when the child discovers and takes
pleasure in the sensations of his sexual organs. Pleasure becomes associated with
scoptophilia and develops at the age of three to five. He thought that scoptophilia is
why children investigate the world and become able to abstract knowledge. This
pattern of inquiry extended through adulthood. (Aronoff, 1962) Thus, Freud believed
that the thirst for knowledge seems to be inseparable from sexual life p. 153 (Freud,
1959b). On one hand Freud implied a link between curiosity and sexual interest. On
the other hand, he thought curiosity resulted from of a child fearing the loss of his/her
parents care and concern:
29


The childs desire for knowledge does not awaken spontaneously ... as
it would if prompted perhaps by an inborn need to seek for causes, but
arises under the goad of a self-seeking impulse which dominates him
when he is confronted by the arrival of a new child perchance at the
end of the second year. Those children whose own nursery at home
does not become divided up in this way are nevertheless able as the
result of their own observations to put themselves in the place of
others who are in this situation in other homes. The loss of the parents
care and concern ... has the effect of awakening the emotions of the
child and sharpening its thinking capacities (Freud, 1959a, p. 62).
Like Freud, Buhler (1928) had a background in biology. However, based on
his observations of children, Buhler offered an alternative explanation to Freuds
pleasure principle. He interpreted childrens play as providing pleasure through
movement and repetition, as well as skill acquisition and improvement. Thus,
children learned and improved from their play, while play provided joy. He saw no
connection to either sexual interest or fear of loss of parental love.
Piaget (1926), who was another biologist by training, believed that question-
asking behavior is biologically based. He thought that through question-asking a child
moved through various stages of intellectual development (i.e., sensori-motor, formal
operations). This account also lacks a connection to sexual interest or a fear of the
loss of love. It is rather part of a childs natural development.
Like McDougall, Freud believed intellectual curiosity grew out of instinct.
Freuds instinctual source as sexual, however, was quite different from McDougalls
instinctual source as wonder. Buhlers conception of instinctual curiosity is more
closely aligned with McDougalls and includes an element of self-improvement.
30


Piagets is very similar to both James and Berlynes ideas about curiosity, because
question-asking is epistemic and motivated by gaps in knowledge. James, like
Berlyne, thought intellectual curiosity was motivated by intellectual inconsistencies
rather than instinct. Of the five, Jamess and Piagets thinking most closely aligns
with Berlynes conceptualization and more recent research.
Berlyne is one of the most important early pioneers in the study of curiosity.
In 1950 he said, wonder, the source of the love of knowledge contains both
curiosity and cognitive surprise. It is aroused by anything extraordinary and difficult
to understand (p. 69). By 1954 Berlyne had identified two kinds of curiosity:
diversive and specific curiosity. Diversive curiosity was a stimulus-seeking behavior.
Specific curiosity included exploratory and epistemic curiosity (1954a). Defined as
the condition of discomfort, due to inadequacy of information, that motivates
specific exploration (p. 26) (1966), specific curiosity is provoked by conflicting,
surprising, puzzling, and unexpected stimuli (1954a). At first Berlyne theorized that
epistemic curiosity operated as a drive-reduction mechanism and much of his
taxonomy for curiosity is based on this theory. Later he modified this theory to
include optimal arousal along with drive reduction. A key aspect of his taxonomy of
epistemic curiosity is conceptual conflict. Conceptual conflict includes doubt,
perplexity, contradiction, conceptual incongruity, confusion, and irrelevance (1960).
He distinguished among the epistemic curiosity-arousing stimuli using the qualities of
novelty, complexity, surprise, and ambiguity. External stimuli may be collated
31


according to these qualities, which is why he called them collative variables. Further,
Berlyne said that epistemic curiosity may be kept alive with questions and that
conceptual conflict is reduced by information acquired through epistemic behavior.
Berlyne (1954b) conducted a study to demonstrate that surprising and
puzzling stimuli arouse epistemic curiosity. The experimental group received (a) a
questionnaire at the beginning about invertebrate animals, (b) a reading about the
animals which included answers to questions, and (c) a questionnaire at the end which
included questions. The control group did not have the questionnaire in the beginning.
Berlyne hypothesized that a questionnaire administered at the beginning would arouse
epistemic curiosity and he used answers to the post-test quiz and subjective reports as
measures of epistemic curiosity. The two groups differed significantly. He found that
(a) the questionnaire at the beginning tended to arouse curiosity, (b) the two measures
of curiosity (self-reported surprisingness and answers to questions after the reading)
were positively correlated, (c) questions about familiar animals and questions whose
concepts were incompatible arouse more curiosity than others, and (d) that surprising
statements were more likely to be recalled as answers than others. Frick and Cofer
(1972) replicated Berlynes study and found much the same thing. Also prompted by
Berlynes suggestion that the desire to know is evoked by surprising information,
Rossing and Long (1981) conducted a study to investigate the correlations between
curiosity evoked by surprise and of perceived value of information to the desire to
know more about psychological research topics. Their sample consisted of 79
32


volunteer adults from evening credit and non-credit classes ranging in age from 21 to
52 years. Although they found positive correlations between both surprise and
valuing and the desire to gain more knowledge, only the valuing relationship was
significant.
Berlynes research broke ground for others studying curiosity. For example,
Maw (1971) agreed with Berlyne that two kinds of curiosity were perceptual and
epistemic. Using Berlynes concept, Maw operationalized this distinction by
describing a curious child as one who (a) responds positively to new, strange,
incongruous things in the environment, (b) shows a need to know more about herself
and her environment, (c) scans her surroundings seeking new experiences, and (d)
persists in examining and exploring stimuli in order to know more about them. Using
a number of instruments, Maw examined curiosity in 5th graders. He found several
personality variables that distinguished between children with high and low curiosity.
Variables included level of self-acceptance, self-sufficiency, sense of security,
loyalty, square shooters, participation in group activities, social adjustment, and sense
of responsibility for group welfare.
Berlyne and Maw contributed to early thinking about curiosity but were by no
means the only ones. For example, Fowler (1965) also was immersed in the study of
curiosity. He discussed the history and theoretical conceptualizations of curiosity and
exploratory behavior. He discussed curiosity as instinct, drive, and response to
novelty, change, and complexity. He introduced the conceptualization of curiosity as
33


optimal arousal. Finally, he addressed the difficulty of determining whether curiosity
is personality expressed in individual differences or motivation.
Another often overlooked scholar is Arnold (1956), who presented a logical argument
for the existence of the desire to know. She argued that curiosity could not be an
instinct because it served no biological basis. She argued that curiosity could not be
accounted for with the classical conditioning model because many motivations would
have to be paired with some psychological need many times, and this was unfeasible.
Neither was drive theory a good explanation, she reasoned, because the desire to
know more is not an accident emerging as a secondary drive from basic drives. She
stated that all these theories were inadequate because each assumed that living beings
were inert, inactive and must be prodded into activity by drives or needs. She claimed
that not only are all of our senses active, but so are thinking, reasoning, judging, and
imagining. As human beings, we cannot help wanting to know about things, their
effect on us, and what we can do with or about them. Arnold believed that this active
process was more than just a problem-solving process as we search for problems
because they are fun.
Second Wave Measurement
Perhaps not realizing that they were acting out the very process described by
Arnold (1956), researchers began developing techniques for measuring curiosity.
There are approximately ten instruments purporting to measure curiosity in its various
34


forms. Spielberger and Starr (1994) related Berlynes theory of diversive and specific
curiosity to Zuckermans sensation seeking behavior and to their own theory about
state and trait curiosity. They introduced the concept of anxiety into the mix and used
Wundts curve to demonstrate that their theory may better explain curiosity. They
reported on several studies undertaken to investigate curiosity. Results indicate that
there are two components, directly related to epistemic and diversive curiosity.
Epistemic curiosity is information seeking; diversive curiosity relates mostly to
experience seeking. Spielberger and Starr introduced the Ontario Test of Intrinsic
Motivation (OTIM) (Day, 1968), Sensation Seeking Scale (SSS) (Zuckerman, Kolin,
Price, & Zoob, 1964), Novelty Experiencing Scale (NES) (Pearson, 1970), Academic
Curiosity Inventory (ACI) (Vidler & Rawan, 1974; 1975), Melbourne Curiosity
Inventory (MCI) (Naylor, 1981), and the State-Trait Curiosity Inventory (STCI)
(Spielberger, Butler, Peters, & Frain, 1976). Their list included perhaps the most
frequently used instruments, but was not all inclusive. Voss and Keller (1983) provide
a more comprehensive listing and description of curiosity measures. Appendix C
summarizes the psychometric information for most of the self-report curiosity
instruments developed during the second wave (Loewenstein, 1994)
Why were so many instruments about curiosity developed? One reason may
be that different theoretical constructions of curiosity were being proposed and tested.
Another reason is that different aspects of the curiosity construct were being
investigated. Last is that different measures were being developed for different
35


populations, however, this is apparent only in Penney and McCanns (1964) curiosity
measure for children. As the following descriptions of the most prominent measures
depict, curiosity was differentially conceived and measured. However, statistical
examination seemed to bring researchers back to Berlyne (1954a) and James (1890)
initial intuition that curiosity is composed of two components: information-seeking
and experience-seeking.
In 1964, Penney and McCann developed the Children's Reactive Curiosity
Scale (CRCS). Designed for students in the 4th, 5th, and 6th grade, the scale was
based on Berlynes definition of specific curiosity: (a) a tendency to approach and
explore relatively new stimulus situations (novelty), (b) a tendency to approach and
explore incongruous, complex stimuli (dissonance, complexity), and (c) a tendency to
vary stimulation in the presence of frequently experienced stimulation (variety).
Additionally in 1966, using the same concept of curiosity and psychometric approach,
Penney and Reinehr developed a Stimulus-Variation Seeking Scale for Adults
(SVSS).
Around the same time Garlington and Shimota (1964) developed the Change
Seeker Index (CSI). They defined change seeking as a habitual, consistent pattern of
behavior which acts to control the amount and kind of stimulus input a given
organism receives, stimulus input includes stimuli from both internal (ideational,
cognition) and external sources (p. 920). Garlington and Shimota believed that
change-seeking was a component of both diversive and epistemic curiosity. Also
36


around the same time Zuckerman produced the Sensation Seeking Scale (SSS)
(1964), a scale still used today. SSS was designed to quantify the construct: optimal
stimulation level, a component Berlyne (1960) later incorporated into his definition
of curiosity.
Pearson (1970) suspected that the instruments identified above were only
partially addressing curiosity, or more precisely, the novelty experiencing component
of curiosity. Therefore, she followed Fiske's (1966a) suggestion to use a conceptual-
operational strategy to construct her scale. Pearson constructed the Novelty
Experiencing Scale (NES) based on a 2-by-2 model of how novelty might be
experienced: external cognition, external sensation, internal cognition, and internal
sensation. She also constructed a 10-item Desire for Novelty Scale and defined the
desire for novelty as expressing the wish for new experiences and recognizing the
boring nature of every day life. She predicted that this scale would be independent of
the four scales comprising the NES. Her prediction was confirmed. Specific NES
scales were differentiated from each other and the global NES score. Thus, she
suggested that a number of relatively unique dispositions related to novelty might
exist, which curiosity measures had not yet captured. Most measures developed and
in use at that time assessed the external sensation component of experiencing novelty.
Some researchers were not as concerned with how curiosity was experienced.
Rather, they wondered if curiosity was a state aroused by stimuli in the environment
or an enduring trait of ones personality. This aspect of curiosity had not been
37


addressed and as a result, began to grow in importance. Camp and Dietrich (1985)
characterized this distinction in the following way: as a trait, curiosity is seen as an
enduring interest in acquiring new information. As a state, or contextually focused
activity, it is seen as epistemic curiosity, or the desire to seek (specific) knowledge
(p. 401). Researchers began to believe that some curiosity measures assessed state
curiosity and others assessed trait curiosity. About five methods for assessing
curiosity as a state or as a trait emerged. These include Days (1969) Ontario Test of
Intrinsic Motivation (OTIM) (1969), Leherisseys (1971a) 20-item State Curiosity
Scale (SCS), State Epistemic Curiosity Scale (SECS), Spielberger, Butler, Peters, and
Frains (1976) State-Trait Curiosity Inventory (STCI), Naylors (1981) Melbourne
Curiosity Inventory (MCI), and Vidler and Rowans (1974) Scale of Academic
Curiosity. See Appendix C for more detailed information.
Vidler and Rowan placed less emphasis on the sate-trait distinction of
curiosity. Their scale was based on earlier work by Chiu (1968). Chiu had developed
an instrument to assess academic motivation based on 16 variables comprising
academic motivation. One of the variables was curiosity. Administering the 278-item
survey to a sample of 285 eleventh graders, Chiu found six factors: curiosity, positive
orientation to learning, need for social recognition, academic ability, motive to avoid
failure, and reaction to expectation. Although Chius sample was small for the
number of items in the survey, Vidler and Rowan adapted the instrument and
administered it to 170 college students. Factor analysis revealed a five factor
38


structure. This finding was surprising because the authors had assumed that academic
curiosity was unidimensional, but not so surprising because the original instrument
had a six-factor structure.
Unlike Vidler and Rowans findings, factor analysis studies of the various
measures of curiosity more often than not revealed two factors. To test the hypothesis
of curiosity as a multifaceted construct, Langevin (1971) chose five measures of
curiosity, including teacher ratings and observations, and the Otis and Raven tests for
intelligence. This was a multi trait-multimethod approach. The sample was 195 6th
grade boys and girls. Factor analyses revealed two weak curiosity factors, which he
named breadth and depth of interest. Langevin was uncertain as to whether his results
reflected the different methods of assessment or whether he found evidence for a two-
factor curiosity construct. Ainley (1987) strengthened Langevins results by also
finding evidence for a two-factor curiosity construct. She administered five curiosity
scales to 227 college students. The scales represented a theoretical cross section of
curiosity as optimal arousal, cognitive processing, and state-trait. Her factor analysis
revealed two factors, which she also labeled breadth and depth of interest.
Somewhat in qualifying contrast, Boyle (1989) examined the factor structure
of curiosity as well. His study varied slightly because he conducted a factor analysis
of state-trait curiosity and state-trait anxiety using four scales, which he administered
to 300 high school students. His factor analysis showed six factors: a positive and
negative factor for each of state curiosity, trait curiosity, and state anxiety. Thus, his
39


findings imply a four factor structure for curiosity. However, if the positive and
negative factors are thought to represent a single continuum, his research might
support a two-factor structure for curiosity. Because of the instruments he used, his
factors define structure with regard to state and trait curiosity.
Lastly, Starr (1992) also assessed the relationships among various conceptions
of curiosity. She administered five instruments to 376 undergraduate students (60%
female). Her factor analyses revealed two factors. With these results, Starr argued that
curiosity is composed, as Berlyne posited, of an information seeking component and
an experience (sensation) experiencing component.
Summary
What can be said about curiosity? With some certainty, two things can be
said. First, researchers tend to agree that curiosity is inborn, but also believe that
curiosity is influenced by the environment. For example, Mohanty and Mishra (1991)
conducted an experiment with 40 four- to five-year olds. Giving one group a series of
tasks to help them grow intellectually and in curiosity, researchers found that this
group improved significantly more than controls in the short- and long-term effects in
both intelligence and curiosity. Their study shows how the environment can exert a
positive influence on the development of curiosity. The possibly negative influences
of the environment on curiosity development concern some researchers. Deci (1995)
and Wlodkowski and Jaynes (1990) have argued that natural curiosity declines as
40


children go to school and they attribute this decline to various aspects of the
schooling process. However, Camp and Dietrich (1985) found high levels of curiosity
in young, middle, and older adults, who took the OTIM. There are still some
unresolved issues and the nature-nurture debate remains complicated. Researchers
also seem to agree on a second aspect of curiosity. Curiosity is apparently composed
of two factors, an information-seeking or epistemic factor and an experience or
sensation-seeking factor. So far, no one has suggested that curiosity is not related to a
love of learning. Thus, Bronzafts (1996) inference that people who are curious and
look forward to learning develop a love of learning disposition seems reasonable.
Intrinsic Motivation
Intrinsic motivation grew up with, and in some ways out of, curiosity
research. As with definitions of curiosity, definitions of intrinsic motivation vary.
Some scholars (Berlyne, 1971; Day, 1969; 1971; Maw, 1971; McReynolds, 1971)
thought of curiosity and intrinsic motivation as the same construct. Other scholars did
not (Dember & Earl, 1957; Fowler, 1965). At least one common thread pulled the
various definitions of intrinsic motivation together. Intrinsic motivation refers to the
inherent nature of the activity itself (Lahey, 2001). Research on intrinsic motivation
moved beyond the bounds of curiosity in two specific ways. First, researchers
investigated the whys and wherefores of intrinsically motivating tasks. Several
taxonomies (Deci, 1980; Malone & Lepper, 1987; Young, 1961) emerged from this
41


research expanding the concept of intrinsic motivation. Second, extrinsic and intrinsic
motivation were examined. Several important theories of motivation emerged from
this second line of research. Extrinsic and intrinsic motivation research also
developed into an area of study on self-concept as competence. This section presents
definitions of intrinsic motivation, relevant research, and connects intrinsic
motivation to other constructs related to love of learning. However, in keeping with
the conceptual framework described in chapter one, the connection between intrinsic
motivation and self-concept as competence will be addressed later in the chapter as
part of the self-concept research related to the love of learning.
Definitions
Apparently, many researchers (Berlyne, 1971; Day, 1971; Maw, 1971) who
studied curiosity redefined their theories, models, and research in terms of intrinsic
motivation. For example, Berlyne (1971) described intrinsic motivation as motivation
aimed at certain internal consequences that constitute intrinsic reinforcements or
reward (p. 188). He further observed that novelty, complexity, surprise, and
ambiguity are all involved in intrinsic motivation. These were the collative variables
he developed in his research on curiosity. Secondly, Day (1969,1971) developed a
specific instrument entitled the Ontario Test of Intrinsic Motivation (OTIM) based on
Berlynes definition of curiosity. Indeed, Intrinsic motivation: A new direction in
education (1971), contained at least three chapters about research on curiosity
42


(Berlyne, 1971; Day, 1971; Maw, 1971). In a chapter on the assessment of intrinsic
motivation, McReynolds (1971) reviewed most of the instruments that had been
developed to assess curiosity implying the two constructs synonomity. Finally,
Beswick (1974) pointed out that curiosity is commonly taken to be the prototypical
example of intrinsic motivation (p. 15). Thus, many early researchers conceived of
curiosity and intrinsic motivation as much the same thing, even if they differed
regarding the essence of each.
Earlier than the confluence of research activity mentioned above, several
theorists occasionally referred to intrinsic motivation. For example, Woodworth
(1918) stated that a child, pursues an activity only when it is intrinsically interesting
to himself (p. 67). Troland (1928) developed the idea of human novelty-seeking as
intrinsically motivating. Murray and Kluckhohn (1953) introduced the idea of modal
activity, which is intrinsic activity governed by an effort to appreciate or achieve
excellence for its own sake. Hilgard and Russell (1950) distinguished between the
intrinsically and extrinsically rewarding relationships of tasks and goals. Maslow
(1954) implied that personal growth motivation is intrinsically motivating. Finally,
Herzberg, Mausner, and Snyderman (1959) defined motivator factors as intrinsic and
hygiene factors as extrinsic to job tasks. Seemingly, these theorists provided cairns
for later intrinsic motivation research.
Although the theorists mentioned above began exploring the intrinsic
motivation realm earlier or concurrently, the first use of the term intrinsic motivation
43


is commonly attributed attributed to Harlow, Harlow, and Meyer (1950) and Harlow
(1950) (Hunt, 1971; Voss & Keller, 1983). Harlow, Harlow, and Meyer (1950)
observed four rhesus monkeys who solved puzzles without extrinsic rewards. The
researchers postulated that the activity provided intrinsic reward. In a follow up study
Harlow (1950) found that two rhesus monkeys were intrinsically motivated to learn
how to solve a more complex puzzle and were intrinsically motivated to improve
their performance once they had learned to solve the puzzle. In summarizing research
on animals, Harlow (1953) argued for a motivation beyond basic needs and secondary
drives. He concluded that animals and humans have a natural desire to manipulate
and suggested that this desire is intrinsically motivated.
The idea that intrinsic motivation was a drive was difficult to release, yet the
definition that most researchers have come to accept is that intrinsic motivation is
derived from the activity itself. For example, Deci (1975a, 1980) described intrinsic
motivation as the activity itself being its own reward. He indicated that this definition
is a good operational definition because the key elements are observable, verifiable,
and quantifiable. Malone and Lepper (1987) used the words fun, interesting,
captivating, enjoyable, and intrinsically motivating interchangeably to describe an
intrinsically motivating activity that people engage in for its own sake. Wlodkowski
and Jaynes (1990) took the desire to learn, plus perseverance, valuing, and enjoyment
of learning into their meaning of intrinsic motivation, in which learning is a satisfying
and rewarding activity in and of itself. That intrinsic motivation is inherent in the
44


activity itself is central to research in the area. However, this essence has by no means
limited researchers conceptualization of intrinsic motivation. On the contrary, it
seems to have inspired several researchers imaginations. What follow are summaries
of several taxonomies that extended the initial meaning of intrinsic motivation.
Taxonomies
As early as 1961, Young identified four variables which he thought comprised
or affected intrinsic motivation. They are competence, effectance, autonomy, and
hedonism. The first three variables are addressed below in the review of self-concept
as competence. The fourth variable also is addressed below as flow. Youngs
taxonomy is somewhat incomplete because the variables he identified do not include
what is meant by an activity being inherently interesting in and of itself. Malone and
Lepper (1987) extend Youngs initial grouping by including inherent interest.
Malone and Lepper (1987) created perhaps the most comprehensive and
extensive taxonomy of intrinsic motivation. They specified two motivational
processes: the individual and interpersonal. Individual motivations include challenge,
curiosity, control, and fantasy. Interpersonal motivations are cooperation,
competition, and recognition. Although the interpersonal motivations are important
and interact in many ways with individual motivations, the individual motivations are
particularly relevant to defining the love of learning. They show connectedness with
the other components proposed here to be part of the love of learning. The following
45


paragraphs summarize the definition for each of the individual motivation
components in Malone and Leppers taxonomy.
The challenge component stems from common belief that people prefer an
optimal level of challenge. Challenge relates to effectance motivation (Harter, 1978;
White, 1959), perceived competence (Deci, 1975; Lepper & Green, 1978), flow states
(Csikszentmihalyi, 1975), and self-efficacy (Bandura, 1977). An activity is usually
challenging, when it involves goals whose attainment is uncertain. Lepper and
Malone (1987) suggested that intrinsic motivation involving challenge, competence,
effectance, or mastery motivation creates an image of humans as problem solvers.
Humans seek to solve problems and problems of intermediate difficulty are best.
Challenge is interconnected with several constructs proposed to be part of love of
learning. The challenge component is explored in greater depth below as part of flow
and self-concept as competence.
Curiosity (reviewed extensively above) is the second individual motivation
component. Malone and Lepper (1987) state that curiosity may be the most direct
intrinsic motivation for learning p. 235. Curiosity is aroused when there is an
optimal level of informational complexity (Berlyne, 1960, 1965) or an optimal level
of discrepancy or incongruity (Hunt, 1971; Piaget, 1951; 1952). In this case cognitive
curiosity refers to the natural drive toward ordering cognitive structures. Intrinsic
motivation involving curiosity, incongruity, or discrepancy evokes an image of
humans as information processors. Humans typically get pleasure from an optimal
46


level of surprise (Lepper & Malone, 1987). Research regarding optimal arousal or
discrepancy is further addressed as flow.
The third individual motivation component, control, is defined by (a) range of
outcomes that the environment provides, and (b) the extent to which the probability of
each outcome in contingent upon the responses of the person. The control component
is an important aspect of much of the research related to intrinsic motivation (e.g.
deCharms, 1968; Deci, 1975). Intrinsic motivation involving perceived control and
self-determination conjures an image of humans as voluntary actors. Humans become
intrinsically motivated when they feel they have personal control over meaningful
outcomes (Lepper & Malone, 1987). The control component appears most frequently
with research relating intrinsic motivation and feelings of efficacy and self-esteem.
As such, research findings about the control component of intrinsic motivation are
presented in self-concept as competence.
The final factor of the Malone and Lepper intrinsic motivation taxonomy is
fantasy. They state that fantasy is most likely to occur in an environment that evokes
mental images of physical or social situations not actually present. Malone and
Lepper often introduced fantasy as a component in their research of intrinsic
motivation (i.e., Lepper & Malone, 1987). The research of Malone, Lepper, and
others relating fantasy and intrinsic motivation is summarized later in this section.
Malone and Leppers taxonomy obviously encompasses a broad view of
intrinsic motivation. From this perspective the love of learning may be comprised
47


mostly of individual motivations of intrinsic motivation. Although fantasy is a means
of creating inherent interest, it is not the only way. Thus, Malone and Lepper do not
completely address inherent interest in an activity, which is the defining essence of
intrinsic motivation. However, interest as a research area has become a research area
in recent decades, and as such, is discussed below. In defining love of learning as a
dispositional construct, the construct of interest as well as inherent interest (intrinsic
motivation) are included.
The third taxonomy may be more accurately typified as two generalizations
about intrinsic motivation. Deci (1980) believed that intrinsic motivation is an
explanatory concept in two ways. First, organisms need an optimal level of
physiological or psychological stimulation. This approach explains behavior that
increases or reduces incongruity. The second way understands intrinsic motivation as
the felt need for competence. In this way intrinsic motivation is purposive and self-
directed. In both ways of explanation the need for optimal challenge exists. As
pointed out above, challenge, as part of and as well as these two generalizations, is
detailed below in the reviews of flow and self concept as competence research.
Decis generalizations are expansive but not as comprehensive or extensive as
Malone and Leppers taxonomy. What is evident among all three perspectives is the
theorists assumption that intrinsic motivation is intimately connected with self-
concept in terms of feeling efficacious, autonomous, competent, and in control.
However, the taxonomies captured more than this; intrinsic motivation means having
48


fun because an activity is inherently interesting. Young mentions hedonism. Malone
and Lepper introduce fantasy as one means to channel fun. Deci speaks of optimal
stimulation. Nonetheless, each taxonomy is limited in its expose of intrinsic
motivation as fun. In general, these taxonomies provided organizing principles for
understanding and extending the construct of intrinsic motivation and research about
intrinsic motivation in general.
Research
Intrinsic motivation. The study of intrinsic motivation has continued for at
least a quarter of a century. One body of research has focused on the intrinsically
motivating nature of various tasks, especially learning tasks. Another body of
research has focused on the contrast between intrinsic and extrinsic motivation.
Finally, several measurements of intrinsic motivation have been developed for
different age groups and a variety of purposes.
To examine the intrinsically motivating nature of a learning task, Ben ware and
Deci (1984) tested whether college students who learned with an active orientation
would be more intrinsically motivated and learn more than students who learned with
a passive orientation. The active orientation was created by having subjects learn
material with the expectation of teaching it to another student; the passive orientation
was created by having subjects learn the same material with the expectation of being
49


tested on it. Forty-three first year college students were randomly assigned to one of
the two conditions. Both groups were given three hours to study a 25-page
moderately difficult article about brain functioning. Subjects who learned in order to
teach were more intrinsically motivated, had higher conceptual learning scores, and
perceived themselves to be more actively engaged with the environment than students
who learned in preparation for a test. However, rote learning scores were the same for
the two groups. Benware and Deci concluded that intrinsic motivation grows out of
more active learning and results in increased conceptual understanding and self-
efficacy.
Using fantasy as a channel of intrinsic motivation in computer activities,
Malone (1981) found computer features most highly correlated with 65 school
childrens preferences included (a) whether or not the game had an explicit goal, (b)
scoring, (c) sound effects, and (d) randomness. These features relate to challenge
(goal), curiosity (randomness), control (scoring) and fantasy (sound effects). Malone
(1981) further discovered in an experiment with eighty 5th graders that external
embellishments in learning environments, in this case computer games, actually
influence intrinsic motivation. Lepper and Malone (1987) embedded identical
instructional sequences in activities that varied in motivational appeal. They found
that children chose the embellished game 50% more frequently, but that the
enhancements did not produce significantly different learning. Lepper and Cordova
(1992) reviewed studies that examined the congruence between intrinsic motivation
50


and educational goals in computer activities. In these computer activities success and
enjoyment depended on learning the subject matter presented. Overall, they found
that students learned more, retained more, and generalized (transferred) more of what
they learned from the educational activities they had rated as fun or had chosen to use.
Fantasy however, must be inherently related to content and educational goals or it
distracts from learning. Finally, Parker and Lepper (1992) examined intrinsic
motivation on the effects of embedding instruction in fantasy contexts on childrens
learning. Students in the fantasy condition showed greater learning and transfer than
students assigned to the no-fantasy condition. Results suggest first that fantasy is
related to intrinsic motivation as Malone and Leppers taxonomy suggests, and that
intrinsic motivation is related to learning and transfer.
In general studies such as these show that inherent interest in an activity is fun
when a fantasy factor is included. This factor affects learning when it is embedded
within the learning task. Inherent enjoyment of an activity varies with fantasy and
fantasy is a factor in the environment that can be manipulated. However, fantasy is
not the only feature in the environment that influences intrinsic motivation. Another
influential factor in the environment is extrinsic reward.
Intrinsic and extrinsic motivations and rewards. Theorists have argued that
that extrinsic rewards undermine intrinsic motivation. In 1964 Holt declared that
we destroy the ... love of learning ... in children by encouraging and
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compelling them to work for petty and contemptible rewards gold
stars, or papers marked 100 and tacked to the walls, or As on report
cards, or honor rolls, or deans lists, or Phi Beta Kappa keys (p. 274).
Montessori (1967) suggested that rewards were unnecessary and perhaps harmful.
More recently, Kohn (1993) also has been critical of extrinsic rewards stating that
they undermine intrinsic interest in an activity.
Through the 1950s, 1960s, and 1970s, research was conducted to determine
the affect of extrinsic rewards on a variety of dependent variables including
achievement, performance, and intrinsic motivation. After examining over 40 studies,
McGraw (1978) concluded that extrinsic rewards had a detrimental affect on
performance. Size of reward and age of participant did not affect this result. Although
more often than not the studies showed that rewards have a detrimental affect on
performance, McGraw qualified his conclusion because research results were not
definitive. He distinguished two aspects of the task that affected whether rewards
have a detrimental affect on performance. He labeled the first aspect attractiveness. If
a task is in any way intellectually challenging, then rewards have a detrimental affect
on performance. If a task is mundane such as lever pressing or vigilance, then rewards
sustain or improve performance. He labeled the second aspect algorithmic-heuristic
distinction. If the task requires participants to create a heuristic rather than to simply
follow an algorithm to complete the task, then extrinsic rewards have a detrimental
affect on performance. If a task involves the consistent application of a predetermined
52


algorithm, then rewards sustain or improve performance. In McGraws distinction
one can see challenge and competence coming into play. One sees that both extrinsic
and intrinsic rewards affect learning and performance.
Several meta-analyses have been conducted over the last 15 years. Rummel
and Feinberg (1988) reviewed 45 studies, Weirsma (1992) reviewed 16 studies, and
Tang and Hall (1995) reviewed 52 studies. All found support for the undermining
effect of rewards although Tang and Hall found that verbal rewards enhanced
intrinsic motivation. However, two meta-analyses challenged that conclusion.
Cameron and Pearce (1994) collected 96 experiments in which an experimental group
received a reward and a control group did not. They found no significant undermining
on most reward contingencies, although verbal rewards enhanced intrinsic motivation
on self-report and behavioral measures. Eisenberger and Cameron (1996) examined
two substes of the 96 studies using funnel graphs and found similar results. The first
subset included 61 studies in which the dependent variable was time spent on an
activity after reward was withdrawn from the experimental group. The second subset
included 64 studies in which the dependent variable was participants attitudes (task
interest, enjoyment, overall satisfaction) toward a task. These studies led Covington
(2000) to conclude that doing well gradewise does not necessarily interfere with
learning for its own sake. However, Deci, Koestner, and Ryan (1999) conducted a
meta-analysis of 128 studies. They found a significant undermining effect (Cohen
composite d = -.24). Their breakdowns of various categories likewise showed
53


consistent undermining effects in almost all categories. Exceptions include verbal
rewards for college students, unexpected rewards, and task-non-contingent rewards.
Csikszentmihalyi (1975) believed before so many studies were conducted, that
intrinsic and extrinsic motivations were neither inversely related nor mutually
exclusive. Conflicting results imply that this may be the case. In fact several scholars
developed perspectives which account for this. First, Deci (1980) suggested that
Cognitive Evaluation Theory (CET) explains how intrinsic motivation and extrinsic
rewards work together. CET states that whether intrinsic or extrinsic motivation is
involved depends on the interpretation (or of the salience) of either the controlling
aspect or the informational aspect of the reward. Of the controlling aspect, Deci
(1995) was still compelled to state that applying principles of reinforcement
undermine intrinsic motivation. Second, Middleton and Toluk (1999) explained how
learners engage in academic tasks either for intrinsic or extrinsic reasons because of
how they value a task. Middleton and Toluk focus on the value aspect of the
expectancy-value theory of motivation. Within the intrinsic framework, learners
compare an academic task with their prior experiences. If it is considered similar to
an interest, learners will engage as long as a task is stimulating (arousal) and as long
as learners feel a sense of control (autonomy) of outcomes. If a task is not considered
an interest, then learners consider extrinsic factors such as reward or avoiding failure
in a cost/benefit analysis of sorts where the expected reward must outweigh the
expected cost to engage.
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Intrinsic motivation is inherent interest in an activity itself. Researchers have
worked with this basic definition and extended it in many ways. Nonetheless,
instruments designed to assess intrinsic motivation have not always been based on
this essential conceptualization. As with research, scales designed to assess intrinsic
motivation have extended the initial definition.
Measures of Intrinsic Motivation
Several different measures of intrinsic motivation have been developed over
the years. Although many more have been developed for curiosity, some measures
seem to measure either or both curiosity and intrinsic motivation. For example, Day
(1969,1971) based the Ontario Test of Intrinsic Motivation (OTIM) on Berlynes
conceptualization of curiosity. Beswick (1974) developed a measure entitled
Curiosity Items to assess academic intrinsic motivation. He based his instrument
partially on Days OTIM. That curiosity and intrinsic motivation are often perceived
as the same is borne out by research by Starr (1992). After analyzing the results
comparing five curiosity instruments, including OTIM, Starr suggested that curiosity
is about the same as intrinsic motivation. However, several researchers have
developed measurements specifically to assess intrinsic motivation. Among them are
Harter (1981), Hamilton, Haier, and Buchsbaum (1984), and Gottfried (1982,1985,
1990).
Beswicks (1974) developed a 16-item assessment of academic intrinsic
55


motivation entitled Curiosity Items. Beswick derived the 16 items from Days OTIM,
Fitzgeralds (1966) openness to experience, Cattells (1957) curiosity erg factor, and
generated original items based on theory and research. Beswick found correlations
with other curiosity measures, general interest, interest in study subjects, perceived
competence of ability in a given subject, goals to attend college, and occupational
choices. Beswicks instrument captures a competence component suggested to be part
of intrinsic motivation. However, like Days OTIM, the scale demonstrates a strong
overlap between curiosity and intrinsic motivation.
The self-report instrument developed by Harter (1981) probably measures
intrinsic motivation more accurately than Beswicks scale. Developed for children in
third through ninth grade, Harters scale taps a childs intrinsic versus extrinsic
orientation toward learning and mastery in the classroom. She defined five separate
dimensions using an intrinsic and extrinsic pole: preference for challenge versus
preference for easy work, curiosity/interest versus teacher approval, independent
mastery attempts versus dependence on the teacher, independent judgment versus
reliance on the teachers judgment, and internal versus external criteria for
success/failure. Factor analyses revealed loading on the components of the scale, as
expected. Her factors in some respects parallel Malone and Leppers (1987)
taxonomy (challenge, curiosity, control), however fantasy is missing. Validity studies
reflect a good fit for the construct as she conceived it. Lepper, Sethi, Dialdin, and
Drake (1997) revised Harters scale to allow for the reporting of both intrinsic and
56


extrinsic motivation. They discovered that intrinsic and extrinsic motivation are not
perfectly inversely correlated, but have a weak negative yet significant correlation.
Hamilton, Haier, and Buchsbaum (1984) developed a self-report measure of
intrinsic enjoyment and boredom coping for adolescents and adults. They defined
intrinsic enjoyment as intense involvement, interest, and absorbed concentration.
They characterized boredom coping as a disposition to restructure ones perceptions
and participation in potentially boring activities so as to decrease boredom. Both traits
were hypothesized to reflect the capacity for good attentional control across a variety
of situations. Items include academic, work, and recreational situations. Although
Hamilton, Haier, and Buchsbaum examined attentional control, the intrinsic
enjoyment items reflect forced choice between intrinsically rewarding and
extrinsically rewarding experiences. Intrinsic enjoyment is significantly correlated
with an independent measure of intrinsic involvement (defined as a low wish to be
somewhere else), the affective experience of potency, self-reports of concentrating
with ease, high ego development, an internal locus of control, lack of boredom
susceptibility, and evoked potential (EP) indices of attentional change and cortical
augmenting. Boredom coping is associated with a higher percent of time actually
spent alone, high continuous performance task measures of attentional capacity, and
low Minnesota Multiphasic Personality Inventory (MMPI) and research diagnostic
criteria indices of psychopathology. Although this instrument seemingly
juxtapositions intrinsic motivation with boredom, the two scales are qualitatively
57


different. Specifically, intrinsic enjoyment reflects choice between inherent
enjoyment of an activity versus an extrinsic reward of outcome. The boredom scale
represents a forced choice between experiencing boredom or doing something about
it. The intrinsic enjoyment scale captures inherent interest in various activities and
also correlates with measures of control and competence.
Gottfried (1982,1985,1990) developed the Childrens Academic Intrinsic
Motivation Inventory (CAIMI) and the Young Childrens Academic Intrinsic
Motivation Inventory (Y-CAIMI). She first developed the former inventory for
children between the fourth and ninth grade. She later developed the latter inventory
for children between seven and nine years old. She defined academic intrinsic
motivation similarly for both age groups. Academic intrinsic motivation includes the
enjoyment of learning, an orientation toward mastery, curiosity, persistence, task
endogeny, and learning challenging, difficult, and novel tasks. The instrument for the
older group includes items about reading, math, social studies, science and school in
general. For the younger group excluded items about social studies and science.
Gottfried has demonstrated positive correlations with achievement, intelligence, and
perception of competence and negative correlations to anxiety.
To summarize, intrinsic motivation is related to a love of learning for two
reasons. First, its definition is inherent interest in an activity, in this instance learning,
reflects prima facie evidence for a love of learning. Second, intrinsic motivation
seems interrelated to other constructs that also seemingly relate to love lofe learning.
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For example, although a few early theorists offered several unique seedlings of
thought about intrinsic motivation, intrinsic motivation research is bound very tightly
at the hip with curiosity research. A majority of researchers saw the two constructs as
the same thing. However, specific research about intrinsic motivation grew into a
distinct area with two definite parts. One part focused specifically on intrinsically
motivating tasks. The other part focused on the contrast between intrinsic motivation
and extrinsic motivation. Measurement of intrinsic motivation has shown
relationships between intrinsic motivation and curiosity as well as intrinsic motivation
and challenge (further discussed with flow), intrinsic motivation and control
(discussed with both flow and self-concept below), and intrinsic motivation and
boredom (a variable in this study). Inherent interest in an activity remains the key
criteria for intrinsic motivation. However, it is evident that intrinsic motivation is
inherently interconnected with numerous variables related to the love of learning.
Flow
Flow is a natural offshoot of intrinsic motivation because flow is the
subjective experience of intrinsic motivation. Deci and Ryan (1985) said flow
represents a descriptive dimension that may signify some of the purer instances of
intrinsic motivation, when highly intrinsically motivated, organisms will be extremely
interested in what they are doing and experience a sense of flow (p. 29).
Csikszentmihalyi (1988a) explains that scholars have found the concept of flow
59


theoretically useful and that flow has become a technical term in the field of intrinsic
motivation (p. 3). One key difference between the two constructs is that intrinsic
motivation research focuses on behavior and flow research focuses on subjective
experience (Csikszentmihalyi, 1988a).
Definition
How is the subjective experience of flow characterized? Athletes describe
flow as being in the zone. Religious mystics describe flow as ecstasy. Artists and
musicians describe flow as aesthetic rapture (Csikszentmihalyi, 1997).
Csikszentmihalyi (1988b, 1990) defines nine components of flow. They are (a) a
balance of challenge and skill, (b) clearly defined goals, (c) immediate feedback, (d)
perceived sense of control, (e) the merging action and awareness, (f) absorbed
concentration, (g) loss of self-conscious awareness, (h) loss of a sense of time, and (i)
an autotelic self. Auto is Greek for self and telos is Greek for goal or purpose. The
autotelic self describes intrinsic motivation when a person is fully engaged in an
activity or goal for its own sake. Flow is an autotelic experience of an optimal state
that is universally experienced (Csikszentmihalyi, 1988c).
The first component of flow is the balance between challenge and skill. This
balance is pivotal not only for skill and challenge but for flow and non-flow
experiences as well. Challenge is by no means unique to flow. Malone and Lepper
(1987) identified challenge is part of a taxonomy of intrinsic motivation. Optimal
60


challenges, successfully met, lead to feelings of efficacy and competence. This
component connects the constructs of flow, intrinsic motivation and self-concept as
competence because the aspect of challenge is inherent in all three. The distinction is
primarily point of view. With flow, challenge is a component of the subjective
experience (Csikszentmihalyi 1988b, 1990). With intrinsic motivation, challenge is
part of a descriptive taxonomy of intrinsic motivation (Malone & Lepper, 1987). With
self-concept as competence, challenge is a variable (internal vs. external, arousing vs.
incongruous) that bridges ones subjective experience with feelings of efficacy and
competence or not (Deci, 1975; White, 1959). However, Csikszentmihalyi (1982)
also argues that the balance between challenge and skill fosters intrinsically-
motivated and self-rewarding learning. This kind of learning generates feelings that
Maslow (1967) described as peak experiences. In fact, Csikszentmihalyi (1982;
1988a) states that flow is similar to Maslows peak experience. Such an argument
implies that the challenge-to-skill balance of flow is also connected to self-concept as
growth, discussed below. Generally, the challenge-to-skill balance is integrated and
overlapping with four of the seven conceptual pieces defining love of learning.
Secondly, in order for an activity to be challenging, there must be goals whose
attainment is uncertain but perceived as achievable. Malone and Lepper (1987) state
that explicit goals of intermediate difficulty whose attainment is perceived as
achievable give direction and purpose. Such goals have been shown to enhance
intrinsic motivation (Malone, 1981; Malone & Lepper, 1987; Manderlink &
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Harackiewicz, 1984), performance (Dweck, 1986) and competence (Harter, 1978;
Manderlink & Harackiewicz, 1984). The sense that one is in the process of achieving
a goal describes part of the flow experience.
Combined with this sense is a third component, immediate feedback. As an
individual engages in an activity where goals are clearly defined, then feedback about
progress towards their achievement becomes part of the process. As an individual
progresses towards a goal and receives feedback that the goal is more nearly
achievable, his or her subjective experience is positively enhanced. Thus, an
individual becomes more engaged in the activity (Manderlink & Harackiewicz, 1984)
and more likely to experience flow. This process facilitates goal accomplishment. As
with the balance of challenge and skill, goals and feedback provide connectivity to
intrinsic motivation and self-concept as competence.
With the balance of challenge and skill, goals, and feedback, the perception
that one is in control, as another component of flow, fits within the intrinsic
motivation taxonomy (Malone & Lepper, 1987) and self-concept as competence
(DeCharms, 1968; 1976; Deci, 1980; Deci, 1995; Harter, 1978; Malone & Lepper,
1987; White, 1959). To experience flow, a person needs to feel that he or she is
actively involved, is doing something, is a moving force in the activity. Research has
demonstrated this in sports (Fredricks, Alfeld-Liro, & Eccles, 1999; Jackson &
Roberts, 1992), music (Fredricks, Alfeld-Liro, & Eccles, 1999), art (Massimini &
Carli, 1988), social activities (Massimini & Carli, 1988), work (Allison, & Duncan,
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1988; Delle Fave & Massimini, 1988, Lefevre, 1988; Neumann, 1999), leisure (Delle
Fave & Massimini, 1988; Lefevre, 1988), and learning (Chan, 1998, Fredricks,
Alfeld-Liro, & Eccles, 1999; Massimini & Carli, 1988, Mayers, 1978, Nakamura,
1988; Neumann, 1999). Control along with the three previously mentioned
components of flow also appear often in the research literature related to intrinsic
motivation and self-concept as competence.
The four remaining components comprising flow do not appear as frequently
in motivation research. They reflect expressions of conscious experience. Merging
action and awareness and concentration on an activity seem to be two sides of a coin.
As a person becomes more fully engaged his or her actions (cognitive, behavioral,
affective), he or she becomes less distracted by either external or internal stimuli. He
or she becomes increasingly absorbed, concentrating more fully on the activity such
that action and awareness merge into a singular experience. As this experience
continues, a person may lose not only his or her sense of self-consciousness but also a
sense of the passage of time. This conscious experience is like being fully asleep to
everything else and totally awake to, aware of, and absorbed in the activity of ones
attention, as if nothing else exists.
Optimal Arousal
With these nine components comprising flow, one cannot overlook the
possibility that the subjective experience of flow may be the subjective experience of
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optimal arousal or optimal incongruity. Indeed, the defining tone of the components
of flow taken together hinges upon the balance between challenge and skill, which of
itself seems illustrative of optimal arousal. This particular line of thinking hooks into
the conceptual understandings and research on curiosity (Berlyne, 1960; 1966;
Harlow, 1953), intrinsic motivation, (Day, Berlyne, & Hunt, 1971; Harter, 1981;
Hunt, 1971; Malone & Lepper, 1987), and self-concept as competence (DeCharms
1968; 1976; White, 1959). This optimal point, however, may be examined from at
least two points of view (Deci & Ryan, 1985); either it is stimulating or frustrating.
Researchers who have examined exploratory behavior (Fiske & Maddi, 1961),
novelty-seeking (Fowler, 1965; Scitovsky, 1992), and sensation seeking (Ainley,
1987) support the view of an optimal point as stimulating. As Hebb (1955) points out
no arousal no learning (p. 249). Researchers who have studied the discrepancy
model also offer evidence of an optimum in which rather than seeking stimulation,
the goal is to reduce incongruity or dissonance (Hunt, 1971). In a similar vein, the
goal to reduce uncertainty has also been perceived in terms of an optimum. This view
is so important to learning that Kagan (1972) defined the very wish to know as the
motive to resolve uncertainty (p. 54). This approach hearkens to Berlynes (1960)
research on curiosity (discussed above) where he identified incongruity and
uncertainty as two of the collative variables. Berlyne (1963) was able to incorporate
optimal psychological and physiological stimulation and incongruity into his
theoretical construct of intrinsic motivation.
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Whether seeking arousal or reducing incongruity, ones attention becomes
more concentrated. Hamiltons (1981) research demonstrates attention is positively
associated with absorbing interest and intrinsic enjoyment and negatively related to
boredom and psychopathology. Self-regulation of attention provides a fascinating
twist to the notion of optimal arousal because it implies that a person has some
control and choice in the matter. As such, attentional-regulation also connects flow
and self-concept as competence. Again, the overlap among the constructs of curiosity,
intrinsic motivation, flow, interest, as well as self-concept as competence seems clear.
Seemingly, flow is the subjective experience of optimal arousal or challenge.
The nervous systems of higher animals function to either increase or reduce
stimulation. Noteworthy are those experiences that are not optimum. When a person
is not aroused enough, often the experience is boredom. When stimulation exceeds
optimum, often the experience is anxiety. (Csikszentmihalyi, 1975; 1982,1997;
Scitovsky, 1992).
Research
Gross (1982) pointed out that Learning for its own sakethe so called joy of
learning has been cited often but rarely studied precisely (p. 166). Flow has been
studied across a wide range of activities around the world mostly among adolescents
and adults. Although flow is experienced when working and studying
(Csikszentmihalyi, 1997), research shows that adolescents most frequently experience
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flow in nonacademic activities such as sports, art, music, and socializing
(Csikszentmihalyi, 1997; Fredricks, Alfeld-Liro, & Eccles, 1999; Massimini & Carli,
1988). Nonetheless, Csikszentmihalyi (1982) reports that in ongoing studies of adults,
one third of their most enjoyable times are spent with intrinsically motivating
activities. Half of that third involves learning of some sort whether it is trying out a
new recipe or learning a new language. Csikszentmihalyi (1999) states that because
flow involves a balance between challenge and skill, it captures that essence of what
makes learning fun. Although the notion that learning is fun has remained largely
elusive to researchers, they have found evidence of flow in many activities in which
adults and adolescents participate.
Flow is subjectively experienced and seems to conceptually overlap with
intrinsic motivation, interest, self-concept as competence, and self-concept as growth.
Although studies demonstrate that flow is universally experienced, flow is less often
experienced during learning. Several reasons that may account for this are that (a)
learning environments do not often create an optimal challenge-to-skill balance, (b)
few studies have specifically focused on learning and flow, and (c) flow experienced
during learning is qualitatively different than flow experienced during other kinds of
activities. In spite of these shortcomings, as mentioned above, Csikszentmihalyi
(1982) argues that 15% of the best everyday experiences occur in the context of
learning (p. 175). Flow is a positive subjective experience defined as part of passion
(Fredricks, Alfeld-Liro, & Eccles, 1999; Neumann, 1999). Thus, one may infer that
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those who have a love or passion for learning are very likely to experience flow when
they learn and are also likely to experience more flow when learning than those who
do not have a great love of learning.
Interest
Love of learning develops from ones discovered interests. Educators and
psychologists have implied, over the last 100 years, that a connection between
interests and the love of learning exists. Dewey (1913) was persuaded that true
interest was the means through which individuals developed or became themselves.
He believed that it was useful to employ interests to educate a child pointing out that
in learning these things [interests] human offspring are brought to the need of
learning other things, and also to acquiring a habit of learning a love of learning
(p. 67). Thus, he provided some initial connectivity between the constructs of love of
learning and interest. In mid-century Arnold (1956) also drew a relationship between
interest and love of learning. Referring to love of learning as the desire to know, she
argued that a desire to know is innate but continues to develop over time. She
believed that once a childs interest is aroused, other problems related to schooling,
such as discipline, and so on, diminish.
In order to map the relationship between interest and the love of learning,
some historical background of interest will be presented. Second, the current
theoretical definitions for interest are provided. Next, that portion of the interest
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research hypothesized to relate to the love of learning is defined and reviewed. The
notion of interest has been around for a couple hundred years. Scholars, however,
hold different perspectives regarding what interest is and how to study it. How did
these various views of interest develop?
Historical Background
Early in the nineteenth century Herbart (1806/1977) developed a philosophy
of interest and early in the twentieth century Dewey (1913) introduced a theory of
education which connected interest and learning. Both Herbart and Dewey brought
out the idea that interest relates to lifelong learning and the self-initiated learning for
mastery, from which satisfaction is derived. However, much of the early interest
research grew out of vocational interest research (Holland, 1976; Walsh & Osipow,
1986) of the 1950s and 1960s (Schiefele, Krapp, & Winteler, 1992). Then in the mid
and late 20th century interest research waned as behaviorism waxed. Research on
interest did not disappear, rather interest research was subsumed within similar terms
such as attention (Eysenck, 1982), curiosity (Berlyne, 1960), emotion (Izard, 1970),
attitude (Evans, 1971), value orientation (Allport, Vernon, Lindzay, 1960),
motivation including achievement motivation (Atkinson & Raynor, 1974), intrinsic
motivation (Day, 1971, Deci, 1975, Deci & Ryan, 1985), and flow (Czikszentmihalyi,
1975). The labyrinth of intereconnections among these constructs exists today.
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Lately, interest has developed as a broad explanatory concept including both
motivation and cognition (Hidi, 1990, Krapp, Hidi, & Renninger, 1992; Renninger,
1984, Schiefele, Winteler, & Krapp, 1988). In fact, Schiefele, Krapp, and Winteler
(1992) refer to interest as cognitive motivation. Traditionally however, interest has
been researched as either individual or situational interest, reflecting the person-
environment interaction which characterizes interest behaviors. As such, interest has
two foci: influence of individual interests as topic-specific preferences and the effect
of interesting environmental factors that trigger a specific situational interest in the
learner (Nenninger, 1992). A third foci, topic interest, which combines individual and
situational interest, emerged at the turn of this century. Whether individual,
situational, or topic interest, both motivation and cognition are involved in the person-
environment interaction.
Theoretical Definitions
Most researchers acknowledge that interest originates from some form of
person-environment interaction. However, some researchers focus on the former and
others on the latter. The former is called individual interest whereas the latter is called
situational interest. Individual interest may be conceived of as a disposition or as a
personality trait. Situational interest occurs when a state of interest is aroused by
features in environment (Hidi, Renninger, & Krapp, 1992). However, topic interest
recently appeared on the radar screen as a third type of interest. Topic interest
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includes aspects of both individual and situational interest (Ainley, Hidi, Bemdorff,
2002). These distinctions are useful for organizing interest research, but how are the
several foci characterized?
On one side of the coin, individual interests are usually defined as relatively
enduring preferences for certain topics, subject areas, or activities (Renninger, 1990;
Schiefele, 1990; Schiefele, 1992). The activity may be narrow, as in tennis, or broad,
as in athletics (Deci, 1992). However, Deci (1992) indicates that the more broadly
one defines dispositional interest, the more broad can be the outcomes one predicts
(p. 50). Some authors define interest as simply an attitude (Evans, 1971; Gardner,
1975). Others say that dispositional interest includes attitudes, values, self-concept,
effectance, and origin motivation (Todt & Schreiber, 1998), implying that interests
are inherently part of the personality.
Individual interest has been conceived of as part of ones personality in terms
of orientations, valuations, and awareness of possibilities (Prenzel, 1992). Because
interests have personal significance, they become integrated into ones value system
and even become components of ones self-concept. In addition to the positive
feelings associated with interest, and the cognitive value the person ascribes to the
object of interest, interest also has an intrinsic character (Schiefele, 1992; 1998).
Learning about something is undertaken for its own sake rather than an external
reason.
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Renninger and her colleagues (Krapp, Hidi and Renninger, 1992; Renninger,
1987) argue that in addition to valuation, individual interest implies an accumulation
of stored knowledge about the object or activity of interest. They further specify
interest as the relationship between a class of objects and an individual to include
stored knowledge and value of which the person may not entirely aware. For these
reasons, scholars characterize individual interest as a disposition or personality trait.
On the other side of the coin, situational interest is defined by characteristics
of a learning environment. Situational stimuli arouse an emotional or actualized state
in the individual. This may be temporary or, by engaging in various activities, may
become a more enduring or dispositional interest (Anderson, Shirey, Wilson, &
Fielding, 1987; Hidi, 1990; Krapp, Hidi, Renninger, 1992).
Hidi (1990) says that situational interest is most frequently researched as text
comprehension and learning, usually in the form of text-based interest. Text-based
interest is a specific form of situational interest generated by reading interesting
sentences across subjects. This interest results from textual features as well as the
individual readers of the text. Research shows that interesting text and stories
motivate individuals to read and influence comprehension and learning.
Topic interest recently emerged in the literature to account for overlapping
conceptual boundaries and rather a lack of distinctiveness between individual and
situational interest. Bergin (1999) suggested that, it is not useful or accurate to claim
that a particular factor is purely personal or purely situational (p. 89). Hidi (1990)
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pointed out that individual and situational interest interact and influence each others
development. Thus, topic interest is defined as the result of individual and situational
interest interaction (Ainley, Hidi, Berdorff, 2002; Renninger, 2000). However, topic
interest is considered a form of individual interest because of its relatively enduring
evaluative orientation toward certain topics (Ainley, Hidi, Berdorff, 2002).
Interest, whether individual, situational, or topical is motivational. The two
motivation theories most frequently referred to in the literature are expectancy-value
theory and intrinsic motivation theory. Expectancy-value theory states that
individuals will engage in activities they find interesting and value but will persist in
activities where they experience success (Pintrich & Schunk, 1996). Intrinsic
motivation involves engaging an object, task, or activity for the inherent enjoyment
that accrues while doing so. Deci (1980) believes that interest is implicit in intrinsic
motivation and that flow and undivided interest are also intrinsic motivations.
Schiefele (1998) suggests that rather than expectancy-value where expectancy implies
more external consequences, interest may be considered activity-value motivation,
where there is flow, intrinsic motivation, and other affective states. This perspective
provides a synthesis of the motivation theories underpinning the concept of interest.
That aspect of interest pertaining to love of learning is interest in learning.
Ainley (1998) states that a students general motivational orientation to learning can
be viewed as interest in learning. (p 258). Ainley further distinguishes individual
interest in learning as a domain defined in terms of increasing knowledge,
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information, and understanding. She and her colleagues define individual interest in
learning as a desire to acquire new information, to find out about new objects,
events, and ideas not restricted to any narrow domain. This may involve approaching
and acquiring information about something novel or it may involve seeking new
information concerning something the student already knows about (p. 546, Ainley,
Hidi, & Bemdorff, 2002).
Difficulty in interpreting the research literature on interest occurs for several
reasons. One, the conceptual distinctions among individual, situational, and topic
interest are blurred. Two, the theoretical underpinnings of cognition, affect, and
motivation have not been clearly established. Three, interest is theoretically
interrelated with a number of other researchable constructs. The section of this field
of research that particularly pertains to love of learning is interest in learning.
Scholars suggest that a general interest in learning may be an important component in
the love of learning (Bergin, 1999; Krapp, Hidi, & Renninger, 1992). However, this
area of research has not been explored widely. What follows is a summary of research
relevant to a general interest in learning.
Research
Typically, results of research demonstrate that those who are interested in
particular activities pay closer attention, persist for longer, learn more, and enjoy
more (Hidi & Bemdorff, 1998; Hidi & Harackiewicz, 2000; Prenzel, 1992;
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Renninger, 1989, 1990; Schiefele, 1991; 1998). Some research has documented a
relationship between interest and achievement. Some research has shown
relationships among depth of interest, depth of learning, and satisfaction with
learning. Finally, some research has revealed a love of academic learning factor.
Taken together, interest in learning, academic or otherwise, indicates a possible love-
of-leaming trait.
Interest in learning usually is assessed with achievement. Schiefele, Krapp,
and Winteler (1992) conducted a meta-analysis of 121 studies and found reported
correlations between interest and achievement ranging from .09 to .67. Most
correlations were in the .2 to .4 range. Krapp, Hidi, and Renninger (1992) conclude
that the relationship between individual interest and academic achievement at best is
.3, but is a function of gender, school subject, and age/grade level. However, a
positive correlation between interest and achievement may not tell the entire story.
Other variables may be involved.
Prenzel (1992) studied 27 college-aged students who reported their
enjoyment, flow, and sense of competence for computers and guitars. Participants
with higher levels of interest, assessed as persistence, also experienced higher levels
of enjoyment, flow, and sense of competence. Though interest in computers or guitars
is not the same as a general interest in learning, Prenzels results reveal the process
and experience of interest in general. Thus, Prenzels findings are consonant with the
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definition of love of learning although not specifically focused on a general interest in
learning.
Ainley (1998) conducted several longitudinal studies of females by
administering the depth-of-interest curiosity scale (Ainley, 1986), quality of school
life scales, and Learning Process Questionnaires (LPQ) (Biggs, 1987) at the 7th, 9th,
and 11th grade level. Those who changed in their depth-of-interest (DOI) scores, also
scored differently on the quality of school life scales, and the LPQ. Differences
between the two groups were significant. Those who maintained high levels of depth
of interest were also satisfied with the quality of their schooling, and tended to score
higher on the deep and achievement oriented learning scales of the LPQ. Likewise,
those students whose DOI showed less satisfaction with schooling, tended to score
higher on surface-oriented learning scale. More recently, Ainley and her colleagues
(Ainly, Hidi, & Bemdorff, 2002) examined several mediating processes between
interest and learning. They found that topic interest related to affective response,
affect to persistence, and persistence to learning (p. 545). They found that individual
interest in learning was positively and significantly related to several mediating
variables in three of the four topics. Although they were unable to explore a full
model of contingencies, Ainley and her colleagues research implies that interest in
learning is related to deeper learning and a satisfaction with the learning experience.
Her studies tie together the interest, positive affect, and achievement threads of
interest in learning research.
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Ainley and her colleagues are developing an interest-in-leaming construct.
However, her construct is very strongly defined by Berlynes definition of curiosity.
On the other hand, other researchers have discovered a specific academic interest
factor. Caracosta and Michael (1986) developed the Dimensions of Self-Concept
(DOSC) instrument and administered it to 239 undergraduate college students.
Though the sample size was small, a factor analysis confirmed five subscales. One
factor was labeled Academic Interest and Satisfaction. Michael, Smith, & Michael
(1989) defined the academic interest and satisfaction factor as follows:
portrays the sheer love of learning and pleasure gained by students in
doing academic work and in studying new subject matter; an affective
state much like that realized by the dedicated scholar who gains
tremendous satisfaction in working in the library, in reading great
books, in writing research papers, and in conceptualizing new theories
or explanations for observed phenomena an intrinsic motivation
involving learning for its own sake (Michael, Smith, & Michael,
1989, p. 2).
Caracosta and Michael (1986) found significance between this factor and self-report
estimates of past and future grades, and specific grades in the class. These
correlations further affirm the relationship between interest in learning and
achievement as well as portray academic interest as including an affective state.
This particular construct appeared again in developing the Studies Attitudes
and Methods Scale (SAMS) (Michael, Denny, Ireland-Galman, and Michael, 1986).
SAMS has six scales. Each scale has five subscales with five items each. SAMS was
administered to 181 community college students. A principal components analysis
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identified five factors. One of the five factors was the Academic Interest love of
learning scale. The authors note that this factor defines a separate dimension but also
shares some variance with the general trait indicative of a positive orientation to study
effort. They defined this factor similarly to the definition for Academic Interest and
Satisfaction in the DOSC. Thus, there is some statistical evidence of an interest-in-
leaming factor, although the factor uncovered using these two instruments has a
particularly academic focus.
Research sheds light on interest in learning, and thus to some extent, the love
of learning. However, conceptual definitions overlap to such an extent that it is
difficult to see the forest for the trees. How can these overlapping meanings be
characterized?
Relationship of Interest to Other
Love of Learning Constructs
The complexity of theories and research on interest in learning comes from
the interconnected web of similar constructs. Researchers (Todt & Schreiber, 1998;
Schiefele, 1998) occasionally refer to curiosity, intrinsic motivation, flow, and sense
of competence synonymously with interest. Sheifele, Krapp, and Winteler (1992)
state that interest has been used interchangeably with terms such as intrinsic
motivation, subject-related affect, attitude, and cognitive motivation (p. 189). Bergin
(1999), who noted that a key to nurturing the appreciation for learning is catching and
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holding interest, identified attention, curiosity, and engagement as synonyms of
interest. How may these constructs be distinguished?
The strongest overlap seems to be with interest and curiosity. For example,
Ainley (1986; 1987; 1998; Ainley, Hidi, & Bemdorff, 2002) believes there are strong
connections between curiosity and interest. She administered 12 subscales from five
measures of curiosity to 227 college students. The factor analysis she conducted
showed two factors, which she labeled depth and breadth of interest (Ainley, 1986;
1987). In 2002 Ainley, Hidi, and Bemdorff defined depth-of-interest curiosity as
general interest in learning. However, Hidi and Anderson (1992) suggest specific
differences between curiosity and interest. They point to Berlynes (1974) research
with collative variables (novelty, complexity, surprisingness, ambiguity, variability).
The relationships between the collative variables and curiosity look like an inverted
U, whereas the relationship between the collative variables and interest is monotonic.
Hidi (1990) notes that life themes and character idenfitification are interesting but are
not collative variables. As constructs, curiosity and interest overlap but are not the
same.
Second in overlap strength is intrinstic motivation and interest. As previously
indicated, intrinsic motivation provides some the theoretical foundation for interest.
Deci (1998) states that interest is implicit in intrinsic motivation and that intrinsic
motivation occurs because an activity is interesting. Additionally, Hamilton, Haier,
and Buchsman (1984) characterize intrinsic enjoyment as intense involvement,
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interest, and and absorbed conentration. Research by Todt and Schreiber (1998)
shows that intrinsic motivation is very similar to interest. However, Rheinberg (1998)
points out that interest is activity-indifferent because many activities may bring a
person in touch with an object or area of interest. Intrinsic motivation, however, is the
desire to perform an activity and is inherent in the activity itself, with or without an
object of interest. Therefore, Hidi and Harackiewicz (2000) suggest that the two
constructs are recursively related to each other, one building on the other and so forth.
The two constructs seem closely connected although they are not the same. Appendix
B shows some of the various definitions for curiosity, intrinsic motivation, and
interest.
Often people believe that interest is the same as liking. However, Hidi &
Anderson (1992) distinguish between them. Berlyne (1974) found that liking reached
a peak at intermediate levels of uncertainty forming a curvilinear relationship whereas
interestingness increased linearly with uncertainty and did not decline. Iran-Nejad
(1987) found that surprise endings to stories do not affect liking but do affect
interestingness. He also showed that the outcome valence (goodness, badness) of a
story influences liking but not interestingness. Thus, interest in learning is different
than liking to learn.
In summary, among the overlapping constructs that comprise love of learning,
interest seems related to but different than curiosity and intrinsic motivation.
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Additionally interest is not same as liking. Thus, interest in learning offers a unique
aspect to the love of learning construct.
Summary
Interest in learning involves motivation, affect, cognition, and may be
portrayed as individual interest. Interest in learning seems to relate to curiosity and
intrinsic motivation. Research suggests that such a trait exists, and results in deeper
learning. Individual interest in learning is hypothesized to be an aspect of love of
learning.
Theorists, however, believe that this aspect is rare. Voss and Schauble (1992)
suggest that love of learning is the exception rather than the rule when they say some
individuals may want to learn for the sake of learning, although typically learning is
related to a more particular goal or interest (p. 105). Additionally, Hidi and
Harackiewicz (2000) note that all children have interests, motivation to explore, to
engage, but not all children have academic interests and motivation to learn to the
best of their abilities in school (p. 168). Thus, love of learning may be
conceptualized as a dispositional trait that includes a specific interest in learning.
Some theorists focus on how self-concept is involved in interest in learning.
William James (1890) noted that each of us literally chooses, by his way of
attending to things, what sort of universe he shall appear to himself to inhabit (p.
424). DeGarmo (1902) stated that
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interest is a feeling that accompanies the idea of self-expression. It has
its origin in the exhilaration, the sense of power, of mastery, that goes
with every internally impelled effort to realize a condition for the
survival of the self, whether such survival touch one aspect of the man
or another (p. 18).
Dewey (1913) noted that genuine interest indicates personal identification with a
course of action. Deci (1998) believes that intrinsic motivation and interest are
inherent in an innate self, which seeks to develop or actualize. Hannover (1998) states
that the development of self-concept and interests mutually influence each other (p.
117). Is there are relationship?
Self-concept in Terms of Competence,
Growth and Complexity, and Meaning and Purpose
The third circle of the conceptual framework for the love of learning construct
involves self-concept in terms of effectance, growth and complexity, and meaning
and purpose. Defining a disposition such as love of learning is difficult without
addressing how such a disposition pertains to ones self. For scores of years scholars
have been not only describing constructs such as curiosity, interest, intrinsic
motivation, and flow in terms of ones self or perception of oneself, but have
extended their writing, as well, to what the self or self-concept might be. Allport
(1955) for example, describes functional autonomy and propriate striving. DeCharms
(1968) and Heider (1958) outline personal causality and causation. Csikszentmihalyi
(1985; 1993) expounds on the increasing complexity of self. Maslow (1943,1967)
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defines self-actualization. For the love of learning conceptual framework, self-
concept in terms of competence, growth, and purpose represents an organizing
principle. As such it provides the who and why of love of learning as the other
constructs, i.e. curiosity, intrinsic motivation, interest, and flow, provide the
behavioral, cognitive, and affective manifestations of the what and how of love of
learning. In this section self-concept will be defined. In the following sections, the
fields of research relating to competence, growth, and purpose will be reviewed.
Self-concept
Maslow (1968/1982) defined self-concept as the ongoing actualization of
potential, capabilities, and talents, as fulfillment of mission, as a fuller knowledge and
acceptance of the persons own intrinsic nature, as a trend toward integration within a
person. Bandura (1977a) defined self-concept as an evaluative component where a
negative self-concept is a proneness to devalue oneself and a positive self-concept
was a tendency to favorably judge oneself. Marsh and Shavelson (1985) broadly
defined self-concept as a persons perception of him- or herself formed through
interpretations of ones experiences, including evaluations by significant others.
However, they believe that self-concept is multifaceted because people tend to
categorize information they have about themselves and relate these categories to one
another. Although scholars tend to agree with the multifaceted nature of self-concept,
defining specific facets has remained problematic. Marsh and Shavelson believe that
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self-concept may be divided into academic self-concept and non-academic self-
concept, where academic subjects comprise academic self-concept and social,
emotional, and physical self-concepts comprise non-academic self-concept. Michael,
Smith, and Michael (1989) developed a self-report inventory consisting of five
school-related factors of self-concept. The factors include level of aspiration, anxiety,
academic interest and satisfaction, leadership and initiative, and identification versus
alienation. The factor the authors define as academic interest and satisfaction
partially coincides with Marsh and Shavelsons academic self-concept as well as with
the love of learning construct. The authors define this factor as follows:
portrays the sheer love of learning and pleasure gained by students in
doing academic work and in studying new subject matter, an affective
state much life that realized by the dedicated scholar who gains
tremendous satisfaction in working in the library, in reading great
books, in writing research papers, and in conceptualizing new theories
or explanations for observed phenomena an intrinsic motivation
involving learning for its own sake (p. 2).
Other than this conceptual coincidence, the love of learning self-concept in term of
competence, growth, and meaningfulness does not fit well within Marsh and
Shavelsons hierarchy. Rather, it represents self-concept across all categories because
some manner of learning can and does take place across all the proposed categories.
In this study self-concept is conceived of as having three aspects relevant to
the love of learning construct. The three aspects are competence, growth and
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Full Text

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DEFINING AND MEASURING THE LOVE OF LEARNING by Terry Ann McFarlane B.A., California State University at Stanislaus, 1972 M.A . , St. Mary's University, 1981 A thesis submitted to the University of Colorado at Denver in partial fulfillment of the requirements for the degree of Doctor of Philosophy Educational Leadership and Innovation 2003

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by Terry Ann McFarlane All rights reserved.

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This thesis for the Doctor of Philosophy degree by Terry Ann McFarlane has been approved by Ellen A. Stevens William Goodwin Michael Marlow d.07J5 Date

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McFarlane, Terry Ann (Ph.D., Educational Leadership and Innovation) Defining and Measuring the Love of Learning Thesis directed by Associate Professor Ellen A. Stevens ABSTRACT The purposes of this study are to operationally defme the construct, love ojlearning, to develop an instrwnent to measure the construct, and to estimate the measure's reliability and validity. To define and measure the love oflearning construct, a comprehensive review of the research most closely related to love of learning was undertaken and a love oflearning instrument was developed. A 72-item pool for the instrument was generated following a framework of operational definitions and a table of specifications. Items were selected for the love of learning instrument using a five-person modified Delphi method. Interrater agreement and reliability were estimated for the item pool and instrument by three methods. Two of the three showed good agreement and reliability, but the repeated measures ANOVAs showed that most of the variance could be attributed to the rater or items by rater interaction (error tenn). The 25-item instrument was administered to students attending eleven institutions of higher education. Demographic mean differences were compared. Item consistency reliability was estimated at .92. Correlation analyses among the iv

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sub constructs and exploratory factor analysis were conducted. Validity was examined using correlational anlayses and a hybrid multitrait-multimethod matrix. Generally, the literature review, results of the surVey administration, and analysis of the measurement's psychometric properties suggest that the love of learning as a theoretical construct exists and varies individually among young adults. Although several problems emerged and the study had several methodological weaknesses, most evidence supports the argument that the instrument measures the love of learning construct. This abstract accurately represents the content of the candidate's thesis. I recommend its pubr f Signed • I -----Ellen A. Stevens v

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ACKNOWLEDGMENTS To Dr. Ellen A. Stevens, a very great friend and advisor, I wish to express my sincere gratitude and appreciation for her vision, wisdom, and guidance throughout my years in the doctoral program and especially for her encouragement, unfailing support, and deep commitment during the dissertation process. My gratitude and appreciation are given to Dr. Laura Goodwin as well, whose wonderful encouragement, insights, and expertise were especially empowering to me in the measurement and analyses phases of the dissertation. I also wish to thank Drs. William Goodwin, Michael Marlow, and Candan Duran-Aydintug for their advice regarding this study. I also wish to thank the members of my doctoral laboratory: Robert Davis, Noel LeJeun, Kim Peterson, Ellen Stevens, and Heidi Strang for serving as experts during the instrument development phase of the study, and to other members of the doctoral laboratory for their support and feedback to me during the process. My thanks also go to my running friends for supporting as well as distracting me during this dissertation process. Last but not least, I would like to thank my coach, Laurie Weiss, who having gone through this process at about the same time in her life and with her experience in writing books, was able to give me special help and guidance to encourage my writing.

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I dedicate this dissertation to the members of my family because of the various roles they play in my life. I dedicate this dissertation to my mom and dad for their unconditional love and support. Mom thought I was a genius and dad told me I could do anything I wanted to do. I dedicate this dissertation to my two beautiful daughters, who encouraged me and had great faith in me. I suppose they always have! And finally, I dedicate this dissertation to my spouse, Scott, who exercised patience beyond belief and provided stability and occasional computer support while I was engaged in this process.

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CONTENTS F . 19ures .................. . ............................................................ . ...................... XIV Tables ....................... . ............................................................................... xv CHAPTER 1. INTRODUCTION ................................................................................... 1 Purposes of the Study .... ; .. l • ••••••••• • ••••••••••••••••••••••••••••••••••••••••••••••••••• 1 The General Problem ............................... . ............ . ...... . .................. 1 Background of the Problem ...................... . ...................................... 3 Conceptual Framework ......................................... . ..... . . . . . ............. 11 Research Questions ............. . ...... . ............. . ...... . ............ . ................ 14 Methodology . . ....................... . ....................................................... 16 Structure of the Dissertation .......................................................... 17 2. REVIEW OF THE LITERATURE ............................................... . ....... 18 Historical Perspective .................................................................... 19 Ancient Philosophers ......................................................... 19 Early Educators and Psychologists .............................. . ... . 24 Contemporary Research on Constructs Related to Love of Learning ......................................................... 27 viii

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Curiosity ............................................................................ 27 First Wave Issues .................................................. 28 Second Wave Measurement.. ................................ 34 Summary ............................................................... 40 Intrinsic Motivation ........................................................... 41 Definitions ........................................................... . . 42 Taxonomies ........................................................... 45 Research ................................................................ 49 Measures of Intrinsic Motivation .......................... 55 Flow ................................................................................... 59 Definition .............................................................. 60 Optimal Arousal .................................................... 63 Research ................................................................ 65 Interest .... . .......................................................................... 67 Historical Background ........................................... 68 Theoretical Definitions .......................................... 69 Research ......................... ; ...................................... 73 Relationship of Interest to Other Love of Learning Constructs ................................. 77 Summary ............................................................... 80 ix

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Self-concept in Terms of Competence, Growth and Complexity, and Meaning and Purpose ........ 81 Self-concept ...................... . .................................... 82 Self-concept in Terms of Competence .................. 84 Self-concept in Terms of Growth and Complexity ....................................... ... .................. 92 Self-concept in Terms of Meaning and Purpose ... 95 Summary ...................... ... .................................... 101 3. METHODOLOGY ............................................................................. 104 Introduction .................................................... . ............................ 104 Design ......................................................................................... 106 Subjects and Sampling Procedures ............................................. 107 Variables ...................................................................................... 108 Love of Learning Variables ............................................. 108 Epistemic Curiosity ............................................. 109 Intrinsic Motivation ............................................. 109 Interest ................................................................. 110 Flow ..................................................................... 110 Self-concept in Terms of Competence ................ 111 Self-concept in Terms of Growth and Complexity .................................... . ..................... 111 x

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Self-concept in Terms of Meaning and Purpose. 112 Positive Model Variables ................................................ 112 Trait Curiosity ..................................................... 113 Intrinsic Enjoyment. ............................................ 113 Negative Model Variables ............................................... 114 Anxiety ................................................................ 115 Boredom .............................................................. 115 B orderline Variable ......................................................... 116 Self-actualization ................................................. 116 Contrary Variable ............................................................ 117 Flexibility ........................................ ... ............ ..... 117 Instrumentation ........................................................................... 118 Data Collection Procedures ......................................................... 121 Phase 1. Instrument Development.. ................................. 121 Phase 2. Reliability and Instrument Structure Study ....... 122 Phase 3. Construct Validity ............................................. 122 Data Analysis Procedures ............................................................ 122 Phase 1. Instrument Development.. ................................. 122 Phase 2. Reliability and Instrument Structure Study ....... 123 Phase 3. Construct Validity ............................................. 123 xi

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Limitations .................................................................................. 124 Summary ..................................................................................... 126 4. RESULTS ....................................................................................... ...... 128 Introduction ................................................................................. 128 Phase 1. Instrument Development.. ............................................. 129 Developing a Framework ................................................ 130 Table of Specifications .................................................... 134 Generating an Item PooL ................................................ 136 Selecting Items for the Survey ........................................ 136 Interrater Reliability ........................................................ 143 Phase 2. Reliability and Instrument Structure Study ................... 149 Data Collection ................................................................ 149 Participants ...................................................................... 150 Results ............................................................................. 151 Means and Mean Comparisons ........................... 151 Reliability and Item Analyses ............................. 155 Factor Analysis .................................................... 157 Phase 3. Construct Validity ......................................................... 165 Data Collection ................................................................ 166 Participants ...................................................................... 167 xii

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Results ............................................................................. 169 Means, Standard Deviations, and Reliabilities .... 169 Correlational Analyses ........................................ 169 Multitrait-multimethod ........................................ 172 Summary ..................................................................................... 175 5. DISCUSSIONS AND CONCLUSIONS ............................................ 178 Summaries and Interpretations .................................................... 179 Question 1 ........... ; ........................................................... 179 Question 2 ....................................................................... 185 Question 3 ....................................................................... 187 Question 4 ....................................................................... 191 Question 5 ....................................................................... 195 Limitations .................................................................................. 198 Theoretical Foundations, Implications for Practice, and Further Research ......................................................................... 202 APPENDIX A. Premises and Principles of the Learner-centered ModeL .................. 210 B. Definitions of Curiosity, Intrinsic Motivation, and Interest ............... 217 c. Psychometric Information about Various Curiosity Instruments ....... 223 D. Contact and Consent Letters ............................................................... 228 xiii

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E. Love of Learning Items and Sources .................................................. 233 BIBLIOGRAPHY ............................................................................................... 247 xiv

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FIGURES Figure 1.1 Conceptual framework for the love of learning .............................................. 13 4.1 Scree Plot ..................................................................................................... 158 5.1 Revised conceptual framework for the love of learning ............................... 184 xv

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TABLES Table 4.1 Number and percentage of items in initial pool and survey for each subconstruct.. .................. ........ ...... . ............ 141 4.2 Love of learning survey items ...................................................................... 142 4.3 Interrater agreement by round for the 72-item pooL ................................... 145 4.4 Repeated measures ANOVAs for the 72-item pool ..................................... 146 4.5 Interrater agreement by round for the 25-item survey ................................. 147 4.6 Repeated measures ANOV As by round for the 25-item survey .................. 148 4.7 Education level ................................ . ........................................... ........ ......... 151 4.8 Mean comparisons for demographic variables ............................................. 152 4.9 Tukey HSD mUltiple comparison post hoc test for educationallevel. ........................ ... ...... . ....................... ......... ................. ... ... 153 4.10 Tukey HSD multiple comparison post hoc test for marital status .............................. ...... .............. . ........................................... 154 4.11 Reliability analysis Scale (alpha): Item-total statistics ........................... 156 4.12 Tests for violations of the sphericity assumptions ...................................... 159 4.13 Factors and loadings comprising the love of learning instrument ........................................................................ 161 4.14 Correlations among love of learning construct and subconstructs ......................................................................................... 164 xvi

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4.15 Education level ......................................................................................... 169 4.16 Means, standard deviations, and reliabilities of validation scales ......................................................................................... 170 4.17 Correlations among the scales and instruments used for construct validation ................................................................................ 171 4.18 Variation of the multitrait-multimethod matrix .......................................... 173 xvii

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CHAPTER 1 INTRODUCTION Purposes of the Study The purposes of this study are to operationally define the construct, love of learning, to develop an instrument to measure the construct, and to estimate the measure's reliability and validity. This study is significant because it will add to the measurement (psychometric) literature. The practical significance follows from the theoretical significance. In knowing what a love of learning is, parents and educators may develop ways to nurture it so that it becomes a way of life . . The General Problem Bronzaft (1996) identified love of learning as the critical determinant in distinguishing successful academically high achievers (ARAs) from others. She interviewed 529 AHAs about their childhood experiences in the home and at school. Although she identified several potential properties and processes related to love of learning, she did not provide a specific definition. She did, however, draw a direct connection between achievement and love of learning. 1

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Berliner and Biddle (1995) drew a somewhat different connection. Their law of student achievement specifically states that "regardless of what anyone claims about students and school characteristics, opportunity to learn is the single most powerful predictor of student achievement" (p. 55). Though one may decry the lack of equitable opportunities in education, would anyone suggest that in any instance there are absolutely no opportunities to learn? Probably not. Therefore, while equitable opportunities to learn are important, creating and using existing opportunities to learn are as important. According to Berliner and Biddle (1995), more students are graduating from high school; more students are attending college; and more students are earning college degrees than in previous decades. Apparently, teachers and students are sufficiently creating and using educational opportunities. Or are they? The evidence that students in America are attaining higher levels of education may not tell the whole story. Experts point out that children enter schools eager to learn but lose that eagerness too soon. Wlodkowski and Jaynes (1990) suggested that this decline is to be expected for several reasons: (a) learning in school occurs in groups with formalized curriculum and grading system, (b) advanced learning becomes increasingly complex, and (c) learning is hampered by many distractions in the world. Massimini and Carli (1988) studied forty-seven 16to 19-year-olds and concluded that they derived enjoyment more from art, hobbies, and socializing than 2

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academic pursuits. Fredricks, Alfeld-Liro, and Eccles (1999) studied self-reported interest in sports, music, and math across the grades. They concluded that the passion to learn is rare and that passion more frequently characterized non-academic achievement activities. Indeed, students may be learning more and enjoying it less. What may be needed more than increased and equitable opportunities to learn is nurturing the eagerness to learn apparent in young students such that a disposition towards a love of learning unfolds in young adults. Such a disposition would give every student something more than economic self-sufficiency, essential as it is. Love of learning would give students the key to self-fulfillment for the rest of their lives. First, however, it is essential to define what is meant by a love of learning. When love of learning is referenced, it is rarely defined. Background of the Problem The assertion that little research has been conducted specifically about the love of learning needs to be qualified. For one, Bronzaft's (1996) study of academically high achievers (ARAs) inferred a great deal about the love of learning. Second, several measurement studies revealed a factor dubbed love of learning or academic interest. Usually, this was in the context of validating a measure for some kind of motivation, study attitudes, academic self-concept, etc. Third, much research has been conducted in several conceptually related areas. For example, curiosity, 3

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intrinsic motivation, flow, interest, and self-concept in terms of competence, growth, and purpose have been studied extensively and may partially comprise what love of learning is. Bronzaft (1996) interviewed many AHAs. Her interviews revealed the importance of home and family in the development of a love of learning. She concluded that the love of learning lies in normal childhood curiosity. She suggested that the following conditions were instrumental in fostering a love of learning: (a) emphasis on reading, (b) parents who value learning, (c) love of learning as a family tradition, (d) teachers who foster love of learning by making a student feel proud and worthwhile, (e) pleasure that comes from doing one's best rather than winning, and (f) love of learning as a way of life. Though she clarified the conditions for fostering a love of learning, Bronzaft never really defined what she meant by love of learning. In attempting to measure such constructs as academic self-concept, study attitudes and methods, and self-direction, researchers have repeatedly uncovered a factor for which love of learning is an apt label. For example, Guglielmino (1977) developed an instrument to assess self-directed learning readiness (SDLR) as part of her doctoral dissertation. Using factor analysis, she identified eight factors and labeled one of them love of learning. In exploring school-related factors of self-concept, Michael, Smith, and Michael (1984) developed a measure entitled Dimensions of Self-Concept (DOSC). 4

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They uncovered five factors and labeled one of the factors Academic interest and satisfaction. They defined this factor as the sheer pleasure gained by students in studying and in doing academic work, much like that experienced by the dedicated scholar who gains great satisfaction in working in the library, in writing papers, and in reading the great books an intrinsic motivation involving love of learning for its own sake (p. 2) . Two years later, Michael, Denny, Ireland-Galman, and Michael (1986) conducted a factorial validity study of the Studies Attitudes and Methods Scale (SAMS). They labeled one of the six factors, Academic interests love of learning. The authors defined this factor very similarly to the academic interest and satisfaction factor of the DOSe. Academic interests love of learning is intrinsic motivation involving learning for its own sake. Thus, there is some psychometric evidence for the existence of a love of learning construct. Although factor analysis alone is insufficient, these studies provide the beginning of a conceptual definition. One infers by studying the descriptions of the factors described above and examining the nature of the items comprising those factors, that love of learning probably consists of curiosity, intrinsic motivation, a positive affective state (flow), self-concept, and interest. Indeed, research literature on these constructs is replete with implications that they are part of and relate to a joy of, love of, enthusiasm for, eagerness for, and desire for learning. 5

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Researchers of curiosity have reached a tentative consensus that curiosity is composed of two factors. Several studies have demonstrated a two-factor solution (Ainley, 1987; Langevin, 1971; Naylor, 1981; Spielberger & Starr, 1994; Starr, 1992). Usually, the two-factors solution forms an epistemic curiosity or information seeking component and a diversive curiosity or experience-seeking component (Spielberger & Starr, 1994; Starr, 1992). Interestingly, Berlyne (1950) originally conceived of curiosity as comprised of two such factors. The former factor is more part of the love of learning because learning more often refers to knowledge acquisition in academic subjects rather than sensational and novel experiences in life. Some researchers have suggested that curiosity and intrinsic motivation are the same thing (Starr, 1992; Lepper & Malone, 1987). They may draw this conclusion in part because eventually Berlyne integrated many of his original ideas regarding curiosity (Berlyne, 1950) with intrinsic motivation (Berlyne, 1971). Although the research regarding intrinsic motivation and curiosity is curiously distinct, the two constructs seem bound to the same dimension of human behavior (Harlow, 1953). This may be because early theorists postulated that either construct was activated by instinct or a drive mechanism and approached research from a behavioristic or psychoanalytic tradition. Recently, however, researchers have taken a more organismic approach (Deci, 1975). Intrinsic motivation has been defined as "human motives stimulated by the 6

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inherent nature of the activity or its natural consequences" (Lahey, 1998, p. 341). Lepper and Malone (1987) greatly elaborated this definition by including in their definition of intrinsic motivation the concepts of challenge, competence, effectance, mastery orientation, curiosity, incongruity, discrepancy, control and self determination. Additionally, Malone and Lepper (1987) characterized intrinsic motivation as fun, interesting, captivating, and enjoyable. Students usually experience intrinsic motivation as fun. Lepper and Cordova (1992) found that students learned more, retained more, and generalized (transferred) more of what they learned from the educational activities they had rated asfun or had chosen to do. In that intrinsic motivation is fun and involves all of the above mentioned components implies that the love of learning inherently includes intrinsic motivation. A key element in the definition of intrinsic motivation is that it includes an affective component. Csikszentmihalyi (1988a) identified this affective component as flow. He said scholars have found the concept of flow theoretically useful and that "flow has become a technical term in the field of intrinsic motivation" (p. 3). He contrasted more recent approaches to the study of intrinsic motivation from flow research by pointing out that much intrinsic motivation research focuses on behavior. Flow is subjective experience. It occurs when there is a balance of skills and the challenge at hand (Csikszentmihalyi, 1990). This implies an optimal amount of arousal. Scitovsky (1992) showed how human beings strive to maintain an optimal 7

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amount of arousal by engaging in behaviors to reduce arousal when it is too high (anxiety) and stimulate arousal when it is too low (boredom). People need change or novelty to function, but not too much or too little. Thus, people need to maintain an optimal amount of arousal. Csikszentmihalyi (1997) reported on many studies comparing happiness, motivation, concentration, and flow with working, studying, maintenance activities and leisure. Flow happens with work, driving, active sports and hobbies, and socializing. Research on flow in learning has been descriptive and limited. Several studies documented that; although flow occurs during learning, it is the exception rather than the rule (Fredricks, Alfeld-Liro, & Eccles, 1999; Massimini & Carli, 1988; Mayers, 1978; Nakamura, 1988). Csikszentmihalyi (1982) posited that the flow experience may mean that intrinsically-motivated and self-rewarding learning facilitates peak experiences (Maslow, 1968/1982). Csikszentmihalyi (1997) argued that the happiness that follows flow is of our own making and leads to increasing complexity and growth in consciousness. Changes in complexity and growth in consciousness imply the involvement of self. Indeed, several researchers have argued that personal causation (DeCharms, 1976), autonomy (Allport, 1955), competence (White, 1959), sense of mastery (Deci, 1980), and finding meaning and purpose (Suchman, 1971) are needs which ignite intrinsic motivation. Thus far, research has shown relationships between these kinds of needs and intrinsic motivation (Deci & Ryan, 1985b). A love of learning disposition involves the agency of self, or rather the self as agency in that a 8

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disposition expresses itself through personality. The love of learning is about the self as more or less in charge of his or her life (Deci, 1995), as more or less competent in various learning experiences (Deci, 1980), as growing and increasing in complexity (Csikszentmihalyi, 1997) to a lesser or greater extent, and as having or creating a meaningful or purposeful life (Suchman, 1971). The self becomes curiously engaged, intrinsically motivated, and in effect, interested in either learning for its own sake or in something to learn about. Learning and the development of the love of learning stems from one's discovered interests. Research suggests that a general interest in learning may be an important component in the love of learning (Bergin, 1999; Krapp, Hidi, & Renninger, 1992). Most researchers acknowledge that interest originates from some form of person-environment interaction. However, some researchers focus on the former and others on the latter. The former is called individual interest (dispositional interest or interest as a psychological state) whereas the latter is called situational interest. Individual interest may be conceived of as a disposition or as a personality trait. Dispositional interests are usually defined as relatively enduring preferences for certain topics, subject areas, or activities (Renninger, 1990; Schiefele, 1990; Scheifele, 1992). Recently, interest is conceived of as part of one's personality in terms of orientations, valuations, and awareness of possibilities. Individual interests have personal significance and thus are integrated into a value system and even 9

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components of one's self-concept (Prenzel, 1992). Besides the positive feelings associated with interest, or the cognitive value the person ascribes to the object of interest, interest also has an intrinsic character. In other words learning about something is undertaken for its own sake rather than an external reason. (Scheifele, 1992). The other side of the coin, situational interest, is identified by the characteristics of a learning environment. Situational interest is considered an emotional state aroused by situational stimuli or as an actualized state generated by certain conditions and/or objects in the environment (Anderson, Shirey, Wilson, & Fielding, 1987; Hidi, 1990; Krapp, Hidi, Renninger, 1992). Recently, researchers have begun to explore the person-environmental interaction of individual and situational interest. In the meantime, whereas situational interest may eventually be considered an antecedent to the love of learning, it is dispositional, individual interest that is a likely component of the love of learning. Without specifically defining love of learning, several authors have suggested how the love of learning may be nurtured. Factor analysis studies have uncovered a factor best labeled as love of learning (Caracosta & Michael, 1986; Guglielmino, 1977; Michael, Denny, Ireland-Galman, & Michael, 1986). Research has been conducted on what may be related concepts, such as curiosity, intrinsic motivation, flow, and interest. Research regarding self as autonomous, competent, growing, and purposeful provides guideposts to the conceptualization of the love of learning. 10

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Defining love of learning involves examining how these diverse areas of investigation converge. Bringing together the theoretical perspectives of several different research areas to develop a definition for love of learning represents a new area of research. With a definition of love of learning and a means to measure it, educators and researchers may then develop better ways to nurture it. Conceptual Framework The theoretical framework is baSed on an integration of several motivation theories and theories of learning. Love of learning seems to encompass a wide range of concepts . Love of learning is like curiosity. Many have called curiosity an innate drive to explore the unfamiliar. The unfamiliar may be cognitive, as in a problem to be solved, or environmental, as in a novel or uncertain situation. Love of learning is like intrinsic motivation in that a person enjoys learning for its own sake. One can experience a positive feeling when intrinsically motivated and occasionally this positive affect becomes flow and joy during learning . Love of learning may be composed of a generalized interest in learning. Lastly, love of learning involves the agency of self. The self experiences self-determination through a sense of autonomy, competence, and mastery in learning. The self experiences growth and increasing complexity in fulfilling its potential. Finally, the self seeks to find meaning and purpose through learning. The theoretical framework in this study will include a 11

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weaving together of the theories about curiosity, intrinsic motivation, flow, interest, and the self-concept related to perceived autonomy, effectance, mastery, growth, improvement, increasing complexity, meaning, and purpose. Let us suppose for the purposes of this study that the love of learning exists as a unifying disposition as part of a person's personality, or more specifically, self concept. Let us also suppose that this disposition is made up of a self-determining desire for mastery or competence, to grow, improve, and increase in complexity thus fulfilling one's potential, and to find purPose or to make meaning of one's life or surroundings. Further, let us suppose that this disposition is composed of curiosity that manifests as intrinsic motivation in selected areas of interest, tasks, or other such undertakings, and that usually the affective experience is positive and sometimes flow is achieved. From these suppositions a theoretical framework emerges. The theoretical framework consists of three components. The three are inherently interrelated but each provides a unique perspective. The first component is the facet of the self-concept related to the desire to be self-determining, to achieve mastery, to experience a sense of competence, to grow in complexity, and to find purpose and/or create meaning. Deci (1995) referred to this facet as personal autonomy. Knowles (1970) identified this aspect as self-direction. Maslow (1971) referred to this facet as self-esteem and self-actualization. The second component is curiosity, intrinsic motivation, and interest. These constructs are often conceived of as 12

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the same thing (Berlyne, 1971; Starr, 1992) or as one subsuming the others (Lepper & Malone, 1987). Curiosity is considered an inborn tendency (Wlodkowski & Jaynes, 1990) and intrinsic motivation is curiosity applied to a specific activity. Interest is quite likely the selective persistence of curiosity (Prenzel, 1992) and preference to engage in a domain of activities including learning. The third component is the subjective and affective experience of intrinsic motivation, or flow. Figure 1.1 illustrates the combining of research areas into three categories and the interrelationships among them. Flow Self-concept in terms of competence, growth, and meaning Curiosity Intrinsic Motivation Interest Figure 1.1 Conceptual framework for love of learning 13

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This framework provides the basis for defining love of learning and developing an instrument to measure it. This framework aligns with Premise 5 and five of the principles of the learner-centered psychological principles developed for the American Psychological Association by the Presidential Task Force on Psychology in Education (Lambert & McCombs, 1998). The premises and principles are provided in Appendix A. However, in order to generate items to assess these overlapping constructs, each construct needs to operationally defined. Operationally defining each construct provides the dimension necessary for developing an adequate measure for the love of learning construct. Research Questions The research questions of this study are: 1. What sub constructs comprise the .overall construct of love of learning within the young adult (18 to 25 years) age group? 2. What are the relationships among the subconstructs of the love of learning construct within the young adult (18 to 25 years) age group? 3. What are the relationships between the love of learning construct and constructs that likely should have strong correlations with the love of learning construct within the young adult (18 to 25 years) age group? 14

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Specifically, for positive model validity (Krathwohl, 1993), what is the convergent relationship (Campbell & Fiske, 1959) between scores on the love of learning measure and scores on a curiosity measure? And, what is the convergent relationship (Campbell & Fiske, 1959) between scores on the love of learning and scores on an intrinsic enjoyment measure? Specifically, for negative model validity (Krathwohl, 1993), what is the discriminant relationship (Campbell & Fiske, 1959) between scores on the love of learning measure and scores on an anxiety measure? Also, what is the discriminant relationship (Campbell & Fiske, 1959) between scores on the love of learning measure and scores on a boredom measure? 4. What is the relationship between the love of learning construct and a construct that likely should have an intermediate-size correlation with the love of learning construct within the young adult (18 to 25 years) age group? Specifically, for borderline validity (Krathwohl, 1993), what is the relationship between scores on the love of learning measure and scores on a self actualization measure? 5. What is the relationship between the love of learning construct and a construct that likely should have low or no correlation with the love of learning construct within the young adult (18 to 25 years) age group? 15

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Specifically, for contrary validity (Krathwohl, 1993), what is the relationship between scores on the love of learning measure and scores on a flexible thinking measure? Methodology To define love of learning required a synthesis of the literature from a number of areas. From this synthesis operational definitions for each subconstruct were developed. Once the subconstructs had been operationally defined, an item pool for each subconstruct was generated and a self-report instrument to assess love of learning was derived from the item pools. A group of experts in the areas of learning and motivation assisted in the content validation of the instrument. The target age group for the instrument is young adults from 18 to 25 years old. One sample was used for the initial study of reliability and underlying relationships among subconstructs of the instrument. A subset sample was used to examine further evidence of construct validity. Students from several colleges were asked to participate. Item analyses, internal consistency reliability, factor analyses, and correlations among various subconstructs were conducted to examine the love of learning construct and the reliability of the instrument. In addition to administering the love of learning instrument, a battery of measures believed to correlate strongly, weakly, or not at all with love of learning were administered to the subset sample. Correlations with other measures were examined and a hybrid multitrait-multimethod 16

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matrix was composed. In these ways, initial evidence regarding the validity of love of learning was estimated and provided. Structure of the Dissertation This dissertation contains five chapters. The first chapter is an introduction to the problem. Chapter two includes a review of the literature. Chapter three describes the methodology. Chapter four provides the results of the study. Chapter five offers discussion, implications, summary, and conclusion. 17

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CHAPTER 2 REVIEW OF THE LITERATURE The idea of love of learning extends back through time. One could imagine, for example, Solomon in 3500 B. C. standing before a great altar of the Lord asking for wisdom above all (1 Kings 3:5-9, New International Version). Or perhaps one could see Aristotle standing in the Lyceum at the Academy of Athens around 300 B. C. and telling a group of students that wisdom is sweet and through wisdom , happiness is gained. Although such examples suggest anecdotes that humankind has valued the path of learning for thousands of years, we have not yet explored the meaning of the love of learning. By extending our understanding in this direction, we may be better able to influence children and students of all ages toward a love of learning. What background exists relevant to the love of learning? This chapter is organized to present first a historical summary of philosophical thinking related to the concept of love of learning. Second, in recent times, educators and psychologists have investigated constructs closely related to the love of learning, such as curiosity, intrinsic motivation, and interest. Research and findings in these areas that pertain to 18

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the love of learning construct are summarized. Finally, implications are derived from this review in terms of how the love of learning may be defined and measured. Historical Perspective Ancient Philosophers Western European history provides a chronological stream of anecdotal evidences that humankind has considered the love of learning and the achievement of wisdom as pursuits of the highest purposes of life. The Biblical character of Solomon desired wisdom more than 5000 years ago. Greek philosophers were preoccupied with the desire to achieve excellence through continuous learning. Roman scholars followed suit. And after a brief hiatus into the deep valuing of the love of God, scientists, philosophers, and artists emerged during the Renaissance thirsting and hungering for knowledge in a dramatic display of the love of learning. The following summary captures some of that stream. One of the earliest lovers of learning in western civilization was Solomon. He pleased the Lord by asking for wisdom above all; he impressed the Queen of Sheba with the extent of his understanding; and he taught his people of the value of wisdom (1 Kings 3:5-9,1 Kings 10:6-8, Proverbs 19:8, Proverbs 22:17-18, Proverbs 24:14, Ecclesiastes 7:12). Solomon declared that wisdom is pleasing to the soul (Proverbs 22:17-18). 19

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Much later the great Greek philosophers articulated the value of learning in order to be happy. Sophocles (trans. 1998) ended his tragic play, Antigone, with the chorus singing, "The greatest part of happiness is wisdom" (lines 1341-1342). Plato (trans. 1989) lived in Athens during the Peloponnesian War, the destruction of the Athenian empire, and the execution of Socrates. In a series of dialogs he reflected on the teachings of Socrates. Repeatedly, he declared that the ultimate purpose of human life is happiness and that happiness is achieved primarily through continuous learning, or acquiring of wisdom. In Charmides, Plato demonstrated that a person will be happy when he or she has knowledge (wisdom) (lines 174-176). In Euthydemus Crito and Cleinias came to understand that happiness is experienced through the acquisition of knowledge (line 282). In Symposium, Diotima described to Socrates the search for true beauty, which ultimately leads to knowledge and bliss (lines 21212). In Meno Plato argued that wisdom generates happiness because through it virtue is achieved (line 88c-d). In Apology, Plato showed how Socrates defended himself to the Athenians as a seeker and lover of true wisdom and knowledge. In Republic he indicated that the human soul's calling is to seek wisdom, to "hold to the upward ways and pursue righteousness with wisdom always and ever" (lines 611e612c, 621b-d). Finally in Timaeus, he not only discerned two desires natural to mankind, one for food and the other for knowledge (line 90a-c), but explicated that the love of learning leads to happiness: 20

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But he who has been earnest in the love of knowledge and of true wisdom, and has exercised his intellect more than any other part of him, ... , will be singularly happy (line 90b-c). Plato revered Socrates and characterized him as a philosopher and teacher who loved to learn. Plato also respected Aristotle, calling him the intellectual of the Academy at Athens. Aristotle (trans. 1984/1952a), known as the Father of Logic, also connected wisdom with happiness. However, for him, wisdom was derived from excellence in functioning, self-sufficiency, and philosophic thought. In as much as philosophic thought can be understood as learning, Aristotle concludes that learning is to be loved for its own sake (Book X, 6-7, line 1177a). Aristotle (trans. 1984/1952b) also declared that "all men by nature desire to know" (Book I, 1, line 980a). Greek philosophers believed that happiness was achieved through continuous learning, and that this learning process should be loved for its own sake. For the most part the Roman scholars followed in the Greek philosophers footsteps. They, too, were concerned with what was the highest good for man. Virgil (trans. 1984/1952) portrayed the happy person as one who understands nature and, therefore, controls his or her own fears (lines 490-493). Plutarch (trans. 1984/1952) declared that those who do not use their inborn love of learning for bettering themselves are not fulfilling their human purpose. Nicomachus (trans. 1984/1952) stated that through learning, or the desire for wisdom, the ultimate goal of mankind, 21

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which is happiness, is achieved (Chapter II, paragraph 3). Aurelius (trans. 1984/1952) asked what could be more agreeable than learning because mankind depends on learning for security and happiness (Book V, paragraph 9). Plotinus (trans. 1984/1952) agreed with Plato that wisdom begets happiness, but to have both requires concentrating on what might be thought of as the highest good (Fourth Tractate, paragraph 16). Roman scholars echoed Greek forerunners in their recognition of an innate love for learning and their assumption that happiness is experienced through learning. Those threads were nearly lost when the rise of Christianity changed the priorities of early philosophic thought in order to put the Divine Creator first. Virtue and happiness were no longer valued in and of themselves, and so the role of learning changed. St. Augustine (1984/400; 1984/413-426) thought little of learning but held that happiness was obtained through knowing and revering God. Aquinas (1984/1952) as well believed that happiness was experienced solely through worshipful acknowledgement of the Heavenly Father. Neither believed that learning fostered happiness. However, Dante (1984/1952) designed a synthesis for the Christian religion and earlier philosophic thought by telling a personal story. Divine Comedy told of enraptured learning by focusing on Infinite Goodness. His description was not unlike Greek and Roman philosophy nor unlike early Christian faith. While religion greatly influenced human thought in Western Europe, commerce and governance remained influential as well. Acknowledgement of the 22

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love of learning is found in Chaucer's (1984/1952) Canterbury Tales. Chaucer lived in England and served Richard II and Henry IV. His travels to France and Italy during the lOO-year war with France contributed to his thinking. The Canterbury Tales shows his ability to adopt multiple perspectives, and one of his most important voices is that of the Clerk. Chaucer describes the clerk as one "Who'd turned to getting knowledge, long ago ... Pregnant of moral virtue was his speech; And gladly would he learn and gladly teach" (p. 164). The Clerk embodies the personality and voice of people who loved to learn for the sake of learning. As Western Europe emerged from the influence of religious dogma and moved toward empirical reasoning and study, the disposition of the love of learning was born again. Controversial Hobbes exemplified one who loved learning during the Renaissance. After his formal schooling, he avidly devoted himself to the study of philosophy and mathematics. Although most of his published works represented philosophical treatments of political problems and were source of controversy, in Leviathan he created a classification scheme for passions, one of which "is the desire to know why, and how" (p. 63). He identified this desire as curiosity and attributed it solely to man. Other Renaissance philosophers addressed the desire and pleasure of learning as well. Hunt (1994) credited Locke as the first associationist because he argued that we combine simple ideas to form complex ideas and that we learn by relating one idea to another. Locke (1984/1952) also suggested that the increased complexity of 23

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ideas by association provides pleasure. Hume (1738/1984) implied that curiosity is innate and that the bringing of knowledge from obscurity to light (in other words, learning) is enjoyable. In the Preface of his Critique of Pure Reason, Kant (1781/1900) implied that reason (i.e. desire to know) is aroused by external stimuli: Experience tells us what is, but not that it must be necessarily what it is and not otherwise. It therefore never gives us any really general truths; and our reason, which particularly anxious for this class of knowledge, is aroused by it rather than satisfied (p. 2). During the Renaissance, Europe was rediscovering the delights of learning. This delight is reflected in several philosophers' writings. Through these early philosophers we find threads of thought that suggest a love of learning exists, that curiosity is innate and aroused by external stimuli, and that learning is intrinsically motivating, enjoyable in and of itself. Early Educators and Psychologists The arguments about human nature put forth by 18th century philosophers became tested in practice by a number of 19th and 20th century educators and psychologists. Educators frequently documented their observations that children experienced joy in learning. For example, Pestalozzi (1915/1894) was concerned with immediate perception. He found that by attending to the "first beginnings" for a long time, students became aware of their own power to persist, succeed, and learn. Through his attending Pestalozzi observed children's joy of learning together and 24

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teaching one another. As with Pestalozzi, Montessori (1964/1912) advocated for education of the senses and also saw avid interest and great pleasure in learning among children. Going beyond the immediate perceptions, Friedrich Froebel (1974/1900) saw the joy children experience in their freshly experienced sense impressions and in their newly acquired skills and believed that as children grow, so does their natural desire to know: Question upon question comes from the lips of the boy thirsting for knowledge -How? Why? When? What for? Of what? -and every somewhat satisfactory answer opens a new world to the boy ... However, it is not alone the desire to try and use his power that prompts the boy at this age to seek adventure .. ; it is particularly the peculiarity and need of his unfolding innermost life ... , to comprehend (the outer world) in its extent, its diversity, its integrity; it is the desire to extend his scope step by step (p. 102-103). However, he observed two kinds of desire for knowledge. He described the first as "the energetic, animating, uniting power" and the second as "the expansive, productive, creative, modifying (extensive) power" (p l33), noting that the second increases with age as the first decreases. Known as the founding father of American psychology (Hunt, 1994), William James (James, 1890) was fascinated by learning, especially his own. He clearly stated his opinion about the value of learning: nothing is more congenial, from babyhood to the end of life, than to be able to assimilate the new to the old, to meet each threatening violator or burster of our well-known series of concepts, as it comes in, see through its unwontedness, and ticket it off as an old friend in disguise. This victorious assimilation of the new is in fact the type of all intellectual pleasure. The lust for it is curiosity. The relations of the 25

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new to the old, before the assimilation is performed, is wonder (pp. 524-525). James believed that the love of learning is one of the best pleasures in life. To summarize, from the Western European historical perspective, human love of learning may be traced for thousands of years. The Biblical king Solomon sough wisdom above all else. Greek philosophers held that achieving excellence through continuous learning was the highest good. Roman philosophers concurred. Then, emerging several hundred years later in Renaissance, a passion for learning was demonstrated by scientists and reflected in the philosophical writings of that time. Even educators through the late 19th century acknowledged in children as well as themselves a joy or love of learning. In the early 20th century conceptual underpinnings of the love of learning began to be studied more scientifically or clinically, but not as love of learning per se. Rather, early scientists believed humans had an instinct to learn. Usually, they referred to this instinct as curiosity. 26

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Contemporary Research on Constructs Related to Love of Learning Curiosity Curiosity is very likely a part of love of learning. Bronzaft (1996) drew this connection when she stated that the "source of love of learning lies in normal childhood curiosity" (p. 43). She believed that love of learning is rooted in curiosity and that curiosity engenders learning. Implied in her belief is the notion that curiosity is inborn. The belief that curiosity is innate has been a persistent thread in the research literature for the past 50 years. Voss and Keller ' s (1983) review traced the conceptualization of curiosity as instinct, drive, intrinsically-motivated behavior, trait vs. state, and developmental process. Spielberger & Starr (1994) focused particularly on Berlyne's theory of diversive and specific curiosity, research conducted to investigate the two constructs, and how that research related to their theory of state-trait curiosity. Loewenstein (1994), on the other hand, described curiosity research as occurring in two waves. The first wave occurred in the 1960s and focused on three issues: what causes curiosity, why people seek curious situations, and what are the situational determinants. The second wave occurred in the 1970s and consisted mostly of developing instruments for and measuring curiosity. Research on curiosity is vast and rich, revealing fascinating results, overlapping and extending into other domains, and fostering new fields for further study. 27

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First Wave Issues Before the first wave Loewenstein (1994) identified, early psychologists dealt with the construct of curiosity. For example, James (1890) described two kinds of curiosity. He emphasized the biological function of the first kind as an instinct-driven behavior involved in approaching and exploring new objects. He stated that "curiosity and fear form a couple of antagonistic emotions liable to be awakened by the same outward thing, and manifestly both useful to their possessor" (p. 429). James defined the second kind of curiosity "scientific curiosity" and "metaphysical wonder" with which "the practical instinctive root has probably nothing to do" rather "the philosophic brain responds to an inconsistency or a gap in its knowledge" (p. 430). James's two kinds of curiosity coincide with Berlyne's conceptualization and other researchers' studies of curiosity. Another early psychologist who dealt with curiosity is McDougall. McDougall (1912) defined instinct as "an inherited or innate psycho-physical disposition which determines its possessor to perceive, and to pay attention to, objects of a certain class, to experience an emotional excitement of a particular quality upon perceiving such an object and to act in regard to it in a particular manner, or, at least, to experience an impulse to such action" (p. 29). He identified curiosity as one of eleven instincts and associated curiosity with the emotion of wonder. He thought that curiosity was 28

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the main source of intellectual energy and effort; to its impulse we certainly owe most of the purely disinterested labours of the highest types of intellect. It must be regarded as one of the principal roots of both science and religion (p. 57). McDougall believed there were individual differences in curiosity that increased or decreased across the life span. McDougall did not distinguish two kinds of curiosity, rather he saw intellectual curiosity as stemming from a curiosity instinct and emotional wonder. A third early psychologist who dealt with curiosity is Freud, who was actually a psychiatrist with medical training. Freud did not specifically address curiosity. Rather , he explained intellectual curiosity as stemming from scotophilia, sexual curiosity, and sibling rivalry (Aronoff, 1962 ; Freud, 1959a, 1959b). Freud defined the instinct for looking as scoptophilia, which causes a child to develop an intense interest in sexual matters. Sexual curiosity starts when the child discovers and takes pleasure in the sensations of his sexual organs. Pleasure becomes associated with scoptophilia and develops at the age of three to five. He thought that scoptophilia is why children investigate the world and become able to abstract knowledge. This pattern of inquiry extended through adulthood. (Aronoff, 1962) Thus, Freud believed that the "thirst for knowledge seems to be inseparable from sexual life" p. 153 (Freud, 1959b) . On one hand Freud implied a link between curiosity and sexual interest. On the other hand , he thought curiosity resulted from of a child fearing the loss of his/her parents care and concern: 29

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The child's desire for knowledge does not awaken spontaneously ... as it would if prompted perhaps by an inborn need to seek for causes, but arises under the goad of a self-seeking impulse which dominates him when he is confronted by the arrival of a new child -perchance at the end of the second year. Those children whose own nursery at home does not become divided up in this way are nevertheless able as the result of their own observations to put themselves in the place of others who are in this situation in other homes. The loss of the parents' care and concern ... has the effect of awakening the emotions of the child and sharpening its thinking capacities (Freud, 1959a, p. 62). Like Freud, Buhler (1928) had a background in biology. However, based on his observations of children, Buhler offered an alternative explanation to Freud's pleasure principle. He interpreted children's playas providing pleasure through movement and repetition, as well as skill acquisition and improvement. Thus, children learned and improved from their play, while play provided joy. He saw no connection to either sexual interest or fear of loss of parental love. Piaget (1926), who was another biologist by training, believed that questionasking behavior is biologically based. He thought that through question-asking a child moved through various stages of intellectual development (i.e., sensori-motor, formal operations). This account also lacks a connection to sexual interest or a fear of the loss oflove. It is rather part of a child's natural development. Like McDougall, Freud believed intellectual curiosity grew out of instinct. Freud's instinctual source as sexual, however, was quite different from McDougall's instinctual source as wonder. Buhler's conception of instinctual curiosity is more closely aligned with McDougall's and includes an element of self-improvement. 30

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Piaget's is very similar to both James and Berlyne's ideas about curiosity, because question-asking is epistemic and motivated by gaps in knowledge. James, like Berlyne, thought intellectual curiosity was motivated by intellectual inconsistencies rather than instinct. Of the five, James's and Piaget's thinking most closely aligns with Berlyne's conceptualization and more recent research. Berlyne is one of the most important early pioneers in the study of curiosity. In 1950 he said, "wonder, the 'source of the love of knowledge' contains both curiosity and cognitive surprise. It is aroused by anything extraordinary and difficult to understand" (p. 69). By 1954 Berlyne had identified two kinds of curiosity: diversive and specific curiosity. Diversive curiosity was a stimulus-seeking behavior. Specific curiosity included exploratory and epistemic curiosity (1954a). Defined as "the condition of discomfort, due to inadequacy of information, that motivates specific exploration" (p. 26) (1966), specific curiosity is provoked by conflicting, surprising, puzzling, and unexpected stimuli (1954a). At first Berlyne theorized that epistemic curiosity operated as a drive-reduction mechanism and much of his taxonomy for curiosity is based on this theory. Later he modified this theory to include optimal arousal along with drive reduction. A key aspect of his taxonomy of epistemic curiosity is conceptual conflict. Conceptual conflict includes doubt, perplexity, contradiction, conceptual incongruity, confusion, and irrelevance (1960). He distinguished among the epistemic curiosity-arousing stimuli using the qualities of novelty, complexity, surprise, and ambiguity. External stimuli may be "collated" 31

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according to these qualities, which is why he called them collative variables. Further, Berlyne said that epistemic curiosity may be kept alive with questions and that conceptual conflict is reduced by information acquired through epistemic behavior. Berlyne (1954b) conducted a study to demonstrate that surprising and puzzling stimuli arouse epistemic curiosity. The experimental group received (a) a questionnaire at the beginning about invertebrate animals, (b) a reading about the animals which included answers to questions, and (c) a questionnaire at the end which included questions. The control group did not have the questionnaire in the beginning. Berlyne hypothesized that a questionnaire administered at the beginning would arouse epistemic curiosity and he used answers to the post-test quiz and subjective reports as measures of epistemic curiosity. The two groups differed significantly. He found that (a) the questionnaire at the beginning tended to arouse curiosity, (b) the two measures of curiosity (self-reported surprisingness and answers to questions after the reading) were positively correlated, (c) questions about familiar animals and questions whose concepts were incompatible arouse more curiosity than others, and (d) that surprising statements were more likely to be recalled as answers than others. Frick and Cofer (1972) replicated Berlyne's study and found much the same thing. Also prompted by Berlyne's suggestion that the desire to know is evoked by surprising information, Rossing and Long (1981) conducted a study to investigate the correlations between curiosity evoked by surprise and of perceived value of information to the desire to know more about psychological research topics. Their sample consisted of 79 32

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volunteer adults from evening credit and non-credit classes ranging in age from 21 to 52 years . Although they found positive correlations between both surprise and valuing and the desire to gain more knowledge, only the valuing relationship was significant. Berlyne's research broke ground for others studying curiosity. For example, Maw (1971) agreed with Berlyne that two kinds of curiosity were perceptual and epistemic. Using Berlyne's concept, Maw operationalized this distinction by describing a curious child as one who (a) responds positively to new, strange, incongruous things in the environment, (b) shows a need to know more about herself and her environment, (c) scans her surroundings seeking new experiences, and Cd) persists in examining and exploring stimuli in order to know more about them. Using a number of instruments, Maw examined curiosity in 5th graders. He found several personality variables that distinguished between children with high and low curiosity. Variables included level of self-acceptance, self sufficiency, sense of security, loyalty, square shooters, participation in group activities, social adjustment, and sense of responsibility for group welfare. Berlyne and Maw contributed to early thinking about curiosity but were by no means the only ones. For example, Fowler (1965) also was immersed in the study of curiosity . He discussed the history and theoretical conceptualizations of curiosity and exploratory behavior. He discussed curiosity as instinct, drive, and response to novelty, change, and complexity. He introduced the conceptualization of curiosity as 33

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optimal arousal. Finally, he addressed the difficulty of detennining whether curiosity is personality expressed in individual differences or motivation. Another often overlooked scholar is Arnold (1956), who presented a logical argument for the existence of the desire to know. She argued that curiosity could not be an instinct because it served no biological basis. She argued that curiosity could not be accounted for with the classical conditioning model because many motivations would have to be paired with some psychological need many times, and this was unfeasible. Neither was drive theory a good explanation, she reasoned, because the desire to know more is not an accident emerging as a secondary drive from basic drives. She stated that all these theories were inadequate because each assumed that living beings were inert, inactive and must be prodded into activity by drives or needs. She claimed that not only are all of our senses active, but so are thinking, reasoning, judging, and imagining. As human beings, we cannot help wanting to know about things, their effect on us, and what we can do with or about them. Arnold believed that this active process was more than just a problem-solving process as we search for problems because they are fun. Second Wave Measurement Perhaps not realizing that they were acting out the very process described by Arnold (1956), researchers began developing techniques for measuring curiosity. There are approximately ten instruments purporting to measure curiosity in its various 34

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forms. Spielberger and Starr (1994) related Berlyne's theory of diversive and specific curiosity to Zuckerman's sensation seeking behavior and to their own theory about state and trait curiosity. They introduced the concept of anxiety into the mix and used Wundt's curve to demonstrate that their theory may better explain curiosity. They reported on several studies undertaken to investigate curiosity. Results indicate that there are two components, directly related to epistemic and diversive curiosity. Epistemic curiosity is information seeking; diversive curiosity relates mostly to experience seeking. Spielberger and Start introduced the Ontario Test of Intrinsic Motivation (OTIM) (Day, 1968), Sensation Seeking Scale (SSS) (Zuckerman, Kolin, Price, & Zoob, 1964), Novelty Experiencing Scale (NES) (Pearson, 1970), Academic Curiosity Inventory (ACI) (Vidler & Rawan, 1974 ; 1975), Melbourne Curiosity Inventory (MCI) (Naylor , 1981), and the State-Trait Curiosity Inventory (STCI) (Spielberger, Butler, Peters, & Frain, 1976). Their list included perhaps the most frequently used instruments, but was not all inclusive . Voss and Keller (1983) provide a more comprehensive listing and description of curiosity measures. Appendix C summarizes the psychometric information for most of the self-report curiosity instruments developed during the second wave (Loewenstein, 1994) Why were so many instruments about curiosity developed? One reason may be that different theoretical constructions of curiosity were being proposed and tested. Another reason is that different aspects of the curiosity construct were being investigated. Last is that different measures were being developed for different 35

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populations, however, this is apparent only in Penney and McCann's (1964) curiosity measure for children. As the following descriptions of the most prominent measures depict, curiosity was differentially conceived and measured. However, statistical examination seemed to bring researchers back to Berlyne (1954a) and James (1890) initial intuition that curiosity is composed of two components: information-seeking and experience-seeking. In 1964, Penney and McCann developed the Children's Reactive Curiosity Scale (CRCS). Designed for students in the 4th, 5th, and 6th grade, the scale was based on Berlyne's definition of specific curiosity: (a) a tendency to approach and explore relatively new stimulus situations (novelty), (b) a tendency to approach and explore incongruous, complex stimuli (dissonance, complexity), and (c) a tendency to vary stimulation in the presence of frequently experienced stimulation (variety). Additionally in 1966, using the same concept of curiosity and psychometric approach, Penney and Reinehr developed a Stimulus-Variation Seeking Scale for Adults (SVSS). Around the same time Garlington and Shimota (1964) developed the Change Seeker Index (CSI). They defined change seeking as a "habitual, consistent pattern of behavior which acts to control the amount and kind of stimulus input a given organism receives. "stimulus input" includes stimuli from both internal (ideational, cognition) and external sources" (p. 920). Garlington and Shimota believed that change-seeking was a component of both diversive and epistemic curiosity. Also 36

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around the same time Zuckerman produced the Sensation Seeking Scale (SSS) (1964), a scale still used today. SSS was designed to quantify the construct: "optimal stimulation level," a component Berlyne (1960) later incorporated into his definition of curiosity. Pearson (1970) suspected that the instruments identified above were only partially addressing curiosity, or more precisely, the novelty experiencing component of curiosity. Therefore, she followed Fiske's (1966a) suggestion to use a conceptual operational strategy to construct her scale. Pearson constructed the Novelty Experiencing Scale (NES) based on a 2-by-2 model of how novelty might be experienced: external cognition, external sensation, internal cognition, and internal sensation. She also constructed a lO-item Desire for Novelty Scale and defined the desire for novelty as expressing the wish for new experiences and recognizing the boring nature of every day life. She predicted that this scale would be independent of the four scales comprising the NES. Her prediction was confirmed. Specific NES scales were differentiated from each other and the global NES score. Thus, she suggested that a number of relatively unique dispositions related to novelty might exist, which curiosity measures had not yet captured. Most measures developed and in use at that time assessed the external sensation component of experiencing novelty. Some researchers were not as concerned with how curiosity was experienced. Rather, they wondered if curiosity was a state aroused by stimuli in the environment or an enduring trait of one's personality. This aspect of curiosity had not been 37

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addressed and as a result, began to grow in importance. Camp and Dietrich (1985) characterized this distinction in the following way: "as a trait, curiosity is seen as an enduring interest in acquiring new information. As a state, or contextually focused activity, it is seen as epistemic curiosity, or the desire to seek (specific) knowledge" (p. 401). Researchers began to believe that some curiosity measures assessed state curiosity and others assessed trait curiosity. About five methods for assessing curiosity as a state or as a trait emerged. These include Day's (1969) Ontario Test of Intrinsic Motivation (OTIM) (1969), Leherissey's (1971a) 20-item State Curiosity Scale (SCS), State Epistemic Curiosity Scale (SECS), Spielberger, Butler, Peters, and Frain's (1976) State-Trait Curiosity Inventory (STCI), Naylor's (1981) Melbourne Curiosity Inventory (MCI), and Vidler and Rowan's (1974) Scale of Academic Curiosity. See Appendix C for more detailed information. Vidler and Rowan placed less emphasis on the sate-trait distinction of curiosity. Their scale was based on earlier work by Chiu (1968). Chiu had developed an instrument to assess academic motivation based on 16 variables comprising academic motivation. One ofthe variables was curiosity. Administering the 278-item survey to a sample of 285 eleventh graders, Chiu found six factors: curiosity, positive orientation to learning, need for social recognition, academic ability, motive to avoid failure, and reaction to expectation. Although Chiu' s sample was small for the number of items in the survey, Vidler and Rowan adapted the instrument and administered it to 170 college students. Factor analysis revealed a five factor 38

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structure. This finding was surprising because the authors had assumed that academic curiosity was unidimensional, but not so surprising because the original instrument had a six-factor structure. Unlike Vidler and Rowan's findings, factor analysis studies of the various measures of curiosity more often than not revealed two factors. To test the hypothesis of curiosity as a multifaceted construct, Langevin (1971) chose five measures of curiosity, including teacher ratings and observations, and the Otis and Raven tests for intelligence. This was a multitrait-multirriethod approach. The sample was 195 6th grade boys and girls. Factor analyses revealed two weak curiosity factors, which he named breadth and depth of interest. Langevin was uncertain as to whether his results reflected the different methods of assessment or whether he found evidence for a two factor curiosity construct. Ainley (1987) strengthened Langevin's results by also finding evidence for a two-factor curiosity construct. She administered five curiosity scales to 227 college students. The scales represented a theoretical cross section of curiosity as optimal arousal, cognitive processing, and state-trait. Her factor analysis revealed two factors, which she also labeled breadth and depth of interest. Somewhat in qualifying contrast, Boyle (1989) examined the factor structure of curiosity as well. His study varied slightly because he conducted a factor analysis of state-trait curiosity and state-trait anxiety using four scales, which he administered to 300 high school students. His factor analysis showed six factors: a positive and negative factor for each of state curiosity, trait curiosity, and state anxiety. Thus, his 39

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findings imply a four factor structure for curiosity. However, if the positive and negative factors are thought to represent a single continuum, his research might support a two-factor structure for curiosity. Because of the instruments he used, his factors define structure with regard to state and trait curiosity. Lastly, Starr (1992) also assessed the relationships among various conceptions of curiosity. She administered five instruments to 376 undergraduate students (60% female). Her factor analyses revealed two factors. With these results, Starr argued that curiosity is composed, as Berlyne posited, of an information seeking component and an experience (sensation) experiencing component. Summary What can be said about curiosity? With some certainty, two things can be said. First, researchers tend to agree that curiosity is inborn, but also believe that curiosity is influenced by the environment. For example, Mohanty and Mishra (1991) conducted an experiment with 40 fourto five-year olds. Giving one group a series of tasks to help them grow intellectually and in curiosity, researchers found that this group improved significantly more than controls in the shortand long-term effects in both intelligence and curiosity. Their study shows how the environment can exert a positive influence on the development of curiosity. The possibly negative influences of the environment on curiosity development concern some researchers. Deci (1995) and Wlodkowski and Jaynes (1990) have argued that natural curiosity declines as 40

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children go to school and they attribute this decline to various aspects of the schooling process . However, Camp and Dietrich (1985) found high levels of curiosity in young , middle, and older adults, who took the OTIM. There are still some unresolved issues and the nature-nurture debate remains complicated. Researchers also seem to agree on a second aspect of curiosity. Curiosity is apparently composed of two factors , an information-seeking or epistemic factor and an experience or sensation-seeking factor. So far, no one has suggested that curiosity is not related to a love of learning. Thus, Bronzaft's (1996) inference that people who are curious and look forward to learning develop a love of learning disposition seems reasonable. Intrinsic Motivation Intrinsic motivation grew up with, and in some ways out of, curiosity research. As with definitions of curiosity, definitions of intrinsic motivation vary. Some scholars (Berlyne, 1971; Day, 1969; 1971; Maw, 1971; McReynolds, 1971) thought of curiosity and intrinsic motivation as the same construct. Other scholars did not (Dember & Earl, 1957; Fowler, 1965). At least one common thread pulled the various definitions of intrinsic motivation together. Intrinsic motivation refers to the inherent nature of the activity itself (Lahey, 2001). Research on intrinsic motivation moved beyond the bounds of curiosity in two specific ways. First, researchers investigated the why's and wherefore's of intrinsically motivating tasks. Several taxonomies (Deci, 1980; Malone & Lepper, 1987; Young, 1961) emerged from this 41

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research expanding the concept of intrinsic motivation. Second, extrinsic and intrinsic motivation were examined. Several important theories of motivation emerged from this second line of research. Extrinsic and intrinsic motivation research also developed into an area of study on self-concept as competence. This section presents definitions of intrinsic motivation, relevant research, and connects intrinsic motivation to other constructs related to love of learning. However, in keeping with the conceptual framework described in chapter one, the connection between intrinsic motivation and self-concept as competence will be addressed later in the chapter as part of the self-concept research related to the love of learning. Definitions Apparently, many researchers (Bedyne, 1971; Day, 1971; Maw, 1971) who studied curiosity redefined their theories, models, and research in terms of intrinsic motivation. For example, Bedyne (1971) described intrinsic motivation as motivation "aimed at certain internal consequences that constitute intrinsic reinforcements or reward" (p. 188). He further observed that novelty, complexity, surprise, and ambiguity are all involved in intrinsic motivation. These were the collative variables he developed in his research on curiosity. Secondly, Day (1969, 1971) developed a specific instrument entitled the Ontario Test of Intrinsic Motivation (OTIM) based on Bedyne's definition of curiosity. Indeed, Intrinsic motivation: A new direction in education (1971), contained at least three chapters about research on curiosity 42

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(Berlyne, " 1971; Day, 1971; Maw, 1971). In a chapter on the assessment of intrinsic motivation, McReynolds (1971) reviewed most of the instruments that had been developed to assess curiosity implying the two constructs' synonomity. Finally, Beswick (1974) pointed out that "curiosity is commonly taken to be the prototypical example of intrinsic motivation" (p. 15). Thus, many early researchers conceived of curiosity and intrinsic motivation as much the same thing, even if they differed regarding the essence of each. Earlier than the confluence of research activity mentioned above, several theorists occasionally referred to intrinsic motivation. For example, Woodworth (1918) stated that a child, pursues an activity only when it is "intrinsically interesting to himself' (p. 67). Troland (1928) developed the idea of human novelty-seeking as intrinsically motivating. Murray and KIuckhohn (1953) introduced the idea of modal activity, which is intrinsic activity governed by an effort to appreciate or achieve excellence for its own sake. Hilgard and Russell (1950) distinguished between the intrinsically and extrinsically rewarding relationships of tasks and goals. Maslow (1954) implied that personal growth motivation is intrinsically motivating. Finally, Herzberg, Mausner, and Snyderman (1959) defined motivator factors as intrinsic and hygiene factors as extrinsic to job tasks. Seemingly, these theorists provided cairns for later intrinsic motivation research. Although the theorists mentioned above began exploring the intrinsic motivation realm earlier or concurrently, the first use of the term intrinsic motivation 43

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is commonly attributed attributed to Harlow, Harlow, and Meyer (1950) and Harlow (1950) (Hunt, 1971; Voss & Keller, 1983). Harlow, Harlow, and Meyer (1950) observed four rhesus monkeys who solved puzzles without extrinsic rewards. The researchers postulated that the activity provided intrinsic reward. In a follow up study Harlow (1950) found that two rhesus monkeys were intrinsically motivated to learn how to solve a more complex puzzle and were intrinsically motivated to improve . their performance once they had learned to solve the puzzle. In summarizing research on animals, Harlow (1953) argued for a motivation beyond basic needs and secondary drives. He concluded that animals and humans have a natural desire to manipulate and suggested that this desire is intrinsically motivated. The idea that intrinsic motivation was a drive was difficult to release, yet the definition that most researchers have come to accept is that intrinsic motivation is derived from the activity itself. For example, Deci (1975a, 1980) described intrinsic motivation as the activity itself being its own reward. He indicated that this definition is a good operational definition because the key elements are observable, verifiable, and quantifiable. Malone and Lepper (1987) used the words fun, interesting, captivating, enjoyable, and intrinsically motivating interchangeably to describe an intrinsically motivating activity that people engage in for its own sake. Wlodkowski and Jaynes (1990) took the desire to learn, plus perseverance, valuing, and enjoyment of learning into their meaning of intrinsic motivation, in which learning is a satisfying and rewarding activity in and of itself. That intrinsic motivation is inherent in the 44

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activity itself is central to research in the area. However, this essence has by no means limited researchers' conceptualization of intrinsic motivation. On the contrary, it seems to have inspired several researchers' imaginations. What follow are summaries of several taxonomies that extended the initial meaning of intrinsic motivation. Taxonomies As early as 1961, Young identified four variables which he thought comprised or affected intrinsic motivation. They are competence, effectance, autonomy, and hedonism. The first three variables are addressed below in the review of self-concept as competence. The fourth variable also is addressed below as flow. Young's taxonomy is somewhat incomplete because the variables he identified do not include what is meant by an activity being inherently interesting in and of itself. Malone and Lepper (1987) extend Young's initial grouping by including inherent interest. Malone and Lepper (1987) created perhaps the most comprehensive and extensive taxonomy of intrinsic motivation. They specified two motivational processes: the individual and interpersonal. Individual motivations include challenge, curiosity, control, and fantasy. Interpersonal motivations are cooperation, competition, and recognition. Although the interpersonal motivations are important and interact in many ways with individual motivations, the individual motivations are particularly relevant to defining the love of learning. They show connectedness with the other components proposed here to be part of the love of learning. The following 45

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paragraphs summarize the definition for each of the individual motivation components in Malone and Lepper's taxonomy. The challenge component stems from common belief that people prefer an optimal level of challenge. Challenge relates to effectance motivation (Harter, 1978; White, 1959), perceived competence (Deci, 1975; Lepper & Green, 1978), flow states (Csikszentmihalyi, 1975), and self-efficacy (Bandura, 1977). An activity is usually challenging, when it involves goals whose attainment is uncertain. Lepper and Malone (1987) suggested that intrinsic motivation involving challenge, competence, effectance, or mastery motivation creates an image of humans as problem solvers. Humans seek to solve problems and problems of intermediate difficulty are best. Challenge is interconnected with several constructs proposed to be part of love of learning. The challenge component is explored in greater depth below as part of flow and self-concept as competence. Curiosity (reviewed extensively above) is the second individual motivation component. Malone and Lepper (1987) state that "curiosity may be the most direct intrinsic motivation for learning" p. 235. Curiosity is aroused when there is an optimal level of informational complexity (Berlyne, 1960, 1965) or an optimal level of discrepancy or incongruity (Hunt, 1971; Piaget, 1951; 1952). In this case cognitive curiosity refers to the natural drive toward ordering cognitive structures. Intrinsic motivation involving curiosity, incongruity, or discrepancy evokes an image of humans as information processors. Humans typically get pleasure from an optimal 46

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level of surprise (Lepper & Malone, 1987). Research regarding optimal arousal or discrepancy is further addressed as flow. The third individual motivation component, control, is defined by (a) range of outcomes that the environment provides, and (b) the extent to which the probability of each outcome in contingent upon the responses of the person. The control component is an important aspect of much of the research related to intrinsic motivation (e.g. deCharms, 1968; Deci, 1975). Intrinsic motivation involving perceived control and self-determination conjures an image of humans as voluntary actors. Humans become intrinsically motivated when they feel they have personal control over meaningful outcomes (Lepper & Malone, 1987). The control component appears most frequently with research relating intrinsic motivation and feelings of efficacy and self-esteem. As such, research findings about the control component of intrinsic motivation are presented in self-concept as competence. The final factor of the Malone and Lepper intrinsic motivation taxonomy is fantasy. They state that fantasy is most likely to occur in an environment that evokes mental images of physical or social situations not actually present. Malone and Lepper often introduced fantasy as a component in their research of intrinsic motivation (i.e., Lepper & Malone, 1987). The research of Malone, Lepper, and others relating fantasy and intrinsic motivation is summarized later in this section. Malone and Lepper's taxonomy obviously encompasses a broad view of intrinsic motivation. From this perspective the love of learning may be comprised 47

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mostly of individual motivations of intrinsic motivation. Although fantasy is a means of creating inherent interest, it is not the only way. Thus, Malone and Lepper do not completely address inherent interest in an activity, which is the defining essence of intrinsic motivation. However, interest as a research area has become a research area in recent decades, and as such, is discussed below. In defining love of learning as a dispositional construct, the construct of interest as well as inherent interest (intrinsic motivation) are included. The third taxonomy may be more accurately typified as two generalizations about intrinsic motivation. Deci (1980) believed that intrinsic motivation is an explanatory concept in two ways. First, organisms need an optimal level of physiological or psychological stimulation. This approach explains behavior that increases or reduces incongruity. The second way understands intrinsic motivation as the felt need for competence. In this way intrinsic motivation is purposive and self directed . In both ways of explanation the need for optimal challenge exists. As pointed out above, challenge, as part of and as well as these two generalizations, is detailed below in the reviews of flow and self concept as competence research. Deci's generalizations are expansive but not as comprehensive or extensive as Malone and Lepper's taxonomy. What is evident among all three perspectives is the theorists' assumption that intrinsic motivation is intimately connected with self concept in terms of feeling efficacious, autonomous, competent, and in control. However, the taxonomies captured more than this; intrinsic motivation means having 48

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fun because an activity is inherently interesting. Young mentions hedonism. Malone and Lepper introduce fantasy as one means to channel fun. Deci speaks of optimal stimulation. Nonetheless, each taxonomy is limited in its expose of intrinsic motivation as fun. In general, these taxonomies provided organizing principles for understanding and extending the construct of intrinsic motivation and research about intrinsic motivation in general. Research Intrinsic motivation. The study of intrinsic motivation has continued for at least a quarter of a century. One body of research has focused on the intrinsically motivating nature of various tasks, especially learning tasks. Another body of research has focused on the contrast between intrinsic and extrinsic motivation. Finally, several measurements of intrinsic motivation have been developed for different age groups and a variety of purposes. To examine the intrinsically motivating nature of a learning task, Benware and Deci (1984) tested whether college students who learned with an active orientation would be more intrinsically motivated and learn more than students who learned with a passive orientation. The active orientation was created by having subjects learn material with the expectation of teaching it to another student; the passive orientation was created by having subjects learn the same material with the expectation of being 49

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tested on it. Forty-three first year college students were randomly assigned to one of the two conditions. Both groups were given three hours to study a 25-page moderately difficult article about brain functioning. Subjects who learned in order to teach were more intrinsically motivated, had higher conceptual learning scores, and perceived themselves to be more actively engaged with the environment than students who in preparation for a test. However, rote learning scores were the same for the two groups. Benware and Deci concluded that intrinsic motivation grows out of more active learning and results in increased conceptual understanding and self efficacy. Using fantasy as a channel of intrinsic motivation in computer activities, Malone (1981) found computer features most highly correlated with 65 school children'S preferences included (a) whether or not the game had an explicit goal, (b) scoring, (c) sound effects, and (d) randomness. These features relate to challenge (goal), curiosity (randomness), control (scoring) and fantasy (sound effects). Malone (1981) further discovered in an experiment with eighty 5th graders that external embellishments in learning environments, in this case computer games, actually influence intrinsic motivation. Lepper and Malone (1987) embedded identical instructional sequences in activities that varied in motivational appeal. They found that children chose the embellished game 50% more frequently, but that the enhancements did not produce significantly different learning. Lepper and Cordova (1992) reviewed studies that examined the congruence between intrinsic motivation 50

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and educational goals in computer activities. In these computer activities success and enjoyment depended on learning the subject matter presented. Overall, they found that students learned more, retained more, and generalized (transferred) more of what they learned from the educational activities they had rated as fun or had chosen to use. Fantasy however, must be inherently related to content and educational goals or it distracts from learning. Finally, Parker and Lepper (1992) examined intrinsic motivation on the effects of embedding instruction in fantasy contexts on children's learning. Students in the fantasy condition showed greater learning and transfer than students assigned to the no-fantasy condition. Results suggest first that fantasy is related to intrinsic motivation as Malone and Lepper's taxonomy suggests, and that intrinsic motivation is related to learning and transfer. In general studies such as these show that inherent interest in an activity is fun when a fantasy factor is included. This factor affects learning when it is embedded within the learning task. Inherent enjoyment of an activity varies with fantasy and fantasy is a factor in the environment that can be manipulated. However, fantasy is not the only feature in the environment that influences intrinsic motivation. Another influential factor in the environment is extrinsic reward. Intrinsic and extrinsic motivations and rewards. Theorists have argued that that extrinsic rewards undermine intrinsic motivation. In 1964 Holt declared that we destroy the ... love of learning '" in children by encouraging and 51

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compelling them to work for petty and contemptible rewards -gold stars, or papers marked 100 and tacked to the walls, or As on report cards, or honor rolls, or dean's lists, or Phi Beta Kappa keys (p. 274). Montessori (1967) suggested that rewards were unnecessary and perhaps harmful. More recently, Kohn (1993) also has been critical of extrinsic rewards stating that they undermine intrinsic interest in an activity. Through the 1950s, 1960s, and 1970s, research was conducted to determine the affect of extrinsic rewards on a variety of dependent variables including achievement, performance, and intrinsic motivation. After examining over 40 studies, McGraw (1978) concluded that extrinsic rewards had a detrimental affect on performance. Size of reward and age of participant did not affect this result. Although more often than not the studies showed that rewards have a detrimental affect on performance, McGraw qualified his conclusion because research results were not definitive. He distinguished two aspects of the task that affected whether rewards have a detrimental affect on performance. He labeled the first aspect attractiveness. If a task is in any way intellectually challenging, then rewards have a detrimental affect on performance. If a task is mundane such as lever pressing or vigilance, then rewards sustain or improve performance. He labeled the second aspect algorithmic-heuristic distinction. If the task requires participants to create a heuristic rather than to simply follow an algorithm to complete the task, then extrinsic rewards have a detrimental affect on performance. If a task involves the consistent application of a predetermined 52

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algorithm, then rewards sustain or improve performance. In McGraw's distinction one can see challenge and competence coming into play. One sees that both extrinsic and intrinsic rewards affect learning and performance. Several meta-analyses have been conducted over the last 15 years. Rummel and Feinberg (1988) reviewed 45 studies, Weirsma (1992) reviewed 16 studies, and Tang and Hall (1995) reviewed 52 studies. All found support for the undermining effect of rewards although Tang and Hall found that verbal rewards enhanced intrinsic motivation. However, two meta-analyses challenged that conclusion. Cameron and Pearce (1994) collected 96 experiments in which an experimental group received a reward and a control group did not. They found no significant undermining on most reward contingencies, although verbal rewards enhanced intrinsic motivation on self-report and behavioral measures. Eisenberger and Cameron (1996) examined two substes of the 96 studies using funnel graphs and found similar results. The first subset included 61 studies in which the dependent variable was time spent on an activity after reward was withdrawn from the experimental group. The second subset included 64 studies in which the dependent variable was participants' attitudes (task interest, enjoyment, overall satisfaction) toward a task. These studies led Covington (2000) to conclude that doing well gradewise does not necessarily interfere with learning for its own sake. However, Deci, Koestner, and Ryan (1999) conducted a meta-analysis of 128 studies. They found a significant undermining effect (Cohen composite d = -.24). Their breakdowns of various categories likewise showed 53

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consistent undermining effects in almost all categories. Exceptions include verbal rewards for college students, unexpected rewards, and task-non-contingent rewards. Csikszentmihalyi (1975) believed before so many studies were conducted, that intrinsic and extrinsic motivations were neither inversely related nor mutually exclusive. Conflicting results imply that this may be the case. In fact several scholars developed perspectives which account for this. First, Deci (1980) suggested that Cognitive Evaluation Theory (CET) explains how intrinsic motivation and extrinsic rewards work together. CET states that whether intrinsic or extrinsic motivation is involved depends on the interpretation (or of the salience) of either the controlling aspect or the informational aspect of the reward. Of the controlling aspect, Deci (1995) was still compelled to state that applying principles of reinforcement undermine intrinsic motivation. Second, Middleton and Toluk (1999) explained how learners engage in academic tasks either for intrinsic or extrinsic reasons because of how they value a task. Middleton and Toluk focus on the value aspect of the expectancy-value theory of motivation. Within the intrinsic framework, learners compare an academic task with their prior experiences. If it is considered similar to an interest, learners will engage as long as a task is stimulating (arousal) and as long as learners feel a sense of control (autonomy) of outcomes. If a task is not considered an interest, then learners consider extrinsic factors such as reward or avoiding failure in a costlbenefit analysis of sorts where the expected reward must outweigh the expected cost to engage. 54

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Intrinsic motivation is inherent interest in an activity itself. Researchers have worked with this basic definition and extended it in many ways. Nonetheless, instruments designed to assess intrinsic motivation have not always been based on this essential conceptualization . As with research, scales designed to assess intrinsic motivation have extended the initial definition. Measures of Intrinsic Motivation Several different measures of intrinsic motivation have been developed over the years. Although many more have been developed for curiosity, some measures seem to measure either or both curiosity and intrinsic motivation. For example, Day (1969, 1971) based the Ontario Test of Intrinsic Motivation (OTIM) on Berlyne's conceptualization of curiosity. Beswick (1974) developed a measure entitled Curiosity Items to assess academic intrinsic motivation. He based his instrument partially on Day's OTIM. That curiosity and intrinsic motivation are often perceived as the same is borne out by research by Starr (1992). After analyzing the results comparing five curiosity instruments, including OTIM, Starr suggested that curiosity is about the same as intrinsic motivation. However, several researchers have developed measurements specifically to assess intrinsic motivation. Among them are Harter (1981), Hamilton, Haier, and Buchsbaum (1984), and Gottfried (1982, 1985, 1990). Beswick's (1974) developed a 16-item assessment of academic intrinsic 55

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motivation entitled Curiosity Items. Beswick derived the 16 items from Day's OTIM, Fitzgerald's (1966) openness to experience, Cattell's (1957) curiosity erg factor, and generated original items based on theory and research. Beswick found correlations with other curiosity measures, general interest, interest in study subjects, perceived competence of ability in a given subject, goals to attend college, and occupational choices. Beswick's instrument captures a competence component suggested to be part of intrinsic motivation. However, like Day's OTIM, the scale demonstrates a strong overlap between curiosity and intrinsic motivation. The self-report instrument developed by Harter (1981) probably measures intrinsic motivation more accurately than Beswick's scale. Developed for children in third through ninth grade, Harter's scale taps a child's intrinsic versus extrinsic orientation toward learning and mastery in the classroom. She defined five separate dimensions using an intrinsic and extrinsic pole: preference for challenge versus preference for easy work, curiosity/interest versus teacher approval, independent mastery attempts versus dependence on the teacher, independent judgment versus reliance on the teacher's judgment, and internal versus external criteria for success/failure. Factor analyses revealed loading on the components of the scale, as expected. Her factors in some respects parallel Malone and Lepper's (1987) taxonomy (challenge, curiosity, control), however fantasy is missing. Validity studies reflect a good fit for the construct as she conceived it. Lepper, Sethi, Dialdin, and Drake (1997) revised Harter's scale to allow for the reporting of both intrinsic and 56

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extrinsic motivation. They discovered that intrinsic and extrinsic motivation are not perfectly inversely correlated, but have a weak negative yet significant correlation. Hamilton, Haier, and Buchsbaum (1984) developed a self-report measure of intrinsic enjoyment and boredom coping for adolescents and adults. They defined intrinsic enjoyment as intense involvement, interest, and absorbed concentration. They characterized boredom coping as a disposition to restructure one's perceptions and participation in potentially boring activities so as to decrease boredom. Both traits were hypothesized to reflect the capacity for good attentional control across a variety of situations. Items include academic, work , and recreational situations. Although Hamilton , Haier, and Buchsbaum examined attentional control, the intrinsic enjoyment items reflect forced choice between intrinsically rewarding and extrinsically rewarding experiences. Intrinsic enjoyment is significantly correlated with an independent measure of intrinsic involvement (defined as a low wish to be somewhere else), the affective experience of potency, self-reports of concentrating with ease, high ego development, an internal locus of control, lack of boredom susceptibility, and evoked potential (EP) indices of attentional change and cortical augmenting. Boredom coping is associated with a higher percent of time actually spent alone, high continuous performance task measures of attentional capacity, and low Minnesota Multiphasic Personality Inventory (MMPI) and research diagnostic criteria indices of psychopathology . Although this instrument seemingly juxtapositions intrinsic motivation with boredom, the two scales are qualitatively 57

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different. Specifically, intrinsic enjoyment reflects choice between inherent enjoyment of an activity versus an extrinsic reward of outcome. The boredom scale represents a forced choice between experiencing boredom or doing something about it. The intrinsic enjoyment scale captures inherent interest in various activities and also correlates with measures of control and competence. Gottfried (1982, 1985, 1990) developed the Children's Academic Intrinsic Motivation Inventory (CAIMI) and the Young Children's Academic Intrinsic Motivation Inventory (Y-CAIMI). She first developed the former inventory for children between the fourth and ninth grade. She later developed the latter inventory for children between seven and nine years old. She defined academic intrinsic motivation similarly for both age groups. Academic intrinsic motivation includes the enjoyment of learning, an orientation toward mastery, curiosity, persistence, task endogeny, and learning challenging, difficult, and novel tasks. The instrument for the older group includes items about reading, math, social studies, science and school in general. For the younger group excluded items about social studies and science. Gottfried has demonstrated positive correlations with achievement, intelligence, and perception of competence and negative correlations to anxiety. To summarize, intrinsic motivation is related to a love of learning for two reasons. First, its definition is inherent interest in an activity, in this instance learning, reflects prima facie evidence for a love of learning. Second, intrinsic motivation seems interrelated to other constructs that also seemingly relate to love lofe learning. 58

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For example, although a few early theorists offered several unique seedlings of thought about intrinsic motivation, intrinsic motivation research is bound very tightly at the hip with curiosity research. A majority of researchers saw the two constructs as the same thing. However, specific research about intrinsic motivation grew into a distinct area with two definite parts. One part focused specifically on intrinsically motivating tasks. The other part focused on the contrast between intrinsic motivation and extrinsic motivation. Measurement of intrinsic motivation has shown relationships between intrinsic motivation and curiosity as well as intrinsic motivation and challenge (further discussed with flow), intrinsic motivation and control (discussed with both flow and self-concept below), and intrinsic motivation and boredom (a variable in this study). Inherent interest in an activity remains the key criteria for intrinsic motivation. However, it is evident that intrinsic motivation is inherently interconnected with numerous variables related to the love of learning. Flow Flow is a natural offshoot of intrinsic motivation because flow is the subjective experience of intrinsic motivation. Deci and Ryan (1985) said "flow represents a descriptive dimension that may signify some of the purer instances of intrinsic motivation, when highly intrinsically motivated, organisms will be extremely interested in what they are doing and experience a sense of flow" (p. 29). Csikszentmihalyi (1988a) explains that scholars have found the concept of flow 59

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theoretically useful and that "flow has become a technical term in the field of intrinsic motivation" (p. 3). One key difference between the two constructs is that intrinsic motivation research focuses on behavior and flow research focuses on subjective experience (Csikszentmihalyi, 1988a). Definition How is the subjective experience of flow characterized? Athletes describe flow as being in the zone. Religious mystics describe flow as ecstasy. Artists and musicians describe flow as aesthetic rapture (Csikszentmihalyi, 1997). Csikszentmihalyi (1988b, 1990) defines nine components of flow. They are (a) a balance of challenge and skill, (b) clearly defined goals, (c) immediate feedback, (d) perceived sense of control, (e) the merging action and awareness, (t) absorbed concentration, (g) loss of self-conscious awareness, (h) loss of a sense of time, and (i) an autotelic self. Auto is Greek for self and telos is Greek for goal or purpose. The autotelic self describes intrinsic motivation when a person is fully engaged in an activity or goal for its own sake. Flow is an autotelic experience of an optimal state that is universally experienced (Csikszentmihalyi, 1988c). The first component of flow is the balance between challenge and skill. This balance is pivotal not only for skill and challenge but for flow and non-flow experiences as well. Challenge is by no means unique to flow. Malone and Lepper (1987) identified challenge is part of a taxonomy of intrinsic motivation. Optimal 60

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challenges, successfully met, lead to feelings of efficacy and competence. This component connects the constructs of flow, intrinsic motivation and self-concept as competence because the aspect of challenge is inherent in all three. The distinction is primarily point of view. With flow, challenge is a component of the subjective experience (Csikszentmihalyi 1988b, 1990). With intrinsic motivation, challenge is part of a descriptive taxonomy of intrinsic motivation (Malone & Lepper, 1987). With self-concept as competence, challenge is a variable (internal vs. external, arousing vs. incongruous) that bridges one's subjective experience with feelings of efficacy and competence or not (Deci, 1975; White, 1959). However, Csikszentmihalyi (1982) also argues that the balance between challenge and skill fosters intrinsically motivated and self-rewarding learning. This kind of learning generates feelings that Maslow (1967) described as peak experiences. In fact, Csikszentmihalyi (1982; 1988a) states that flow is similar to Maslow's peak experience. Such an argument implies that the challenge-to-skill balance of flow is also connected to self-concept as growth, discussed below. Generally, the challenge-to-skill balance is integrated and overlapping with four of the seven conceptual pieces defining love of learning. Secondly, in order for an activity to be challenging, there must be goals whose attainment is uncertain but perceived as achievable. Malone and Lepper (1987) state that explicit goals of intermediate difficulty whose attainment is perceived as achievable give direction and purpose. Such goals have been shown to enhance intrinsic motivation (Malone, 1981; Malone & Lepper, 1987; Manderlink & 61

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Harackiewicz, 1984), performance (Dweck, 1986) and competence (Harter, 1978; Manderlink & Harackiewicz, 1984). The sense that one is in the process of achieving a goal describes part of the flow experience. Combined with this sense is a third component, immediate feedback. As an individual engages in an activity where goals are clearly defined, then feedback about progress towards their achievement becomes part of the process. As an individual progresses towards a goal and receives feedback that the goal is more nearly achievable, his or her subjective experience is positively enhanced. Thus, an individual becomes more engaged in the activity (Manderlink & Harackiewicz, 1984) and more likely to experience flow. This process facilitates goal accomplishment. As with the balance of challenge and skill, goals and feedback provide connectivity to intrinsic motivation and self-concept as competence. With the balance of challenge and skill, goals, and feedback, the perception that one is in control, as another component of flow, fits within the intrinsic motivation taxonomy (Malone & Lepper, 1987) and self-concept as competence (DeCharms, 1968; 1976; Deci, 1980; Deci, 1995; Harter, 1978; Malone & Lepper, 1987; White, 1959). To experience flow, a person needs to feel that he or she is actively involved, is doing something, is a moving force in the activity. Research has demonstrated this in sports (Fredricks, Alfeld-Liro, & Eccles, 1999; Jackson & Roberts, 1992), music (Fredricks, Alfeld-Liro, & Eccles, 1999), art (Massimini & Carli, 1988), social activities (Massimini & Carli, 1988), work (Allison, & Duncan, 62

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1988; Delle Fave & Massimini, 1988, Lefevre, 1988; Neumann, 1999), leisure (Delle Fave & Massimini, 1988; Lefevre, 1988), and learning (Chan, 1998 , Fredricks, Alfeld-Liro, & Eccles, 1999; Massimini & Carli, 1988, Mayers, 1978, Nakamura, 1988; Neumann, 1999). Control along with the three previously mentioned components of flow also appear often in the research literature related to intrinsic motivation and self-concept as competence. The four remaining components comprising flow do not appear as frequently in motivation research. They reflect expressions of conscious experience . Merging action and awareness and concentration on an activity seem to be two sides of a coin. As a person becomes more fully engaged his or her actions (cognitive, behavioral, affective), he or she becomes less distracted by either external or internal stimuli. He or she becomes increasingly absorbed, concentrating more fully on the activity such that action and awareness merge into a singular experience. As this experience continues, a person may lose not only his or her sense of self-consciousness but also a sense of the passage of time . This conscious experience is like being fully asleep to everything else and totally awake to, aware of, and absorbed in the activity of one's attention , as if nothing else exists. Optimal Arousal With these nine components comprising flow, one cannot overlook the possibility that the subjective experience of flow may be the subjective experience of 63

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optimal arousal or optimal incongruity. Indeed, the defining tone of the components of flow taken together hinges upon the balance between challenge and skill, which of itself seems illustrative of optimal arousal. This particular line of thinking hooks into the conceptual understandings and research on curiosity (Berlyne, 1960; 1966; Harlow, 1953), intrinsic motivation, (Day, Berlyne, & Hunt, 1971; Harter, 1981; Hunt, 1971; Malone & Lepper, 1987), and self-concept as competence (DeCharms 1968; 1976; White, 1959). This optimal point, however, may be examined from at least two points of view (Deci & Ryan, 1985); either it is stimulating or frustrating. Researchers who have examined exploratory behavior (Fiske & Maddi, 1961), novelty-seeking (Fowler, 1965; Scitovsky, 1992), and sensation seeking (Ainley, 1987) support the view of an optimal point as stimulating. As Hebb (1955) points out "no arousal no learning" (p. 249). Researchers who have studied the discrepancy model also offer evidence of an optimum in which rather than seeking stimulation, the goal is to reduce incongruity or dissonance (Hunt, 1971). In a similar vein, the goal to reduce uncertainty has also been perceived in terms of an optimum. This view is so important to learning that Kagan (1972) defined the very wish to know as the "motive to resolve uncertainty" (p. 54). This approach hearkens to Berlyne's (1960) research on curiosity (discussed above) where he identified incongruity and uncertainty as two of the collative variables. Berlyne (1963) was able to incorporate optimal psychological and physiological stimulation and incongruity into his theoretical construct of intrinsic motivation. 64

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Whether seeking arousal or reducing incongruity, one's attention becomes more concentrated. Hamilton's (1981) research demonstrates attention is positively associated with absorbing interest and intrinsic enjoyment and negatively related to boredom and psychopathology. Self-regulation of attention provides a fascinating twist to the notion of optimal arousal because it implies that a person has some control and choice in the matter. As such, attentional regulation also connects flow and self-concept as competence. Again, the overlap among the constructs of curiosity, intrinsic motivation, flow, interest, as well as self-concept as competence seems clear . Seemingly, flow is the subjective experience of optimal arousal or challenge. The nervous systems of higher animals function to either increase or reduce stimulation . Noteworthy are those experiences that are not optimum. When a person is not aroused enough, often the experience is boredom. When stimulation exceeds optimum, often the experience is anxiety. (Csikszentmihalyi, 1975; 1982, 1997; Scitovsky, 1992). Research Gross (1982) pointed out that " Learning for its own sake--the so called joy of learning -has been cited often but rarely studied precisely" (p. 166). Flow has been studied across a wide range of activities around the world mostly among adolescents and adults. Although flow is experienced when working and studying (Csikszentmihalyi, 1997), research shows that adolescents most frequently experience 65

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flow in nonacademic activities such as sports, art, music, and socializing (Csikszentmihalyi, 1997; Fredricks, Alfeld-Liro, & Eccles, 1999; Massimini & Carli, 1988). Nonetheless, Csikszentmihalyi (1982) reports that in ongoing studies of adults, one third of their most enjoyable times are spent with intrinsically motivating activities. Half of that third involves learning of some sort whether it is trying out a new recipe or learning a new language. Csikszentmihalyi (1999) states that because flow involves a balance between challenge and skill, it captures that essence of what makes learning fun. Although the notion that learning is fun has remained largely elusive to researchers, they have found evidence of flow in many activities in which adults and adolescents participate. Flow is subjectively experienced and seems to conceptually overlap with intrinsic motivation, interest, self-concept as competence, and self-concept as growth. Although studies demonstrate that flow is universally experienced, flow is less often experienced during learning. Several reasons that may account for this are that (a) learning environments do not often create an optimal challenge-to-skill balance, (b) few studies have specifically focused on learning and flow, and (c) flow experienced during learning is qualitatively different than flow experienced during other kinds of activities. In spite of these shortcomings, as mentioned above, Csikszentmihalyi (1982) argues that "15% of the best everyday experiences occur in the context of learning" (p. 175). Flow is a positive subjective experience defined as part of passion (Fredricks, Alfeld-Liro, & Eccles, 1999; Neumann, 1999). Thus, one may infer that 66

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those who have a love or passion for learning are very likely to experience flow when they learn and are also likely to experience more flow when learning than those who do not have a great love of learning. Interest Love oflearning develops from one's discovered interests. Educators and psychologists have implied, over the last 100 years, that a connection between interests and the love of learning exists. Dewey (1913) was persuaded that true interest was the means through which individuals developed or "became themselves." He believed that it was useful to employ interests to educate a child pointing out that "in learning these things [interests] human offspring are brought to the need of learning other things, and also to acquiring a habit of learning -a love of learning" (p. 67). Thus, he provided some initial connectivity between the constructs of love of learning and interest. In mid-century Arnold (1956) also drew a relationship between interest and love of learning. Referring to love of learning as the desire to know, she argued that a desire to know is innate but continues to develop over time. She believed that once a child's interest is aroused, other problems related to schooling, such as discipline, and so on, diminish. In order to map the relationship between interest and the love of learning, some historical background of interest will be presented. Second, the current theoretical definitions for interest are provided. Next, that portion of the interest 67

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research hypothesized to relate to the love of learning is defined and reviewed. The notion of interest has been around for a couple hundred years. Scholars, however, hold different perspectives regarding what interest is and how to study it. How did these various views of interest develop? Historical Background Early in the nineteenth century Herbart (180611977) developed a philosophy of interest and early in the twentieth century Dewey (1913) introduced a theory of education which connected interest and learning. Both Herbart and Dewey brought out the idea that interest relates to lifelong learning and the self-initiated learning for mastery, from which satisfaction is derived. However, much of the early interest research grew out of vocational interest research (Holland, 1976; Walsh & Osipow, 1986) of the 1950s and 1960s (Schiefele, Krapp, & Winteler, 1992). Then in the mid and late 20th century interest research waned as behaviorism waxed. Research on interest did not disappear, rather interest research was subsumed within similar terms such as attention (Eysenck, 1982), curiosity (Berlyne, 1960), emotion (Izard, 1970), attitude (Evans , 1971), value orientation (Allport, Vernon, Lindzay, 1960), motivation including achievement motivation (Atkinson & Raynor, 1974), intrinsic motivation (Day, 1971, Deci, 1975, Deci & Ryan, 1985), and flow (Czikszentmihalyi, 1975). The labyrinth ofintereconnections among these constructs exists today. 68

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Lately, interest has developed as a broad explanatory concept including both motivation and cognition (Hidi, 1990, Krapp, Hidi, & Renninger, 1992; Renninger, 1984, Schiefele, Winteler, & Krapp, 1988). In fact, Schiefele, Krapp, and Winteler (1992) refer to interest as cognitive motivation. Traditionally however, interest has been researched as either individual or situational interest, reflecting the person environment interaction which characterizes interest behaviors. As such, interest has two foci: influence of individual interests as topic-specific preferences and the effect of interesting environmental factors that trigger a specific situational interest in the learner (Nenninger, 1992). A third foci, topic interest, which combines individual and situational interest, emerged at the turn of this century. Whether individual, situational, or topic interest, both motivation and cognition are involved in the person environment interaction. Theoretical Definitions Most researchers acknowledge that interest originates from some form of person-environment interaction. However, some researchers focus on the former and others on the latter. The former is called individual interest whereas the latter is called situational interest. Individual interest may be conceived of as a disposition or as a personality trait. Situational interest occurs when a state of interest is aroused by features in environment (Hidi, Renninger, & Krapp, 1992). However, topic interest recently appeared on the radar screen as a third type of interest. Topic interest 69

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includes aspects of both individual and situational interest (Ainley, Hidi, Berndorff, 2002). These distinctions are useful for organizing interest research, but how are the several foci characterized? On one side of the coin, individual interests are usually defined as relatively enduring preferences for certain topics, subject areas, or activities (Renninger, 1990; Schiefele, 1990; Schiefele, 1992). The activity may be narrow, as in tennis, or broad, as in athletics (Deci, 1992). However, Deci (1992) indicates that "the more broadly one defines dispositional interest, the more broad can be the outcomes one predicts" (p. 50). Some authors define interest as simply an attitude (Evans, 1971; Gardner, 1975). Others say that dispositional interest includes attitudes, values, self-concept, effectance, and origin motivation (Todt & Schreiber, 1998), implying that interests are inherently part of the personality. Individual interest has been conceived of as part of one's personality in terms of orientations, valuations, and awareness of possibilities (Frenzel, 1992) . Because interests have personal significance, they become integrated into one's value system and even become components of one's self-concept. In addition to the positive feelings associated with interest, and the cognitive value the person ascribes to the object of interest, interest also has an intrinsic character (Schiefele, 1992; 1998). Learning about something is undertaken for its own sake rather than an external reason. 70

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Renninger and her colleagues (Krapp, Hidi and Renninger, 1992; Renninger, 1987) argue that in addition to valuation, individual interest implies an accumulation of stored knowledge about the object or activity of interest. They further specify interest as the relationship between a class of objects and an individual to include stored knowledge and value of which the person may not entirely aware. For these reasons, scholars characterize individual interest as a disposition or personality trait. On the other side of the coin, situational interest is defined by characteristics of a learning environment. Situational stimuli arouse an emotional or actualized state in the individual. This may be temporary or, by engaging in various activities, may become a more enduring or dispositional interest (Anderson, Shirey, Wilson, & Fielding, 1987; Hidi, Krapp, Hidi, Renninger, 1992). Hidi (1990) says that situational interest is most frequently researched as text comprehension and learning, usually in the form of text-based interest. Text-based interest is a specific form of situational interest generated by reading interesting sentences across subjects. This interest results from textual features as well as the individual readers of the text. Research shows that interesting text and stories motivate individuals to read and influence comprehension and learning. Topic interest recently emerged in the literature to account for overlapping conceptual boundaries and rather a lack of distinctiveness between individual and situational interest. Bergin (1999) suggested that, "it is not useful or accurate to claim that a particular factor is purely personal or purely situational" (p. 89). Hidi (1990) 71

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pointed out that individual and situational interest interact and influence each other's development. Thus, topic interest is defined as the result of individual and situational interest interaction (Ainley, Hidi, Berdorff , 2002; Renninger, 2000). However, topic interest is considered a form of individual interest because of its relatively enduring evaluative orientation toward certain topics (Ainley, Hidi, Berdorff , 2002) . Interest, whether individual, situational, or topical is motivational. The two motivation theories most frequently referred to in the literature are expectancy-value theory and intrinsic motivation theory. Expectancy-value theory states that individuals will engage in activities they find interesting and value but will persist in activities where they experience success (Pintrich & Schunk, 1996). Intrinsic motivation involves engaging an object, task, or activity for the inherent enjoyment that accrues while doing so. Deci (1980) believes that interest is implicit in intrinsic motivation and that flow and undivided interest are also intrinsic motivations. Schiefele (1998) suggests that rather than expectancy-value where expectancy implies more external consequences, interest may be considered activity-value motivation, where there is flow, intrinsic motivation, and other affective states. This perspective provides a synthesis of the motivation theories underpinning the concept of interest. That aspect of interest pertaining to love of learning is interest in learning. Ainley (1998) states that "a student's general motivational orientation to learning can be viewed as interest in learning." (p 258). Ainley further distinguishes individual interest in learning as a domain defined in terms of increasing knowledge, 72

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information, and understanding. She and her colleagues define individual interest in learning as "a desire to acquire new information, to find out about new objects, events, and ideas not restricted to any narrow domain. This may involve approaching and acquiring information about something novel or it may involve seeking new information concerning something the student already knows about" (p. 546, Ainley, Hidi, & Bemdorff, 2002). Difficulty in interpreting the research literature on interest occurs for several reasons. One, the conceptual distinctions among individual, situational, and topic interest are blurred. Two, the theoretical underpinnings of cognition, affect, and motivation have not been clearly established. Three, interest is theoretically interrelated with a number of other researchable constructs. The section of this field of research that particularly pertains to love of learning is interest in learning. Scholars suggest that a general interest in learning may be an important component in the love of learning (Bergin, 1999; Krapp, Hidi, & Renninger, 1992). However, this area of research has not been explored widely. What follows is a summary of research relevant to a general interest in learning. Research Typically, results of research demonstrate that those who are interested in particular activities pay closer attention, persist for longer, learn more, and enjoy more (Hidi & Bemdorff, 1998; Hidi & Harackiewicz, 2000; Prenzel, 1992; 73

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Renninger, 1989, 1990; Schiefele, 1991; 1998). Some research has documented a relationship between interest and achievement. Some research has shown relationships among depth of interest, depth of learning, and satisfaction with learning. Finally, some research has revealed a love of academic learning factor. Taken together, interest in learning, academic or otherwise, indicates a possible love of-learning trait. Interest in learning usually is assessed with achievement. Schiefele, Krapp, and Winteler (1992) conducted a meta-analysis of 121 studies and found reported correlations between interest and achievement ranging from . 09 to .67. Most correlations were in the .2 to .4 range. Krapp, Hidi, and Renninger (1992) conclude that the relationship between individual interest and academic achievement at best is .3, but is a function of gender, school subject, and age/grade level. However, a positive correlation between interest and achievement may not tell the entire story. Other variables may be involved. Prenzel (1992) studied 27 college-aged students who reported their enjoyment, flow, and sense of competence for computers and guitars. Participants with higher levels of interest, assessed as persistence, also experienced higher levels of enjoyment, flow, and sense of competence. Though interest in computers or guitars is not the same as a general interest in learning, Prenzel's results reveal the process and experience of interest in general. Thus, Prenzel' s findings are consonant with the 74

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definition of love of learning although not specifically focused on a general interest in learning. Ainley (1998) conducted several longitudinal studies of females by administering the depth of-interest curiosity scale (Ainley, 1986), quality of school life scales, and Learning Process Questionnaires (LPQ) (Biggs, 1987) at the 7th, 9th, and 11 th grade level. Those who changed in their depth-of-interest (DOl) scores, also scored differently on the quality of school life scales, and the LPQ. Differences between the two groups were significant. Those who maintained high levels of depth of interest were also satisfied with the quality of their schooling, and tended to score higher on the deep and achievement oriented learning scales of the LPQ. Likewise, those students whose DOl showed less satisfaction with schooling, tended to score higher on surface-oriented learning scale. More recently, Ainley and her colleagues (Ainly, Hidi, & Berndorff, 2002) examined several mediating processes between interest and learning. They found that topic interest "related to affective response, affect to persistence, and persistence to learning" (p. 545). They found that individual interest in learning was positively and significantly related to several mediating variables in three of the four topics. Although they were unable to explore a full model of contingencies, Ainley and her colleagues research implies that interest in learning is related to deeper learning and a satisfaction with the learning experience. Her studies tie together the interest , positive affect, and achievement threads of interest in learning research. 75

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Ainley and her colleagues are developing an interest-in-Iearning construct. However, her construct is very strongly defined by Bedyne's definition of curiosity. On the other hand, other researchers have discovered a specific academic interest factor. Caracosta and Michael (1986) developed the Dimensions of Self-Concept (DOSC) instrument and administered it to 239 undergraduate college students. Though the sample size was small, a factor analysis confirmed five subscales. One factor was labeled Academic Interest and Satisfaction. Michael, Smith, & Michael (1989) defined the academic interest and satisfaction factor as follows: portrays the sheer love of learning and pleasure gained by students in doing academic work and in studying new subject matter; an affective state much like that realized by the dedicated scholar who gains tremendous satisfaction in working in the library, in reading great books, in writing research papers, and in conceptualizing new theories or explanations for observed phenomena an intrinsic motivation involving learning for it's own sake (Michael, Smith, & Michael, 1989, p. 2). Caracosta and Michael (1986) found significance between this factor and self-report estimates of past and future grades, and specific grades in the class. These correlations further affirm the relationship between interest in learning and achievement as well as portray academic interest as including an affective state. This particular construct appeared again in developing the Studies Attitudes and Methods Scale (SAMS) (Michael, Denny, Ireland-Galman, and Michael, 1986). SAMS has six scales. Each scale has five subscales with five items each. SAMS was administered to 181 community college students. A principal components analysis 76

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identified five factors. One of the five factors was the Academic Interest love of learning scale. The authors note that this factor defines a separate dimension but also shares some variance with the general trait indicative of a positive orientation to study effort. They defined this factor similarly to the definition for Academic Interest and Satisfaction in the DOSe. Thus, there is some statistical evidence of an interest-inlearning factor, although the factor uncovered using these two instruments has a particularly academic focus. Research sheds light on interest in learning, and thus to some extent, the love of learning. However, conceptual definitions overlap to such an extent that it is difficult to see the forest for the trees. How can these overlapping meanings be characterized? Relationship of Interest to Other Love of Learning Constructs The complexity of theories and research on interest in learning comes from the interconnected web of similar constructs. Researchers (Todt & Schreiber, 1998; Schiefele, 1998) occasionally refer to curiosity, intrinsic motivation, flow, and sense of competence synonymously with interest. Sheifele, Krapp, and Winteler (1992) state that "interest has been used interchangeably with terms such as intrinsic motivation, subject-related affect, attitude, and cognitive motivation" (p. 189). Bergin (1999), who noted that a key to nurturing the appreciation for learning is catching and 77

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holding interest, identified attention, curiosity, and engagement as synonyms of interest. How may these constructs be distinguished? The strongest overlap seems to be with interest and curiosity. For example, Ainley (1986; 1987; 1998; Ainley, Hidi, & Bemdorff, 2002) believes there are strong connections between curiosity and interest. She administered 12 subscales from five measures of curiosity to 227 college students. The factor analysis she conducted showed two factors, which she labeled depth and breadth of interest (Ainley, 1986; 1987). In 2002 Ainley, Hidi, and Bemdorff defined depth-of-interest curiosity as general interest in learning. However, Hidi and Anderson (1992) suggest specific differences between curiosity and interest. They point to Berlyne's (1974) research with collative variables (novelty, complexity, surprisingness, ambiguity, variability). The relationships between the collative variables and curiosity look like an inverted U, whereas the relationship between the collative variables and interest is monotonic. Hidi (1990) notes that life themes and character idenfitification are interesting but are not collative variables. As constructs, curiosity and interest overlap but are not the same. Second in overlap strength is intrinstic motivation and interest. As previously indicated, intrinsic motivation provides some the theoretical foundation for interest. Deci (1998) states that interest is implicit in intrinsic motivation and that intrinsic motivation occurs because an activity is interesting. Additionally, Hamilton, Haier, and Buchsman (1984) characterize intrinsic enjoyment as intense involvement, 78

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interest, and and absorbed conentration. Research by Todt and Schreiber (1998) shows that intrinsic motivation is very similar to interest. However, Rheinberg (1998) points out that interest is activity-indifferent because many activities may bring a person in touch with an object or area of interest. Intrinsic motivation, however, is the desire to perform an activity and is inherent in the activity itself, with or without an object of interest. Therefore, Hidi and Harackiewicz (2000) suggest that the two constructs are recursively related to each other, one building on the other and so forth. The two constructs seem closely connected although they are not the same. Appendix B shows some of the various definitions for curiosity, intrinsic motivation, and interest. Often people believe that interest is the same as liking. However, Hidi & Anderson (1992) distinguish between them. Berlyne (1974) found that liking reached a peak at intermediate levels of uncertainty forming a curvilinear relationship whereas interestingness increased linearly with uncertainty and did not decline. Iran-Nejad (1987) found that surprise endings to stories do not affect liking but do affect interestingness. He also showed that the outcome valence (goodness, badness) of a story influences liking but not interestingness. Thus, interest in learning is different than liking to learn. In summary, among the overlapping constructs that comprise love of learning, interest seems related to but different than curiosity and intrinsic motivation. 79

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Additionally interest is not same as liking. Thus, interest in learning offers a unique aspect to the love of learning construct. Summary Interest in learning involves motivation, affect, cognition, and may be portrayed as individual interest. Interest in learning seems to relate to ' curiosity and intrinsic motivation. Research suggests that such a trait exists, and results in deeper learning. Individual interest in learning is hypothesized to be an aspect of love of learning. Theorists, however, believe that this aspect is rare. Voss and Schauble (1992) suggest that love of learning is the exception rather than the rule when they say some "individuals may want to learn for the sake of learning, although typically learning is related to a more particular goal or interest" (p. 105). Additionally, Hidi and Harackiewicz (2000) note that "all children have interests, motivation to explore, to engage, but not all children have academic interests and motivation to learn to the best of their abilities in school" (p. 168). Thus, love of learning may be conceptualized as a dispositional trait that includes a specific interest in learning. Some theorists focus on how self-concept is involved in interest in learning. William James (1890) noted that "each of us literally chooses, by his way of attending to things, what sort of universe he shall appear to himself to inhabit" (p. 424). DeGarmo (1902) stated that 80

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interest is a feeling that accompanies the idea of self-expression. It has its origin in the exhilaration, the sense of power, of mastery, that goes with every internally impelled effort to realize a condition for the survival of the self, whether such survival touch one aspect of the man or another (p. 18). Dewey (1913) noted that genuine interest indicates personal identification with a course of action. Deci (1998) believes that intrinsic motivation and interest are inherent in an innate self , which seeks to develop or actualize . Hannover (1998) states that "the development of self-concept and interests mutually influence each other" (p. 117). Is there are relationship? Self-concept in Terms of Competence, Growth and Complexity, and Meaning and Purpose The third circle of the conceptual framework for the love of learning construct invol ves self-concept in terms of effectance, growth and complexity, and meaning and purpose. Defining a disposition such as love of learning is difficult without addressing how such a disposition pertains to one's self. For scores of years scholars have been not only describing constructs such as curiosity, interest, intrinsic motivation, and flow in terms of one's self or perception of oneself, but have extended their writing, as well, to what the self or self-concept might be . Allport (1955) for example, describes functional autonomy and propriate striving. DeCharms (1968) and Heider (1958) outline personal causality and causation. Csikszentmihalyi (1985; 1993) expounds on the increasing complexity of self. Maslow (1943, 1967) 81

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defines self-actualization. For the love of learning conceptual framework, self concept in terms of competence, growth, and purpose represents an organizing principle. As such it provides the who and why of love of learning as the other constructs, i.e. curiosity, intrinsic motivation, interest, and flow, provide the behavioral , cognitive, and affective manifestations of the what and how of love of learning. In this section self-concept will be defined. In the following sections, the fields of research relating to competence, growth, and purpose will be reviewed . Self-concept Maslow (1968/1982) defined self-concept as the ongoing actualization of potential, capabilities, and talents, as fulfillment of mission, as a fuller knowledge and acceptance of the person's own intrinsic nature, as a trend toward integration within a person . Bandura (1977a) defined self-concept as an evaluative component where a negative self-concept is a proneness to devalue oneself and a positive self-concept was a tendency to favorably judge oneself. Marsh and Shavelson (1985) broadly defined self-concept as a person ' s perception of himor herself formed through interpretations of one's experiences, including evaluations by significant others . However, they believe that self-concept is multifaceted because people tend to categorize information they have about themselves and relate these categories to one another. Although scholars tend to agree with the multifaceted nature of self-concept, defining specific facets has remained problematic. Marsh and Shavelson believe that 82

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self-concept may be divided into academic self-concept and non-academic selfconcept, where academic subjects comprise academic self-concept and social, emotional, and physical self-concepts comprise non-academic self-concept. Michael, Smith, and Michael (1989) developed a self-report inventory consisting of five school-related factors of self-concept. The factors include level of aspiration, anxiety, academic interest and satisfaction, leadership and initiative, and identification versus alienation. The factor the authors define as academic interest and satisfaction partially coincides with Marsh and Shavelson's academic self-concept as well as with the love of learning construct. The authors define this factor as follows: portrays the sheer love of learning and pleasure gained by students in doing academic work and in studying new subject matter, an affective state much life that realized by the dedicated scholar who gains tremendous satisfaction in working in the library, in reading great books, in writing research papers, and in conceptualizing new theories or explanations for observed phenomena an intrinsic motivation involving learning for it's own sake (p. 2). Other than this conceptual coincidence, the love of learning self-concept in term of competence, growth, and meaningfulness does not fit well within Marsh and Shavelson's hierarchy. Rather, it represents self-concept across all categories because some manner of lealning can and does take place across all the proposed categories. In this study self-concept is conceived of as having three aspects relevant to the love of learning construct. The three aspects are competence, growth and 83

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complexity, and meaning and purpose. These three aspects of self-concept are described below. Self-concept in Terms of Competence Self-concept in terms of competence or effectance involves the experience of being effective, the affective experience of efficacy, and the sense of having some control over the outcomes of one's actions. These concepts are described below . Effectance. Widely cited , White (1959) stated that competence refers to "an organism's capacity to interact effectively with its environment" (p. 297). Webster's Third New International Dictionary of the English Language Unabridged (1981) defines competence as sufficiency and the quality or state of being functionally adequate or of having sufficient knowledge, judgment, skill or strength. Random House Webster's Unabridged Dictionary, 2nd edition (2001) defines competence as adequacy; possession of required skill , knowledge, qualifications, or capacity. Key ideas are sufficiency, adequacy, requisite ability for some purpose. White argued that Hull's traditional drive theory and Freud's psychoanalytic instinct theory are incomplete motivational models of both human and animal behavior. These theories do not explain behaviors such as exploration, mastery, play, and one's general attempt to deal competently with one's environment. White believed that people manifest an intrinsic urge toward competence and he thought that when gratified, this 84

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urge produced inherent pleasure. Since White wanted to capture the motivational aspects of competence, he proposed a new name, effectance. Harter (1978) studied effectance in more detail and developmentally. Based on White (1959), she isolated four components of effectance motivation at different developmental levels: (a) response variation; (b) curiosity for novel stimuli; (c) mastery for the sake of competence; (d) preference for challenging activities. The difference between the third and fourth component is that the third component involves the experience of mastery and the fourth provides a great sense of efficacy. Mastery motivation is the desire to solve cognitively challenging problems for the gratification inherent in discovering the solution. Dweck (1986) further explored mastery learning. She found that success usually leads to feelings of efficacy or intrinsic pleasure. Harter's four components of effectance parallel Malone and Lepper's (1987) taxonomy of intrinsic motivations described earlier. This suggests that Harter's components of effectance overlap in meaning with several constructs (i. e., curiosity, intrinsic motivation, and self-concept in terms of competence) hypothesized to comprise love of learning. Using the four components of effectance, Harter (1981) developed a self report scale that taps a child's intrinsic versus extrinsic orientation toward learning and mastery in the classroom. Five separate dimensions are defined by an intrinsic and an extrinsic pole: preference for challenge versus preference for easy work, curiosity and interest versus teacher approval, independent mastery attempts versus 85

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dependence on the teacher, independent judgment versus reliance on the teacher's judgment, and internal versus external criteria for success or failure. Higher order factoring revealed two interdependent clusters of subscales: the first three dimensions form the first factor and were interpreted as motivational in nature; the remaining two dimensions form a second factor and were interpreted as cogniti ve informational in nature. Whether motivational or informational, the two factors also reflect an overlapping nature of Harter's effectance components, which further suggests that the definition of love of learning is comprised of these and other overlapping constructs. For example, curiosity and interest are constructs believed to comprise love of learning. As well, preference for optimal challenges has been identified as part of flow and intrinsic motivation. Finally, desire for mastery is conceived as part of self-concept in terms of competence. The second factor also coincides with self-concept in terms of competence, because perceived control encompasses internal versus external points of influence. Efficacy. As noted above, effectance involves feelings of efficacy. White (1959) acknowledged that the feeling of efficacy is subjective side of effectance. He thought that efficacy comes from satisfaction aroused by novelty in stimulus and response, and when one's response affects change in the environment. This idea aligns efficacy with Berlyne's epistemic curiosity, however, it adds the dimension of efficacious affect. Other researchers concurred with this added dimension. For 86

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example, Deci (1975) stated that "effectance motivation causes behaviors which allow a person to have feelings of efficacy" (p. 55). Further, Harter (1978) pointed out that competence, and internal perception of control enhance feelings of efficacy or intrinsic pleasure. Bandura (1977) believed that efficacy is more than a result of effectance. He presented a theory in which efficacy served as a cognitive central processor. In his model expectations of personal efficacy are derived from four principal sources of information: performance accomplishments, vicarious experience, verbal persuasion, and physiological states. Bandura proposed that cognition's role is in the acquisition and regulation of behavior and motivation's role is primarily concerned with activation and persistence of behavior. He suggested that efficacy played a cognitive role in processing information. Efficacy information processing leads to learning, or the acquisition and regulation of new cognitive and behavioral patterns. However, learning and efficacy information processing both influence the motivational processes. Skinner, Zimmer-Gembeck, and Connell (1998) found that self-efficacy, defined as beliefs about capacity and control, related to self-regulation and predicted individual goal setting, initiation and implementation of action, and persistence. Her study may be interpreted to show how efficacy, as part of effectance, is part of the conceptualization of love of learning. Specifically, initiation and implementation of 87

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action and persistence are arguably behavioral descriptors for intrinsic motivation, curiosity, and interest. Mayers' research (1978) connected feelings of efficacy, intrinsic motivation, and flow. He stated that intrinsic to intrinsic motivation is the emotional response: feeling efficacious . He studied 80 high school students. Participants included 80 boys: 20 each freshmen, sophomores juniors, and seniors, and 40 from the working class. His study was a sex by age by social class design with five students per cell. Data collection involved two 40-minute interviews with each student and each student's self-reports from a time sampling. He found that appropriate challenge, flow experiences and enjoyment, and feelings of efficacy lead to positive moods, stronger wish to be in learning environments, increased class involvement, and stronger academic performance. His finding supports Bandura's mddel and by implication suggests that the definition of love of learning includes overlapping constructs of intrinsic motivation, flow, and self-concept in terms of competence. Perceived control. Effectance and feelings of efficacy imply that a third factor may be involved. This factor is control. In fact Malone and Lepper (1987) felt that control was a cornerstone of the traditional analysis of intrinsic motivation. The self concept as competent encompasses the idea that a person believes that he or she has some control over outcomes in a learning situation. Control has received a wide amount of attention. Skinner (1996) found over 100 terms related to perceived 88

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control. Those pertinent to love of learning include personal causality and causation, locus of control, self-detennination, and perceived control. An early perspective of control consists of personal causality and causation (Heider, 1958; DeCharms, 1968; 1976). Heider (1958) introduced the concept of personal causality by stating that "intention is the central factor in personal causality" (p. 100). DeCharms (1968) extended the construct by defining personal causation as "the initiation by an individual of behavior intended to produce a change in his environment" (p. 6). He believed that all bf humankind had an internal locus of causality and that "man's primary motivational propensity is to be effective in producing changes in his environment" (p. 269). As deC harms stated, "man is the origin of his behavior. This forms the essence of the concept of personal causation" (p. 271). However, deCharms felt that individual differences existed such that individuals could be categorized as origins or pawns. He defined origins as those who perceive their behavior as detennined by their own choosing and pawns as those who perceive their behavior as detennined by external forces beyond their control. DeCharms (1976) extended his origins and pawns concept into the classroom. StUdying 1200 students in 32 classrooms across the 5th, 6th, 7th, and 8th grade, he found that student motivation and achievement were higher in those classrooms where teachers had been trained to foster origin attitudes in students. In alignment with Heider's personal causality and deCharms personal causation, Rotter's (1966) conception of internal locus of control was that successful 89

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encounters with one's environment lead to beliefs that one is competent and selfdetermining. External control implies a defensive response to failure to interact effectively with environment. Rotter described loci of control this way: When a reinforcement is perceived by the subject as following some action of his own but not being entirely contingent upon his action, then, in our culture, it is typically perceived as the result of luck, chance, fate, as under the control of powerful others, or as unpredictable because of the great complexity of the forces surrounding him. When the event is interpreted in this way by an individual, we have labeled this a belief in external control. If the person perceives that the event is contingent upon his own behavior or his own relatively permanent characteristics, we have termed this a belief in internal control (p. 1). Rotter became concerned with the question of whether or not people believe that their own behavior, skills, or internal dispositions determine what reinforcements they receive. He developed the InternalExternal Locus of Control Scale, with 29 forced choice items to assess this belief. The instrument has had good reliability and validity. Connecting with Rotter's loci of control as self-determining, Deci (1975) interpreted an internal locus of control as being somewhat like intrinsic motivation. He declared that "intrinsically motivated behaviors are behaviors which a person engages in to feel competent and self-determining," (p. 61) incorporating the idea of self-determination. His self-determination model grew from intrinsic and extrinsic research where findings had been mixed. Basically, Deci and Ryan (1985) proposed that self-determination was comprised of three causality orientations. They conceptualized causality orientations as relatively enduring aspects of people that 90

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characterize the degree of self-detennination of their behavior. The three orientations are autonomy, control, and impersonal. They defined autonomy as experienced choice, high intrinsic motivation, and self-detennination regarding extrinsic rewards. They conceived of control as doing something because it should be done and relying on controlling events such as deadlines. Finally, they conceptualized the impersonal as feelings of incompetence and an inability to master one's situations. The orientations are measured by three subscales of the General Causality Orientations Scale (Deci & Ryan, 1985). The scale was shown to have internal consistency and temporal stability. The orientations fit appropriately into a theoretically-relevant network of constructs and behaviors. Using this instrument to assess teachers, Deci, Schwartz, Sheinman, and Ryan (1981) studied 115 students in the fourth to sixth grades and found that in autonomy-oriented classrooms, students felt better about themselves, were more intrinsically motivated to learn, and seemed to perform better. Zimbardo (1969) and Langer (1975) both thought that perception of control is more important that actual control. Skinner, Zimmer-Gembeck, and Connell (1998) defined perceived control as a "set of beliefs about how effective the self can be in producing desired and preventing undesired outcomes" (p. 2). They conducted a longitudinal study that included 1600 students in the third through seventh grades. They collected data every Fall and Spring for three years. Data consisted of self reports, teachers' reports of engagement, and a subset of grades and achievement tests. They examined individual differences and growth curves using hierarchical 91

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linear modeling. Their results, like deCharms (1976) and Deci et al (1981), showed that supportive teachers were correlated positively with positive control while unsupportive teachers were correlated with disaffection, lower grades, doubting skill, trusting luck. They found that perceived control is a strong predictor of academic achievement and that academic achievement influences perceived control. Deci (1995) drew an equivalence between effectance and intrinsic motivation. He stated that intrinsic motivation is the desire to be the origin of one's own actions and that feeling competent and feeling enjoyment are rewards of intrinsic motivation. Because of the interconnectedness of these constructs, there is reason to believe that self-concept in terms of competence is a defining part of love of learning. Self-concept in Terms of Growth and Complexity DeGarmo (1902) explained that impulses, desires, interests, and volition are part of the self, seeking through its own activity to express or realize itself. DeGarmo suggested that beyond survival, humankind has a "curiosity to know, response to beauty, reverence for what is good and noble" (p. 13). He believed that human beings are in the process of transforming themselves into their ideal nature. This line of thought suggests that the self-concept in terms of growth is part of the love of learning construct. 92

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Allport (1955) described this transformation as a transitive process of change and becoming. His was a psychology of personality and the personality's process of becoming. He believed that becoming involves our own individuality, which gives us insights for acquiring orderly knowledge about life. In fact, he thought that the personality is a process of becoming, which is governed by a disposition to realize one's possibilities. He described becoming as the process of incorporating earlier stages into later and when that is impractical, of managing the conflict between early and late stages as well as one can. Allport used the term propriate striving to describe the process of becoming. Propriate striving is central to our sense of existence, unifying our personality. Inherent in Allport's process of becoming is a sense of autonomy. Autonomy is one of three causality orientations, which reflect Deci' s self determination theory (1980), discussed above. What is meant by autonomy? Angyal (1967/1941) described life as a process of self-expansion with a general trend toward increasing autonomy. He stated that autonomy means governed from within. He felt that life processes tend towards increasing autonomy. Life processes do not simply maintain life but transcend to interact with an ever increasing realm of events. Thus, Angyal conceived of life as a self-transcending process, reflecting the process towards increasing autonomy. The tendency toward increased autonomy is not the only tendency in human beings. Inherent as well, in the process of becoming and in increasing autonomy, is the concept of increasing complexity. Csikszentmihalyi (1982) stated that intentional 93

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and intrinsically-motivated activity leads to learning or changes in the complexity of the organism. He thought that this kind of learning, which is reflected in the ability to find increasingly complex challenges and increasing self-improvement, fosters the personal growth and happiness. Wlodkowski and Ginsberg (1995) agreed that challenging learning experiences are intrinsically motivating because they increase the complexity of th.e individual. Maslow (1968/1982) probably drew the connection between love of learning and self-concept in terms of growth and increasing complexity most clearly. He described the need to know for its own sake, for sheer delight as part of growth, actualizing human potential, and expressing inherent nature. He said that this growth is followed by exhilaration and illumination . Maslow (1971) suggested that the ultimate goal of education is to help the person fulfill his or her potential as a human being. This is accomplished through the actualization process of the individual. Maslow (1971) believed that the self-actualization process is about self-growth. Ryff (1985) indicated that the theories of Allport and Maslow represent the field of growth psychology. Growth psychology offers a unique perspective in defining the love of learning. As Deci (1995) suggested, "the strivings for competence and autonomy together -propelled by curiosity and interest -are complementary growth factors that lead people to become increasingly accomplished and to go on learning throughout their lifetimes" p. 71. This remark implies a desire 94

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to learn, if not an actual love of learning. Thus, there is reason to believe that the love of learning construct is comprised of self-concept in terms of growth and complexity. Selfconcept in Terms of Meaning and Purpose A theme throughout educational literature has been, and continues to be humankind's need or desire to find or have a meaningful purpose in life. DeGarmo (1902) believed that "the self is seeking through its own activity to express or realize itself' (p. 12). This statement weaves together the idea of intrinsic motivation and self-concept in terms of meaning. Love of learning is being conceptualized to include an aspect of the self finding meaning and purpose. What is meant by meaning? A number of conceptions exist regarding what meaning is. Langer (1942) posited that there is a "basic and persuasive human need to invest meaning in one's world, to search for and find significance everywhere" (p. 164). She argued that our purposes influence who we are, what we perceive, and how we think and feel. They shape our reality. Similarly, Cohen, Stotland, and Wolf (1955) introduced the notion of the need for cognition. They stated that the need for cognition corresponds to the individual's tendency to organize his experience in a meaningful manner. Individual differences emerge from the degree to which people need to experience an integrated and meaningful world. Buhler (1965) stated that humans live with intention and purpose, and that having a purpose gives meaning to 95

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life. Maddi (1970) reasoned that finding meaning in life was inherent in human nature and stemmed from our cognitive needs to symbolize, imagine, and judge. Deci (1975b) thought that Maddi's theory connected humankind's search for meaning with intrinsic motivation and self-concept in terms of competence. One of the most influential thinkers in this area is Victor Frankl. Frankl (1969/1988) declared that living with intention comprised a motivation theory describing humankind's self-transcendent process. He called the theory the will to meaning. He believed that life never ceases to have meaning. However, he thought that when the will to meaning is frustrated, an individual experiences existential frustration or vacuum. Frankl believed that people today are tense because they have experienced a loss of meaning in their lives. The loss of meaning has manifested as a states of boredom and apathy. He defined boredom as the incapacity to take an interest and apathy as the incapacity to take initiative. He strongly believed that education should foster and refine the capacity to find meaning. Love of learning is conceptualized to be a major process by which human beings find meaning in their lives. Meanings are found not given. Frankl believed that the pursuit of happiness was illusory, that happiness ensued from having or finding a reason to be happy. He described the will to meaning as the finding of the reason to be happy. Crumbaugh and Mahollick (1981) believed that one of humankind's primary motives is the will to meaning and that human beings seek meaning and purpose in their lives. They developed the Purpose in Life Test to assess Frankl's will to 96

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meaning (Crumbaugh & Maholick, 1963). The Purpose in Life Test has 20 items and uses as-point bi-polar scale. They administered the test to 1151 sUbjects. Split half reliability is .81 and Spearman-Brown correction to .90; again as .85 and .92 respectively. Crumbaugh and Maholick demonstrated that the will to meaning is independent of other personality variables. Whereas Frankl (1969) and others focus on meaning as the having of reasons and purpose, others, such as Suchman (1971) and Mezirow (1991), address meaning as learning and interpretation. Suchmari (1971) described the pursuit of meaning as the desire to inquire. He described inquiry as natural, as the pursuit of new meanings and experiences, and as free and self-directed. He felt that a sense of autonomy was inherent in the pursuit of meaning, which connects this part of self-concept to self concept in terms of growth and complexity. Suchman delineates closure and "opensure" as types of motivations to inquire. Closure motivation is the seeking of a correct answer or some sort of problem-solving. Opensure, on the other hand, is the seeking of experiences, for the purpose of producing or finding meaning. In developing his comprehensive theory on transformative learning Mezirow (1991) mentions meaning as interpretation. He states that we must be able to "name" our reality to be free, and it is this process that the finding of meaning and purpose takes form. Adults learn to negotiate meanings, purposes, and values critically, reflectively, and rationally instead of passively accepting things. Mezirow defines meaning schemes as comprised of specific knowledge, beliefs, value judgments and 97

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feelings from experience. He defines meaning perspectives as created by ideologies, learning styles, self-deceptions, codes that govern the activities of perceiving, comprehending, and remembering. For Mezirow, meaning is an interpretation construed through thought and language. Mezirow thought adult learning includes the process of confirming or negating meaning schemes and restructuring meaning perspectives. He pointed out that in meaning making humans construe experience and give it coherence. Wlodkowski and Ginsberg (1995) stated that enhancing meaning is one of four primary components of motivation. By enhancing meaning, they meant the creation of engaging and challenging learning experiences that include students' perspectives and values. Wlodkowski and Ginsberg describe three types of meaning. They call the first type of meaning deep meaning. because it consists of passionate feelings, a sense of territoriality, and connecting to something greater than oneselves. Caine and Caine (1991) describe this kind of meaning as/elt meaning. Felt meaning is not only personal, but can be profound in that it creates a sense of purpose. Felt meaning encompasses relevance, connection, and emotion. This conception of meaning is like Frankl's will to meaning in that it is profound, emotional, and purposeful. Wlodkowski and Ginsberg call the second kind of meaning suiface meaning because although it explains what and how, emotional significance is absent. However, surface meaning provides identity and clarity. Wlodkowski and Ginsberg 98

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describe the third kind of meaning as emerging relevance. Emerging relevance occurs when learning creates its own meaning, as in the case of insight or confirming a prediction. These two meanings are close to Suchman's and Mezirow's interpretation of meaning. No matter what interpretation is made of the concept of meaning, Frankl (1969) stated that "being human means being in the face of meaning to fulfill and values to realize" (p. 52). This notion compares somewhat to Maslow (1968/1982) conceptualization of self-actualization. However, Frankl (1969) suggested that self actualization is an effect of the will to meaning, of fulfillment of meaning. Whether an effect or not, the two constructs seem related somewhat Maul and Maul (1983) created the Styles of Living Preference Scale to assess the 15 factors of self actualization. One component of their instrument parallels the aspect of love of learning as self-concept in terms of meaning and purpose. This component is meaningfulness of experience. At its extreme meaningfulness of experience describes a profound, mystical, peak experience. For Maul and Maul, meaningfulness of experience also implies the extension of one's boundaries and becoming one with humankind, nature, and the universe. This conceptualization demonstrates a small overlap with the love of learning construct and self-actualization. The common denominator between self-concept in terms of self-concept in terms of meaning and the meaningfulness of experience component of self-actualization is that for both 99

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existence is intentional and transcendental. Other research has been conducted about the finding of meaning and purpose in life, although most is only tangentially related to love of learning. For example, John-Steiner (1985) interviewed many different kinds of creative people asking them about their lives and their work. She found that although these people had unique and various experiences, they all found their lives deeply meaningful. Another example of research is reflected in the work of Merriam and Clark (1991). They assumed an intrinsic connection among work, love, and learning, with events as sources and stimuli for learning. They asked adults to chart their adult life by year, rating each year as good, okay, or bad with reference to love and work. Next, they asked these adults to describe by year various learning experiences and each's significance. Merriam and Clark found that adults' learning is deeply and personally meaningful. Finally, finding meaning and purpose in one's life has been shown to be associated with health, well-being, and happiness. Ryff (1989) undertook the task of defining well-being more comprehensively. Her definitions included six components; four out of five are included in this circle of the conceptual framework. Her research suggested that autonomy, effectance, purpose in life, and personal growth were strongly correlated with constructs thought to relate to well-being. Myers' (1992) findings imply that happiness is enabled through fit and healthy bodies, realistic goals 100

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and expectations, positive self-esteem, feelings of control, optimism, outgoingness, supportive friendships, an intimate, warm, and equitable marriage, challenging work and active leisure, and faith that entails communal support, purpose, acceptance, outward focus, and hope. Key in the very last aspect is the having of a purpose, or a meaning for life. Learning to discover that purpose may become a driving passion. In summary, Csikszentmihalyi (1982) stated that enjoyment comes not from instinctual need but from achievement of emergent goals, responding to opportunities in environment that one learns about ot discovers in the course of one's life. DeCharms (1976) pointed out that a school is a prison for those who can use it to no purpose, while others, even in the most prisonlike schools, sink their pickax to a purpose and find meaning. For a child to find meaning in school he should have a purpose for being there; he should want what the school has to offer; he should be motivated to learn. When he is committed to learning, he will come freely to school because school will have meaning for him (p. 15). Thus, finding meaning and purpose is part of the becoming process of the personality. For as William James (1890) observed "each of us literally chooses, by his way of attending to things, what sort of universe he shall appear to himself to inhabit" (p. 424). Summary Self-concept in terms of competence, growth, and meaning goes beyond the 101

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behavioral, cognitive, affective, and experiential subconstructs defining love of learning. It involves identity and perception. Maslow (1968/1982) defined selfconcept as the ongoing actualization of potential, capabilities and talents, as fulfillment of mission (or call, fate, destiny, or vocation) as a fuller knowledge of, an acceptance of, the person's own intrinsic nature, as an unceasing trend toward unity, integration or synergy within a person. Cp.53). Rotter (1966) theorized that successful encounters with one's environment lead to belief that one is competent and self-determining. Harter (1978) described intrinsic motivation as a self-subsystem "based in the need for competence and selfdetermination. It involves behavioral decision making (self-determined behavior), managing motives effectively, and internal perceived locus of causality, feelings of self-determination, and a high degree of perceived competence or self-esteem" (p. 41). This definition demonstrates the overlap between these constructs hypothesized to define love of learning. Developing a theory, Deci (1980) described how intrinsic motivation is an explanatory concept in two ways. First, organisms need an optimal level of physiological or psychological stimulation, discussed earlier. The second understands intrinsic motivation as the felt need for competence. He saw that inherent in both explanations is a need for optimal challenge. He thought that the process was like a spiral, involving the self striving to be competent and self-determining, seeking and meeting optimal challenges, satisfying those needs, and the accompanying feeling 102

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of efficacy. Thus, these processes are hypothesized to be part of the love of learning construct. Self-concept in tenns of competence, growth, and meaning is intertwined with other love of learning constructs at some level , to some extent, and in some way. Because curiosity, intrinsic motivation, interest, and flow are constructs hypothesized to comprise love of learning, it is likely that self-concept in tenns of competence, growth, and meaning is part of love of learning as well . Implied in Myers (1992) findings regarding the well-being are reasons for why people love to learn. Humans love the process of learning because it provides a sense of competence, feelings of efficacy, increasing autonomy, growth and complexity, meaning and purpose, as well as the experience of flow. Thus , these integrated and overlapping constructs become part of the working definition of love of learning. 103

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CHAPTER 3 METHODOLOGY Introduction The purposes of this study were to define the construct, love of learning, to develop an instrument to measure the love of learning construct, and to estimate its reliability and validity. This chapter presents the design of the study, describes the subjects and sampling procedures, conceptually and operationally defines the variables examined, outlines the instruments which will be used, describes the data collection and analysis procedures, and anticipates the limitations. The research questions of this study are: 1. What subconstructs comprise the overall construct of love of learning within the young adult (18 to 25 years) age group? 2 . What are the relationships among the subconstructs of the love of learning construct within the young adult (18 to 25 years) age group? 3. What are the relationships between the love of learning construct and constructs that likely should have strong correlations with the love of learning construct within 104

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the young adult (18 to 25 years) age group? Specifically, for positive model validity (Krathwohl, 1993): What is the convergent relationship (Campbell & Fiske, 1959) between scores on the love of learning measure and scores on a curiosity measure? What is the convergent relationship (Campbell & Fiske, 1959) between scores on the love of learning and scores on an intrinsic enjoyment measure? Specifically, for negative model validity (Krathwohl , 1993): What is the discriminant relationship (Campbell & Fiske, 1959) between scores on the love of learning measure and scores on an anxiety measure? What is the discriminant relationship (Campbell & Fiske, 1959) between scores on the love of learning measure and scores on a boredom measure? 4. What is the relationship between the love of learning construct and a construct that likely should have an intermediate-size correlation with the love of learning construct within the young adult (18 to 25 years) age group? Specifically, for borderline validity (Krathwohl, 1993), what is the relationship between scores on the love of learning measure and scores on a self-actualization measure? 5. What is the relationship between the love of learning construct and a construct that likely should have low or no correlation with the love of learning construct within the 105

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young adult (18 to 25 years) age group? Specifically, for contrary validity (Krathwohl, 1993), what is the relationship between scores on the love of learning measure and scores on a flexible thinking measure? Design The design of this study was descriptive and correlational , incorporated survey research, and drew on factor analysis and the multitrait-multimethod (MTMM) among other approaches to construct validity. After reviewing the literature, a working definition was developed that love of learning consists of several related constructs (Fiske, 1966b) . These constructs include curiosity, intrinsic motivation, interest, flow, the agency of self in terms of competence, growth and complexity, and meaning and purpose. In phase 1 operational definitions were developed for each construct hypothesized to comprise love of learning, a pool of items was generated for each construct, and a love of learning instrument was developed using a participatory consensus-seeking method with five experts. Interrater agreement and reliability were assessed. In phase 2 the instrument was administered to a sample of college students. College students were chosen because obtaining access to college students was considerably easier than getting the necessary permissions and access to K-12 students within various school districts. Also, a trait, such as love of learning, was thought to be more stable in young adults 106

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than in children and adolescents. The internal consistency and structure of the instrument were examined. In phase 3 several approaches to examining construct validity were undertaken. Using Krathwohl's descriptions (Krathwohl, 1993), validity variables include curiosity and intrinsic enjoyment as positive models, anxiety and boredom as negative models, self-actualization as a borderline model, and flexible thinking or its opposite, rigidity, as a contrary model. The positive and negative model variables were further examined in a hybrid multitrait-multimethod matrix (Campbell & Fiske, 1959). Subjects and Sampling Procedures The popUlation of interest was English-speaking young adults from 18to 25years old living in the United States. Participants were volunteers from community colleges, state colleges, and universities. A total sample of 447 young adults completed the initial love of learning instrument. The sample was large to achieve a 10 to 1 ratio for the factor analyses (Hair et aI, 1998). A subset of the original sample completed an additional battery of six scales. This subset was smaller but large enough to provide stable results, 156 participants. This size is adequate to examine the evidence of validity for the love of learning instrument. Participants were volunteers who met the above criteria and were willing to complete the survey. In 107

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some cases, instructors offered incentives such as credit or extra credit in a course. In a number of instances a chance to win a $25 gift certificate was offered for participating in the validity phase of the study. In other instances, no incentives were provided. Variables The key variables are listed below. An operational definition was developed for each. Variables are organized into five areas. The first area indicates the set of variables hypothesized to comprise the love of learning. The second area consists of two model variables hypothesized to correlate strongly and positively to the love of learning construct. The third area consists of the two model variables hypothesized to correlate strongly and negatively to the love of learning construct. The fourth area consists of one borderline variable hypothesized to correlate moderately with the love of learning construct. The fifth area consists of one contrary variable hypothesized to correlate weakly or not at all with the love of learning construct. Love of Learning Variables The love of learning construct, while periodically used in the educational literature, has rarely been defined. When mentioned, love of learning is usually 108

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associated with such constructs as curiosity, intrinsic motivation, interest, flow, self competence, personal growth, and finding meaning and purpose in life. However, these constructs have been defined, studied, and measured to a moderate extent. It is reasonable to assume that these constructs may form a foundational meaning of the love of learning construct. Thus, an instrument consisting of items that measure these subconstructs may provide an indication of love of learning. The variables thought to comprise love of learning are presented below accompanied by an operational definition of each. Epistemic Curiosity Epistemic curiosity is characterized as information seeking (Spielberger & Starr, 1994, Starr, 1992). It is reflected in the frequency and duration of information seeking behaviors as well as the intensity of the desire (attitude) towards seeking and finding information. Epistemic curiosity was measured as part of the love of learning instrument developed as part of this study. Intrinsic Motivation Intrinsic motivation to learn is defined as learning for its own sake (Deci, 1975; 1980). It is operationalized as freely choosing to engage in learning activities, as engaging in learning activities frequently, as engaging in learning activities for 109

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long periods of time as well as expressing a positive attitude towards engaging in learning activities for their own sake . Intrinsic motivation was measured as part of the love of learning instrument developed as part of this study. Interest Interest in learning implies a relatively enduring preference for and selective persistence in learning over other activities (Prenzel, 1992; Renninger, 1990; Schiefele, 1990; Schiefele, 1992). It is operationalized as preferring to learn about something over another activity as well as selectively persisting in learning. It may be further operationalized as expressing attitudes of preference for learning over other activities as well as selectively persisting in learning. Interest was measured as part of the love of learning instrument developed as part of this study. Flow Flow involves feeling that one's skills are appropriate to the challenge at hand, in a goal-oriented, action-system with clear rules and adequate feedback. One becomes so absorbed that no attention is paid to anything else, self-consciousness disappears, and one may lose track of time. The feeling afterward is so gratifying that a person will engage in this activity for its own sake . Flow is operationalized as when an individual encounters a learning activity where there are clear goals with 110

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immediate feedback and his or her skills are well-matched to the challenge such that he or she is able to concentrate on the activity, forget about outside distractions, experience a merging of action and awareness, lose a sense of self-consciousness and time, and feel that he or she is in control of the situation. Further, after the flow experience, individuals sense a rush of positive and usually want to reengage (Csikszentmihalyi, 1990). Flow was measured as part of the love of learning instrument developed as part of this study. Self-concept in Terms o/Competence The subconstruct of self-concept in terms of competence is conceived of as exercising autonomy and feeling effective (Deci, 1975). It is operationally defined as engaging in behaviors and expressing positive attitudes about being competent. Selfconcept in terms of competence was measured as-part of the love of learning instrument developed as part of this study. Self-concept in Terms o/Growth and Complexity The subconstruct of self-concept in terms of growth and complexity is conceived of as seeing oneself as growing, improving, and increasing in complexity (Csikszentmihalyi, 1982; Maslow, 1968/1982). It is operationally defined as the 111

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engaging in behaviors that one believes will foster growth and self-improvements as well as expressing attitudes that growth, self-improvement etc., are desirable. Self concept in terms of growth and complexity was measured as part of the love of learning instrument developed as part of this study. Self-concept in Terms of Meaning and Purpose The subconstruct of self-concept in terms of meaning and purpose is operationally defined as engaging in that help one find meaning and/or define one's purpose and expressing the attitude that such activities are worthwhile (Crumbaugh & Mahollick, 1981; Suchman, 1971). Self-concept in terms of meaning and purpose was measured as part of the love of learning instrument to be developed as part of this study. Positive Model Variables The positive model variables are variables expected to correlate strongly and positively with scores on the love of learning instrument (Krathwohl, 1993). Probably many variables correlate positively and highly with the love of learning construct, however, two were selected to reflect a cross section of the variables correlating with the love of learning construct. For example, curiosity is a variable that comprises love of learning and one that has been amply researched and measured. A valid measure of love of learning should be strongly and positively correlated to curiosity. Secondly, 112

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intrinsic enjoyment is a broadly defined variable that encompasses intrinsic motivation, interest, and flow. As such, a strong and positive correlation between intrinsic enjoyment and a love of learning measure would provide evidence of validity. The two positive model variables are listed and operationally defined as follows: Trait Curiosity The construct of trait curiosity may be characterized as individual differences in the capacity to experience curiosity and operationalized as scores on the Trait Curiosity Subscale of the Melbourne Curiosity Inventory (MCI) (Naylor, 1981). Trait curiosity was measured as a construct expected to strongly and positively correlate to the love of learning instrument. Intrinsic Enjoyment The construct of intrinsic enjoyment may be characterized by intense involvement, interest, and absorbed concentration (Hamilton, Haier, & Buchsbaum, 1984). Intrinsic enjoyment may be operationalized as scores on the Intrinsic Enjoyment subscale of the Intrinsic Enjoyment and Boredom Coping Scales. Intrinsic enjoyment was measured as a construct expected to strongly and positively correlate to the love of learning instrument. 113

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Negative Model Variables Negative model variables are expected to correlate strongly and negatively with the love of learning construct (Krathwohl, 1993). As with the positive model variables, probably many variables correlate negatively and highly with the love of learning construct, however, two seem particularly relevant to the love of learning construct. The two negative model variables are anxiety and boredom. A relationship has been repeatedly characterized in the research literature among anxiety, boredom, and the particular love of learning subconstructs of curiosity, intrinsic motivation, and flow. Apparently, too much stimulation creates anxious feelings, too little stimulation leads to boredom, and optimal arousal (either external or internal) affords curiosity, intrinsic motivation, and flow-like experiences. Some researchers have suggested that interest and anxiety form a dynamical relationship in the self-regulation of learning (Iran-Nejad & Cecil, 1992). Others conceive of interest and boredom as existing at opposite ends of an attentional regulation continuum (Hamilton, 1984). Thus, a negative correlation between anxiety and love of learning, and between boredom and love of learning would provide evidence of validity for the love of learning measure. The two negative model variables are described below: 114

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Anxiety The construct of anxiety has a worry or cognitive component that relates to negative thoughts and an emotional component that refers to affective and physiological arousal. Often anxiety reflects a reaction to overstimulating situations. Anxiety is operationalized as scores on the Test Anxiety subscale of the Motivated Strategies for Learning Questionnaire (MSLQ) (Pintrich, Smith, Garcia, & McKeachie, 1991). Anxiety was measured as a construct expected to strongly and negatively correlate to the love of learning instrument. Boredom Boredom is characterized as a subjective experience that results from too little stimulation, monotony, low attention regulation, perceived uselessness of information, and perhaps the sense that one is unable to effectively do anything about it. Boredom is operationalized as scores on the Boredom Proneness Scale (Farmer & Sundberg, 1986). Boredom was measured as a construct expected to strongly and negatively correlate to the love of learning instrument. 115

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Borderline Variable A borderline variable is a variable that is conceptually similar but not quite the same as the love of learning construct. Self-actualization embodies the idea of fulfilling one s potential, functioning autonomously, and living a meaningful life (Crandall & Jones, 1991; Maslow, 1968/1982; Maul & Maul, 1983). Thus, self actualization seems to be similar to the aspects of self-concept defined in this study: self-determination, growth and complexity, and meaning and purpose. However, self actualization goes well beyond love of learning. Therefore, a moderate and positive correlation between self-actualization and love of learning would supply evidence for the validity of the love of learning measure. Self-actualization The construct of self-actualization essentially means the discovery of the real self. Self actualization is about self-expression, self-growth, and optimizing potential (Maslow, 196811982). Life becomes more worthwhile (Maslow, 1971). Self actualization is operationalized as scores on the Short Index of Self-Actualization (Jones & Crandall, 1986). Self-actualization was measured as a construct that positively and moderately correlates to the love of learning instrument. 116

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Contrary Variable A contrary case is an example of a variable that has a low or no correlation to the love of learning measure. The variable of flexibility may provide a contrary case. For example, love of learning seems to imply flexibility in thinking. However, such an idea also implies that the opposite of flexibility implies a lack of love of learning. This suggests that a rigid thinking person would not love learning. Such a proposition does not seem a fair or logical. Individuals who are flexible thinkers and individuals who are rigid thinkers both may have a love of learning disposition. Thus, a low or no correlation between flexible thinking and love of learning would provide evidence of validity for the love of learning measure. Flexibility The construct of flexibility is conceived of as a continuum of flexible-rigid thinking. Flexible thinking is a multifaceted construct that encompasses the cultivation of reflectiveness rather than impulsivity, the seeking and processing of information that disconfirms one's beliefs, and the willingness to change one's beliefs in the face of contradictory evidence. Flexibility is operationalized as scores from the Flexible Thinking Subscale of the Generalizable Critical Thinking Scale (Sa, West, & Stanovich, 1999). Flexibility was measured as a construct expected to correlate a little or not at all to the love of learning instrument. 117

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Instrumentation A love of learning instrument was developed for this research. Included in the instrument are the subconstructs of curiosity, intrinsic motivation, interest, flow, and self-concept in terms of competence , increasing growth and complexity, as well as the pursuit of meaning and purpose. Each sub construct is represented with items assessing behaviors and attitudes following Ajzen and Fishbein's (1980) expectancy value model for scaling. The instrument is a five-point Likert agree-disagree response scale. For the positive model validity cases, two existing scales were used. To measure curiosity, a 20-item true-false trait scale from the Melbourne Curiosity Inventory (MCI) (Naylor, 1981) was used . Cronbach's alpha coefficient ranges between .84 and .93 with samples sizes : 98 to 339, consisting of high school students, teacher trainees, and graduate teacher trainees. Test-retest reliability over 25 days with 103 college students was r = .83, and over five weeks with 82 male high school students was r = .77 . The Trait subscale is positively correlated to the State Curiosity subscale. It is positively correlated to the Investigative interest and negatively correlated to the Realistic and Conventional interests of Strong-Campbell Interest Inventory. Intrinsic enjoyment is a broadly defined variable that encompasses intrinsic 118

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motivation, interest, and flow. To measure intrinsic enjoyment, a 9-item forced choice scale from the Intrinsic Enjoyment and Boredom Coping Scales (Hamilton, Haier, & Buchsbaum, 1984) was used. Cronbach's alpha for 63 high school students was low at .43, which authors attributed to low number of items and situation specific nature of content. Test -retest reliability over a one to three week period for 14 nursing students was .68. The Intrinsic Enjoyment Scale was positively correlated to ego development, locus of control, and several measures of attention. For the negative model cases two existing scales were selected. To measure anxiety, the Test Anxiety subscale of the Motivated Strategies for Learning Questionnaire (MSLQ) (Pintrich, Smith, Garcia, & McKeachie, 1991) was chosen. This subscale has five items based on a seven-point Not true at all to Very true of me Likert response scale. Cronbach's alpha has been reported as .80 and the subscale negatively correlates to academic performance. The Boredom Proneness Scale (Farmer & Sundberg, 1986) was selected to assess boredom. It contains 28 true-faise items. Internal consistency using KR-20 with 233 college students was .79. Test-retest reliability over one week with 62 college students was .83. The Boredom Proneness Scale was positively correlated with a composite score of disinterest, with topics rated as boring, and one of two lectures rated as boring. It was negatively correlated with attention. The scale also was correlated positively with other boredom measures, including the Boredom 119

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Susceptibility subscale of Zuckerman's Sensation Seeking Scale (Zuckerman, Kolin, & Zoob, 1964), and from a set of studies evaluating interest and attention in the classroom. For the borderline case self-actualization was measured using the Short Index of Self-Actualization (Jones & Crandall, 1986). This instrument has 15 items using six-point Likert scale of Strongly Agree to Strongly Disagree. Test-retest reliability over 12 days with 67 students was .67 and Cronbach's alpha with 332 students was .65. There are reported high positive correlations with Personal Orientation Inventory (POI) (Shostrom, 1964), self-esteem, rational behavior and beliefs, a negative correlation with neuroticism, and a non-significant correlation with extraversion. The index effectively discriminates actualizers from non-actualizers, based on peer nominations among students. Finally, for the contrary case flexibility was measured using the Flexible Thinking Scale (Sa, West, & Stanovich, 1999). The Flexible Thinking Scale has ten items, using a 6-point spread from Strongly agree to Strongly disagree. Stanovich and West (1997) developed the Flexible Thinking Subscale from the critical thinking literature as part of a battery to assess Actively Open-Minded Thinking (AOMT). Items tap reflective thinking, willingness to consider evidence contrary to one's beliefs, willingness to consider alternative explanations, and tolerance for ambiguity. Split-half reliability (Spearman-Brown corrected) was.49 and Cronbach's alpha was 120

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.50. These are low and may be due to the small number of items as well as the breadth of coverage for content. The FT Scale correlated positively with the openness ideas (.36) and the openness values (.36) subscales and negatively with the absolutism ( .37), dogmatism (-.19), categorical thinking (-.31) and superstitious thinking (-.26) subscales of the AOMT. These correlations suggest that the Flexible Thinking Subscale represents an eclectic conception that correlates a little or not at all to the love of learning construct. Data Collection Procedures Data collection occurred in three phases: instrument development, reliability and instrument structure study, and estimation of construct validity. Phase 1. Instrument Development A pool of 72 items was generated from the literature and derived from other measures. Items were created and categorized according to the operational definitions of each subconstruct they most aptly seem to measure. A panel of five experts rated each item on a three-point scale according to how well it assesses the sub construct and purpose for learning. Interrater agreement and reliability were examined using three methods. 121

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Phase 2. Reliability and Instrument Structure Study The initial instrument was administered to a sample of 447 young adults. Participants were instructed regarding the purpose of the study, that their identity will be protected, and that their participation was appreciated. The data were used to estimate the internal consistency reliability of the instrument, to conduct an item analysis, and to examine the relationships among the love of learning construct and subconstructs hypothesized to comprise love of learning. Phase 3. Construct Validity To study construct validity, the love of learning instrument along with scales assessing the model, borderline, and contrary cases were administered to a subset of the first sample. This phase included 156 participants. This sample size was considered large enough to provide stable results. Data Analysis Procedures Phase I. Instrument Development A panel of five experts in the fields of adult learning and motivation theory evaluated each item on a three-point scale according to how well it assesses the 122

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operational definition of the subconstruct. Items with the highest consensus of Fits quite well among the five raters were selected for the initial love of learning instrument. Interrater agreement and reliability were determined for the initial 72item pool and the 25-item instrument using three techniques Phase 2. Reliability and Instrument Structure Study To assess the reliability of the instrument, Cronbach's alpha (an internal consistency reliability estimation) was estimated and an item analysis was conducted. Cronbach's alpha is a measure of internal consistency, which gives an indication of item content homogeneity. An item analysis was conducted to investigate each item's contribution to the instrument overall. Means among demographic variables were compared. Pearson's correlations among the love of learning construct and subconstructs hypothesized to comprise love of learning were estimated. Finally, an exploratory factor analysis was conducted to "determine whether item responses "cluster" together in patterns predictable or reasonable in light of the" theoretical structure of the love of learning construct (Crocker & Algina, 1986, p. 232). 123

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Phase 3. Construct Validity To estimate validity, the love of learning instrument along with scales measuring the construct validity variables were administered to a subset sample of 156 participants. Evidence for construct validity was examined. Crocker and Algina (1986) identify four approaches for collecting evidence for construct validity. The first two of these , mean differences among groups and factor analysis, were conducted as part of the examination of the love of learning instrument in phase 2. The third and fourth approaches are correlational analysis and multitrait-multimethod analysis. A set of correlational analyses between total scores on the love of learning instrument and scores for each construct validity variable (trait curiosity, intrinsic enjoyment, anxiety, boredom, self-actualization, and flexibility) was conducted during this phase. Further, a subset of the above correlational analyses was examined according to Campbell and Fiske (1959) multitrait-multimethod matrix. Campbell and Fiske thought that the kind of measure could influence the validity of the measure. Examining similar constructs with contrasting measures and different constructs using similar measures provides insight regarding the effect of the type of measurement. 124

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Limitations Although this study may provide a useful definition of the love of learning and a method for measuring it among young adults, it will tell us little of how the love of learning may be fostered, enhanced, and maintained in children. However, a love of learning instrument may provide the beginning. Additionally, there are other limitations to this study. The threats to the validity of this study included possibly an unrepresentative sample. The sample was obtained not randomly but rather by convenience. Those schools and colleges who responded positively to letters of request provided the opportunity to collect data. Students were further given the choice to participate or not. Because it was not feasible to randomly select from among the entire population of 18to 25-year olds, the sample obtained may not truly reflect the population of interest. Of lesser concern but still a potential threat is timing. Since data were collected before and after September 11, 200 1, responses from young adults may reflect attitudes and values of a less certain future. As well, reactive effects, such as Hawthorne effect, John Henry effect, and novelty effect, may influence the way participants responded to the questions on this instrument. Finally, response bias may also be present because all items had positive wording. However, participants were 125

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encouraged to respond honestly and because their identity will be protected, reactive effects may be lessened. Summary This study has three purposes. The first is to define the love of learning construct. The second is to develop an instrument to measure the love of learning construct. The third is to estimate the reliability and validity of the instrument. The design of the study is descriptive and correlational and uses survey research with young adults, 18 to 25 years of age. A sample of young adults was drawn from community colleges, state colleges, and universities. Along with a love of learning instrument developed as part of this study, the Trait Curiosity subscale of the Melbourne Curiosity Inventory (MCI) was used to assess trait curiosity. The Intrinsic Enjoyment Scale of the Intrinsic Enjoyment and Boredom Coping Scales was used to assess intrinsic enjoyment. The Test Anxiety subscale of the Motivated Strategies for Learning Questionnaire (MSLQ) was used to assess anxiety. The Boredom Proneness Scale was used to assess boredom. The Short Index of Self-Actualization was used to assess self-actualization. Finally, the Flexible Thinking subscale of the Active Open Minded Thinking (AOMT) was used to assess flexibility. Variables included within love of learning construct are curiosity, intrinsic motivation, interest, flow, the agency 126

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of self in terms of competence, increasing growth and complexity, and finding meaning and purpose. Data collection was accomplished using an instrument developed as part of this study. Analyses include reliability estimation, item analyses, demographic variable mean comparisons, factor analyses, and a variety of Pearson correlational analyses. 127

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CHAPTER 4 RESULTS Introduction The results of this study are presented according to the three phases of the study. Phase 1 was the test development phase. Operational definitions were developed for each of the seven subconstructs hypothesized to comprise the love of learning construct and an item pool was generated for each subconstruct based on the framework of operational definitions. Five subject matter experts participated in a modified Delphi method to rate and provide feedback to each other about each of the 72 items. Their ratings and comments were used to select the 25 items for the initial love of learning survey. Interrater agreement and reliability were examined for the 72-item pool and the resulting 25-item survey for two rounds using three techniques. In phase 2, the survey was administered, the means of several demographic variables were compared, internal consistency reliability was estimated, and the underlying structure of the love of learning instrument was examined through correlational and factor analyses. Phase 3 focused on construct validity evidence. Pearson correlation coefficients were calculated between the love of learning instrument and six scales 128

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hypothesized to correlate with the love oflearning construct either strongly, weakly, or not at all. Correlations were as expected. Correlation coefficients were arranged into a hybrid multi trait-multi method matrix to examine convergent and discriminant validity coefficients. Monotrait-heteromethod, heterotrait-monomethod, and heterotrait-heteromethod correlations formed a matrix suggesting that measurement did not contribute much to correlations among those instruments. Convergent validity coefficients were high and discriminant validity coefficients were low, which is desirable. However, similar coefficients for the Melbourne Curiosity Inventory were also correspondingly high and low, suggesting that the love of learning instrument might be measuring little more than trait curiosity. Phase 1. Instrument Development Guidelines in the Standards for Educational and Psychological Testing (American Educational Research Association (AERA), American Psychological Association (APA), and the National Council on Measurement in Education (NCME), 1999) were followed in developing the love of learning instrument. The first step included extending the original construct into a framework that characterizes the construct being measured. A second step involved developing a table of item specifications. The third step consisted of creating an item pool for each subconstruct. The last step involved using a consensus-seeking participatory approach to select 129

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items from the item pools for the initial love of learning scale. Developing a Framework In the first step, the love of learning construct was extended into a framework that reflected the scope of the construct being measured. Fiske (1966b) suggested that inadequacy in measurement is based on the way a construct has been delineated and "the poor coordination between this description and the measurement operations developed for the construct" (p. 76). To address this inadequacy, a working definition was created as a template for the design of a love of learning measurement. Fiske's idea of a working definition emphasizes the belief that "no conceptualization should be considered to be fixed and immutable; rather, it should be seen as something that should be modified as subsequent theoretical and empirical work may indicate" (p. 77). The working definition for love of learning consists of those facets discovered in the literature review that are frequently associated with love of learning. Operational definitions of these facets or subconstructs proposed to comprise the love of learning construct became the framework of the working definition. Thus, the framework delineated the facets of the love of learning construct. As the review of the literature revealed, the love of learning is usually associated with such other constructs as epistemic curiosity, intrinsic motivation, interest, flow, and the agency of self in terms of competence, personal growth, and 130

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finding meaning and purpose in life. These facets or subconstructs have been defined, studied, and measured to a moderate extent. Thus, it seemed reasonable to assume that these constructs formed a foundational meaning or working definition for the love of learning. Gable and Wolf (1993) advised that operational definitions be developed for each of the sub constructs of the domain being measured. Based on the literature reviews of these subconstructs, the following operational definitions were developed: 1. Epistemic curiosity is information seeking (Spielberger & Starr, 1994; Starr, 1992). It is reflected in the frequency and duration of information seeking behaviors as well as the intensity of the desire (attitude) towards seeking and finding information. 2. Intrinsic motivation is defined as learning for its own sake (Deci, 1975; 1980). It is be operationalized as freely choosing to engage in learning activities, as engaging in learning activities frequently, as engaging in learning activities for long periods of time as well as expressing a positive attitude towards engaging in learning activities for their own sake. 3. Interest in learning implies a relatively enduring preference for and selective persistence in learning over other activities (Prenzel, 1992; Renninger, 1990; Schiefele, 1990; Schiefele, 1992). It is operationalized as preferring to learn about something over another activity as well as selectively persisting in learning. Interest 131

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in learning is further operationalized as expressing attitudes of preference for learning over other activities as well as selectively persisting in learning. 4. Flow consists of feeling that one's skills are appropriate to the challenge at hand, in a goal-oriented, action-system with clear rules and adequate feedback. One becomes so absorbed that no attention is paid to anything else, self-consciousness disappears, and one may lose track of time. The feeling afterward is so gratifying that a person will engage in this activity for its own sake (Csikszentmihalyi, 1990). 5. Self-concept in terms of competence is exercising autonomy and feeling efficacious (Deci, 1975). It is operationally defined as engaging in behaviors and expressing positive attitudes about being self-determined. 6. Self-concept in terms of growth and complexity is seeing oneself as growing, improving, and increasing in complexity (Csikszentmihalyi, 1982; Maslow, 1968/1982). It is operationally defined as the engaging in behaviors that one believes will foster growth and self-improvements as well as expressing attitudes that growth, self-improvement etc., are desirable. 7. Self-concept in terms of meaning and purpose is operationally defined as engaging in activities that help one find meaning or define one's purpose and expressing the attitude that such activities are worthwhile (Crumbaugh & Mahollick, 1981; Suchman, 1971). These definitions were modified for the panel of experts to use in judging the 132

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items for inclusion on the love of learning scale. The following are the operational definitions used in the Delphi method: 1. Curiosity is seeking information frequently and persistently and expressing the desire ( attitude) to seek information. 2. Intrinsic motivation is engaging in learning for its own sake and because it is fun, as well as expressing a positive attitude towards engaging in learning activities for their own sake and because they are fun. 3. Interest is preferring to learn about something over another activity, engaging in learning frequently and for long periods of time, and expressing attitudes of preference for learning over other activities as well as frequently and persistently engaging in learning activities. 4. Flow is experiencing a balance of challenge and skill, merging action and awareness, having clear goals, receiving immediate feedback, concentrating on the task at hand, forgetting about outside distractions, perceiving a sense of control, losing self-consciousness, and losing a sense of time while learning. 5.Self-concept in terms of self-determination is exercising autonomy and feeling competent while learning. 6. Self-concept in terms of growth, increasing complexity, and self improvement is engaging in learning behaviors that one believes will foster growth, increase complexity, and nurture self-improvement as well as expressing attitudes 133

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that growth, increasing complexity, and self-improvement are desirable. 7. Self-concept in terms of finding meaning and purpose is engaging in learning activities that help one find meaning and/or define one's purpose as well as expressing attitudes that such learning activities are worthwhile. These operational definitions provided the initial framework within which items were selected or written for the item pools of each subconstruct, and then judged for inclusion in the initial love of learning instrument. Table of Specifications In accordance with to the Standards for Educational and Psychological Testing (AERA, APA, & NCME, 1999), the next step involved developing a table of test specifications. The following specifications were established: 1. Items need to reflect some aspect of an operational definition of a subconstruct hypothesized to comprise the love of learning. Thus, a level of scale specificity (DeVellis, 1991) is established by the subconstructs. 2. Items need to be worded so that behaviors, attitudes, or beliefs about the construct are assessed. According to Ajzen and Fishbein's (1980) expectancy-value model for scaling, peoples' attitudes, beliefs, and evaluations about a target object may be combined to represent an overall attitude toward that object. 3. Items need to be worded to achieve clarity. DeVellis (1991) stated that 134

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clarity defines most of the characteristics of a good item. To achieve clarity, wording needs to be unambiguous, short, and easy to read. Finally, items need to include a single choice or thought to avoid double barreled wording. 4. Items need to be positively worded. Some disagreement exists regarding whether or not to include negatively worded items (DeVellis , 1991). Negatively worded items typically are written to avoid acquiescence, affirmative, or agreement response biases. However, they are frequently confusing. Thus, to keep the survey easy to understand, items were worded positively. 5. Response format need to be a five-point Likert scale format of Strongly Agree to Strongly Disagree, with a mid-point reflecting neither agree nor disagree. A five-point response format was selected to allow respondents to choose a neutral position. A Likert scale was selected because of its wide and ease of use in assessing behaviors and attitudes (DeVellis, 1991) . Although DeVellis argued for using a variety of response formats in a self-report instrument, the response scale selecting levels of agreement rather than importance, frequency, likelihood, or quality was chosen also because of its wide and simple use. 6. Scoring needs to be standard with Strongly Agree equaling 5 and Strongly Disagree equaling 1. Thus, the higher total raw scores correspond to more of the love of learning trait. These specifications provided guidance in generating and modifying items for the initial item pool for the love of learning instrument. 135

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Generating an Item Pool The next step included generating an item pool for each subconstruct. Some items were modified from existing scales. Some were derived from scholarly writings about a given subconstruct. Some items came from brainstorming sessions in measurement courses. Some items were generated to reflect specific aspects of the subconstructs' operational definitions. Items were chosen and modified or generated to ensure that each component of each operational definition was represented with at least one item, usually several. Items were worded in accordance with Ajzen and Fishbein's (1980) conceptual framework for attitude and behavior consistency. Gable and Wolf (1993) suggested that at least 10 to 12 items be generated for the item pool of each subconstruct and DeVellis (1991) estimated that three or four times the number of items on the final survey be generated. The number of items generated for each subconstruct ranged from 6 to 12 and 72 items comprised the total item pool (see Table 4.1). Appendix E shows the 72 items listed by subconstruct as well as the list of measures, references, and other sources from which items were derived. Selecting Items for the Survey The last step was to use a consensus seeking participatory approach to choose items from the item pools for inclusion in the initial love of learning scale. Five 136

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subject matter experts agreed to participate in a partially face-to-face and partially electronically modified version of the Delphi method. According to Ziglio (1996), the Delphi method originated in the 1950s and 1960s at the RAND Corporation. Helmer (1967) one of the creators of Delphi, described the method as an attempt to make effective use of informed intuitive judgment. He suggested three rules: (a) select experts wisely, (b) establish an optimal environment in which experts may work, and (c) use a careful and systematic process in deriving from expert opinion a consensus position. Seven subject matter experts were invited and five agreed to participate. Of these all have expertise in the areas of adult learning and education as well as motivational theory. Each brought to the task a unique perspective. One panelist has specific experience in faculty development. Another panelist has a background in medical technology. One panelist'S background is in communications and philosophy. One member of the panel has a geology and computer science background. Finally, one member's background was in art history and experiential learning through travel. One member has a Ph.D.; the remaining four were doctoral candidates. The first round was a face-to-face meeting in a classroom. All panelists attended except one who was unable to attend and participated completely by email. All panelists knew each other. Instructions to the panelists were as follows: 137

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1. Read the operational definitions for each of the sub constructs that I have hypothesized comprise the construct love of learning. They include curiosity, intrinsic motivation, interest, flow, self-concept with regard to determination (autonomy, competence), self-concept with regard to improvement (growth, increasing complexity), and self-concept with regard to finding meaning and/or purpose. 2. Read each item designed to measure a specific construct. Determine whether you believe the item fits the operational definition, somewhat fits the operational definition, or does not fit the operational definition. Circle, bold, or italicize your decision. Do this for all items (72). Email your decisions to me, or bring them to our next meeting (two weeks). 3. If you wish to comment on your decision, please do so. A frequency count of the ratings and comments will be compiled for the second round. The second round will be the same as the first except that you will be provided with the information from the first round. You will learn how your fellow subject matter experts have rated each item. 4. Questions? Each panelist was given a packet containing the operational definition for each sub construct, the pool of items selected for each subconstruct, and the rating scale for each item in each pool for each subconstruct. Each panelist was given two weeks for round one in which to rate and 138

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comment on each of the 72 items. The first round of comments and ratings were collected, tallied and compiled, and sent back to panel members by email. The second round was conducted entirely by email. Each panelist was given another two weeks for round two in which to see the ratings and comments from round one as well as rate and comment on each of the 72 items a second time. At the end of the second round, ratings and comments were collected and tallied again. Those items with the strongest consensus and the most ratings of Fits quite well were selected for inclusion in the initial love of learning scale. Some items from each subconstruct fell into these criteria. Specific information used to select final items for the survey included the following: 1. Total number of Does Not Fit, Fits Somewhat, and Fits Quite Well ratings for each item for round one. 2. Total number of Does Not Fit, Fits Somewhat, and Fits Quite Well ratings for each item for round two. 3. Subject matter expert comments for each item for round one. 4. Subject matter expert comments for each item for round two. S. Code indicating which part of the operational definition each item reflected. Items with the most ratings of Fits Quite Well for both rounds were selected first. Of these, three items were so similar in wording and content that one was chosen to represent all three. Second, those items with the most ratings of Fits Quite Well that completed the operational definitions for each subconstruct were selected. 139

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Of these, one item was reworded. Finally, an item about persistence in learning that completed the operational definition of interest was selected although agreement was low. The resulting initial love of learning scale had 25 items distributed rather evenly across the seven subconstructs. Each component of each operational definition was reflected in one or more of the 25 items. Some representativeness in coverage was lost with the flow subconstruct because its operational definition has ten components. Four of ten items were selected. These four included perception of control, ability to concentrate, forgetting outside distractions, and losing track of time. Flow items which were not included consisted of items about having clear goals, immediate feedback, a balance between skills and challenge, merging of action and awareness, loss of self-consciousness, and positive feelings experienced afterwards. These components seemed to be captured by other items. Table 4.1 shows the final number of items selected from each subconstruct. Of the 25 items selected, eight were generated to fit an operational definition in this study, three were generated from writings in areas thought to relate to love of learning, nine were derived or modified from multiple sources, including readings or other instruments, and five were derived or modified from a single instrument. Table 4.2 shows the selected items and their source fonning the initial item pools for each subconstruct. 140

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Table 4 . 1 Number and percentage of items in initial pool and survey for each subconstruct. Subconstruct Items in initial pool 1. Curiosity 6 (8.3%) 2. Intrinsic motivation 10 (13.9%) 3. Interest 12 (16.7%) 4. Flow 12 (16.7%) 5. Self-concept Competence 12 (16.7%) 6. Self-concept Increasing 9 (12.5%) growth, complexity, improvement 7. Self-concept Finding meaning 11 (15.3%) and purpose Total 72 Items selected for the love of learning instrument 3 (12%) 3 (12%) 3 (12%) 4 (16%) 4 (16%) 4 (16%) 4 (16%) 25 The 25 items selected for the survey were extracted from the 72 items and their corresponding operational definitions. They were numbered from 1 to 25. A random number generator computer program was used specifying a 1 to 25 range. 141

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The item's position in the survey was by random assignment rather than its place within the pools for each subconstruct. Table 4.2 Love of learning survey items 1. Learning gives me opportunities to create new meanings in my life. 2. I learn to satisfy a deep curiosity about life and ideas. 3. Learning is my favorite free time activity 4. When I become absorbed in learning, I forget about outside distractions. 5. I usually feel a sense of control of the learning process. 6. I prefer to fill my spare time learning about things. 7. I learn to improve my understanding of life. 8. I enjoy looking at problems from different points of view 9. I like to learn just for the sake of learning. 10. I embrace learning challenges that allow me to achieve excellence. 11. I often use my free time learning about things. 12. I learn because I enjoy becoming more familiar with different things. 13. I very much like to discover new ideas that can be further explored. 14. I usually am persistent when I am learning. 15. Learning gives me a sense of competence. 16. I feel that I am successful as a learner. 17. If there is something I want to learn, I can figure out a way to learn it. 18. I frequently find myself asking questions to get more information. 19. I find learning to be personally meaningful in some way. 20. I like dealing with questions where there is not one right answer. 142

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Table 4 . 2 (Cont.) 21. I can often totally concentrate when I am learning. 22. I learn in order to improve myself. 23. I am usually on the lookout for opportunities in which I can learn something. 24. Learning is fun. 25. I occasionally become so absorbed in learning that I lose track of time. Interrater Reliability Interrater reliability was estimated using three methods for the 72-item pool and for the 25-item survey. The three methods included percentage of agreement, average Pearson's correlation using Fisher's Z transformation, and generalizability theory techniques using repeated measures analysis of variance (Crocker & Algina, 1986; Cronbach, GIeser , & Rajaratnam, 1972; Goodwin, 2001). First, interrater agreement and reliability were estimated for the complete set of 72 items in each round, although round two of the rating process included the results and comments from round one for all subject matter experts. Second, interrater agreement and reliability were estimated for the selected set of 25 items in each round. Interrater agreement and reliability are measures of consistency in judgments provided by two or more raters . They become relevant when judgments are subjective (Goodwin, 2001). Interrater agreement is the extent of a match in ratings assigned by 143

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raters. Interrater reliability is the extent to which raters order items in the same way. Three methods were used to assess interrater agreement and interrater reliability. Each method provides unique information regarding rater consistency, thus, information regarding the items chosen for the initial love of learning survey. First, simple percentages of agreement were calculated. Because there were five raters, 80% agreement was defined as four out of five raters assigning the same rating to an item and 100% agreement was defined as five out of five raters assigning the same rating to an item. This method was applied to both rounds of the Delphi Method, recognizing that raters had the results and comments from round one available in round two. Table 4.3 shows the percentage of agreement among raters determined in this way. A second method of determining interrater reliability is by calculating the average correlation coefficient among all raters and items. The average correlation coefficient is calculated by determining the correlation coefficients between each item and raters, converting these correlations to Fisher's Z transformation, calculating the mean, and finding the equivalent correlation. This was accomplished for each round using Pearson's correlation coefficient. Again reflecting the consensus seeking nature of the Delphi method, the correlation increased from the first to second round. Round one correlation was r = .367 and round two correlation was r = .413. 144

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Table 4.3 Interrater agreement by round for the 72-item pool Percentage of Agreement Combined 80 and 100% Agreement Round one 80% 100% 21172 7172 (29.2%) (9.7%) 28172 (38.9%) Round two 80% 100% 26172 16172 (36.2%) (22.2%) 42172 (58.3%) The third method for determining interrater reliability is based on Generalizability Theory (Cronbach et ai, 1972; Goodwin, 2001). Two repeated measures ANOV As were conducted, one for each round. Most of the variance was accounted for in the interaction or error term (see Table 4.4), meaning that there was a relatively high amount of error variance. As was expected, interrater reliability increased from round one to round two. Unexpected results were the dramatic differences among the three methods. Interrater agreement and reliability using correlations were comparable. The repeated measures 145

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ANOV As revealed that most of the variance in both rounds is contained in the interaction or error term, and little variance is accounted for in the items factor. As was expected, interrater reliability increased from round one to round two. Unexpected results were the dramatic differences among the three methods. Interrater agreement and reliability using correlations were comparable. The repeated measures ANOV As revealed that most of the variance in both rounds is contained in the interaction or error term, and little variance is accounted for in the items factor. Table 4.4 Repeated measures ANOV As for the 72-item pool Round one Round two Source of df Mean Variance % of total df Mean Variance % of total Variance Squares Component Variance Estimates Squares Component Variance Estimates Rater 3 4.365 .0548 Items 71 .577 .0395 Item by Rater 213 .41 .419 10.7% 1 .34 .00059 7.7% 71 .566 . 0915 81.6% 71 .383 .383 146 .125% 19.3% 80.6%

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A second set of interrater agreement and reliability estimates was calculated for each round of ratings using 25 items selected for the love of learning survey. As was expected, interrater agreement and reliability improved over those for all 72 items. Percentages of agreement for each round increased by at least 5% and at most 29% (see Table 4.5) . The average Pearson's correlation coefficients rose to r = .80 and r = .86, respectively. However, the improvement was inconsequential for the repeated measures ANOV As. Indeed, the ANDV As for the 25 items differed little from the ANOV As for the 72 items . In other words, the error or interaction term accounted for the most variance (See Table 4.6). Rater variance was higher for the 25-item repeated measures ANOVAs than for the 72-item repeated measures ANOV As and decreased from round one to round two for both the 25and the 72-item generalizability ANOV As. Item variance was low in round one and increased in round two for both the 72-item and 25-item ANOVAs . Table 4.5 Interrater agreement by round for the 25-item survey Round one Round two Percentage of Agreement 80% 100% 80% 100 147

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Table 4.5 (Cont.) Round one Round two 11/25 4125 16/25 8125 (44%) (16%) (64%) (32%) Combined 80 and 100% 15/25 (60%) 24/25 (96%) Agreement Table 4.6 Repeated measures ANOV As by round for the 25-item survey Round one Round two Source of df Mean Variance % of total df Mean Variance % of total Variance Squares Component Variance Estimates Squares Component Variance Estimates Rater 4 2.168 Item 24 .265 Item by .075 .0064 Rater 96 .296 .296 19.9% 4 .592 .018 1.6% 24 .205 .014 78.5% 96 .134 .134 148 10.8% 8.4% 80.8%

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Phase 2. Reliability and Instrument Structure Study Data Collection Letters were sent to 19 psychology department chairs in 11 universities and state colleges, and 8 community colleges. The letter of contact is provided in Appendix D. Additionally, two emails were sent out, one to a social sciences department chair of an online organization that provides college courses to community colleges and the other to a research coordinator for a military academy. Telephone calls were made to a department of psychology chair at a community college and his research coordinator counterpart. Further, four professors, each from a different institution of higher education were contacted face-to-face. All in all, 26 initial contacts were made. Eleven contacts responded positively, 2 contacts responded negatively, and 13 contacts did not respond. This represents a 42% response rate. Data were collected at the 11 institutions from which favorable responses were received. These included 7 state colleges and universities, 3 community colleges, and 1 online organization that provides college classes via the internet to approximately 15 community colleges and 1 state college. Conditions for survey administration varied from institution to institution . In six institutions, I was allowed to visit specific classes, explain the study, and ask for 149

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voluntary participation. In four institutions, the professors chose to administer the survey by themselves, following the guidelines provided. For the online organization, the survey was made available online with written instructions provided by the course instructors. Conditions specified by the Human Subjects Review Committee(s) were followed, according to the specific institution if required, and in accordance with the University of Colorado at Denver if not otherwise specified. As such, each student was given information about the purpose of the study and advised that his or her responses would be kept anonymous and confidential, and that participation was voluntary (see Appendix D). Incentives for survey completion varied as well. For classes at three institutions, completion of the survey satisfied a course requirement. For classes at two institutions, extra credit was awarded for completing the survey. For the remainder, no incentives were provided. All students who wished to complete the survey were encouraged to do so, although only students in the 18 to 25 year old range were included in the calculation of reliability and item analyses. Participants A total sample of 447 participants (18to 25-years old) participated in this phase of the study. Participants included 306 (68.5%) women and 141 (31.5%) men. All except one claimed to have at least completed high school (see Table 4.7). About 150

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89% (397) participants were single, 10% (44) were married, and 1 % (6) were separated or divorced. Sixty-one completed the survey via the internet, 90 completed the survey at a community college, and 296 completed the survey at a state college or university. Table 4.7 Education level Less than high school High school Attended some college Associates degree Bachelor's degree Post college graduate 1 (.2%) 46 (10.3%) 330 (73.8%) 50 (11.2%) 10 (2.2%) 10 (2.2%) Results Means and Mean Comparisons The mean score on the love of learning instrument for this age group was 96.8 and the standard deviation was 12.2. A series of mean comparisons were conducted using the demographic data and the love of learning scores. There was no significant 151

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difference between the two gender means. There were significant differences among the means for marital status, educational level, and whether the survey was completed online or face-to-face. Table 4.8 shows the results. Table 4.8 Mean comparisons for demographic variables N Mean Fort Significance Gender t = .729 .467 Female 306 97.05 Male 141 96.14 Marital Status F= 3.269 .039 Single 397 96.34 Married 44 101.09 Separated or divorced 6 93.33 Educational Level F=2.5 . 043 High School 46 94.22 Some College 330 96.39 Associate's Degree 50 99.86 Bachelor's Degree 10 98.50 Post College 10 104.60 Schools t = -4.365 . 0001 Online 62 102.95 Classroom 384 95.79 152

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Levene's test for violation of the assumption of homogeneity of variances was conducted for all comparisons because group sizes were unequal. In each case, the result was not significant. Tukey ' s HSD multiple comparison post hoc test using a harmonic mean for unequal n's for educational level showed that no single pair of educational levels had a statistically significant difference between means (see Table 4.9). However, Tukey's HSD mUltiple comparison post hoc test using a harmonic mean for unequal n's for marital status showed that a significant difference existed between married and single groups (see Table 4.10). Table 4.9 Tukey HSD multiple comparison post hoc test for educational level Education Mean difference Significance High School Some College 2.17 .788 High School Associate's Degree 5.64 .152 High School Bachelor's Degree 4.28 .851 High School Post College Graduate 10.38 . 103 Some College Associate's Degree 3.47 . 326 Some College Bachelor's Degree 2.11 .983 Some College Post College Graduate 8.21 .218 153

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Table 4.9 (Cont.) Education Mean difference Associate's Degree Bachelor's Degree 1.36 Associate's Degree Post College Graduate 4.74 Bachelor's Degree Post College Graduate 6.10 Significance .998 .793 .795 It was expected that there would be no significant gender differences. Marital status produced a significant difference with married students having higher love of learning scores than single students. Such a difference was anticipated, although not a significant difference. The literature suggests that there is a positive association between various happiness and well-being measures and marital status (Meyers, Table 4.10 Tukey HSD multiple comparison post hoc test for marital status Marital status Single -Married' Single Separated or divorced Married Separated or divorced *p> .05 Mean difference 4.76 3.00 7.76 154 Significance .038* .820 .309

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1992). This love of learning measure contains a definite positive affective tone. On the other hand, a more dramatic difference among educational levels was expected. The overall between groups for educational level was significant, but not any single paired comparison. One can see a gradual increase in love of learning mean scores as amount of education increases, except between Associate's and Bachelor's Degree, but apparently these increases are not statistically significant. Finally, not completely unexpectedly, there was a significant difference between face-to-face and online respondents. Online students have higher love of learning scores, perhaps because they need to be self-directed, motivated, and autonomous in order to succeed in the online learning environment. Reliability and Item Analyses Reliability and item analyses for inter-item consistency were estimated for the love of learning instrument. Inter-item consistency was estimated using Cronbach's (Cronback, 1951) alpha (a = .92). Item analysis consisted of examining alpha reliability of the instrument if an item was deleted. Most were lower than the reliability of the complete instrument (reference Table 4.11). 155

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Table 4.11 Reliability analysis Scale (alpha) Item-total statistics Scale mean Scale variance Corrected Squared Alpha if if item if item item-total multiple item deleted deleted deleted correlation correlation correlation 1 92.4092 142.7907 .5284 .3797 .9204 2 92.6759 141.0721 .5716 .4360 .9196 3 93.7402 136.3955 .6464 .5606 . 9181 4 93.2092 138.6589 .4977 .3872 . 9211 5 93.1494 141.3348 .4771 .3594 . 9211 6 93.6161 136.4675 .6419 .5908 . 9182 7 92.6782 141.9515 .5224 .4274 .9204 8 92.6023 141.5350 .5234 .4043 . 9203 9 93.1586 137.3365 .6432 .4894 .9182 10 92.8207 139.7788 .5941 .4024 .9192 11 93.5793 136.5715 .6297 .6028 .9184 12 92.7218 142 . 6713 .5425 .4060 .9202 13 92.8184 139.9001 .6038 .4511 .9191 14 93.0322 140.7916 .5161 .3992 .9204 15 93.3264 138.3033 .5010 .4300 .9212 16 92.7862 141.5510 .5305 .4486 . 9202 17 92.6943 142.9547 .4934 .3569 .9208 156

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Table 4.11 (cont.) Scale mean Scale variance Corrected Squared Alpha if if item if item item-total multiple item deleted deleted deleted correlation correlation correlation 18 92.8690 138.6026 .5486 .3769 .9200 19 92.6138 140.2791 .6653 .5521 .9185 20 93.2782 142.0722 .3181 .1990 .9253 21 93.5379 139.1385 .4792 .3785 .9215 22 92.5977 141.0843 .5861 .4901 .9195 23 93.1287 138.5640 .6325 .4622 .9185 24 92.8897 139.8357 .6399 .4769 .9186 25 92.5356 141.4705 .5872 .4780 .9195 Hotelling's T -Squared = 1740.9581 F= 68.6956 Prob. = .0000 Degrees of Freedom: Numerator = 24 Denominator = 411 Reliability Coefficients alpha = .9229 Standardized item alpha = .9270 Factor Analysis An exploratory factor analysis was conducted using the love of learning instrument to examine the underlying structure. A principal components factor 157

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analysis extracted one factor with an eigenvalue of greater than 9, and three factors with eigenvalues greater than one. A scree plot showed a dramatic drop with leveling at four factors (Figure 4.1). The four-factor model accounted for 53% of the variance. An oblique rotation factor analysis was conducted specifying four factors. All items loaded at .487 or greater. Figure 4.1 Scree Plot Q) ::J C Q) 0) 8 6 4 2 Scree Plot i.iJ ____ ____ ____ ____ ____ ____ 3 5 7 9 11 13 15 17 19 21 23 25 Component Number 158

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The key assumption to test when using factor analysis is sphericity. Sphericity assumes that the variances of the differences for all pairs of correlations are the same. The Bartlett Test of sphericity examines the presence of correlations among variables. It is desirable for the variables to be somewhat correlated with one another. The Bartlett test for the love ofleaming instrument was significant (see Table 4.10). Another test to assess the adequacy of the data set for using factor analysis is the measure of sampling adequacy (MSA). The index range is from 0 to 1, where 1 means that each variable is perfectly predicted by the other variables. Indices below .50 are unacceptable. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO MSA) tests for both questionnaires were above .935, which is acceptable (see Table 4.12). Table 4.12 Tests for violations of the sphericity assumptions KMO Measure of Sampling Adequacy Bartlett's Test of Sphericity .935 p < .0001 Using an oblique rotation and a .4 loading as a rule of thumb, 17 items loaded highly on more than one factor. However, for all but 3 items the strongest loading was at 159

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least one tenth and usually greater than one tenth larger than the second strongest loading. Thus, 14 items were selected to the factor for which they had the highest loading. Items 4, 10, and 13 showed smaller differences between factor loadings greater than .4. Each of these items was examined in terms of fit with the high loading factors. In each case, the item seemed to fit best with its highest factor. Rather than include these items on more than one factor, it was decided to keep them in the factor where they loaded most highly. Thus, no one item is included on more than one factor. These results seem to reflect the overlapping nature of the subconstructs used to define love of learning. Nonetheless, with the distinctions made, the factors were labeled as follows: Factor 1 is self-improvement, factor 2 is successful challenges, factor 3 is enjoyment of learning, and factor 4 is complexity in learning. Table 4.13 shows the items and loadings for each factor. Factor 1 labeled self-improvement contains eight items. Items were originally generated to reflect operational definitions for self-concept in terms of meaning, growth, and competence. Items tend to reflect the essence of learning for the purpose of improving oneself. Factor 2 labeled successful challenges contains six items. These items were generated to reflect the operational definitions of flow, self-concept in terms of competence, and interest. This factor has items that reflect successful experiences with learning. 160

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Table 4.13 Factors and loadings comprising the love of learning instrument Factor % Variance Loading Factor 1 Self-improvement 36.90 1. Learning gives me opportunities to create new meanings in my life. 2. 7. 12. I learn to satisfy a deep curiosity about life and ideas. I learn to improve my understanding of life. I learn because I enjoy becoming more familiar with different things. 18. I frequently find myself asking questions to get more information. 19. 22. 25. I find learning to be personally meaningful in some way. I learn in order to improve myself. Learning gives me a sense of competence. Factor 2 Successful challenges 6.32 5. I usually feel a sense of control of the learning process. 10. I embrace learning challenges that allow me to achieve excellence. 14. I usually am persistent when I am learning. 16. I feel that I am successful as a learner. 161 .691 .645 .729 .633 .516 .768 .735 .721 .654 .510 .725 .778

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Table 4.13 (cont.) Factor % Variance Loading 17. If there is something I want to learn, I can figure out a way to learn it. 21. I can often totally concentrate when I am learning. Factor 3 Enjoyment of learning 3 . 4. 6. 9 . 13. 15. Learning is my favorite free time activity . When I become absorbed in learning, I forget about outside distractions. I prefer to fill my spare time learning about things. I like to learn just for the sake of learning. I very much like to discover new ideas that can be further explored. I occasionally become so absorbed in learning that I lose track of time. 23 . I am usually on the lookout for opportunities 24. in which I can learn something. Learning is fun. Factor 4 Complexity in learning 5.48 4.29 .634 .677 -.817 -.487 -.811 -.658 -.572 -.594 -.634 -.630 8. I enjoy looking at problems from different points of view. .651 20. I like dealing with questions where there is not one right answer. .683 162

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Factor 3 is labeled enjoyment of learning and contains eight items. Actually, all items loaded negatively on this factor suggesting rather the opposite of enjoyment! Nonetheless, as a group they reflect an affective tone. These items were originally generated to reflect the operational definitions of interest, flow, intrinsic motivation, and curiosity. This factor captures learning for fun, learning for the sake of learning, absorption in the learning process, and seeking opportunities to learn. Factor 4 is complexity in learning and contains only two items. Both items were generated to reflect the operational definition of self-concept in terms of growth and complexity. This factor reflects the uncertainty and multiple perspective taking involved in learning about complex phenomena. These factors reflected a clustering of items that seemed reasonable in light of the working definition of the love of learning construct. Correlational analyses. The items selected for each sub construct were grouped together and a variable was created. Pearson correlation coefficients among the love of learning construct and subconstructs hypothesized to comprise love of learning were estimated (See Table 4.14). Correlations among the love of learning construct and its subconstructs were positive, high, and significant suggesting strong conceptual overlaps among the subconstructs hypothesized to comprise love of learning. 163

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Table 4.14 Correlations among love of learning construct and subconstructs LOL Curiosity InMot Interest Flow Comp Grow Purp LOL 1.000 Curiosity .814** InMot .768** .601** Interest .837** .639** .636** Flow .765** .509** .529** .595** Comp .813** .620** .562** .611 ** .598** Grow .756** .607** .533** .523** .428** .570** Purp .787** .632** .571** .572** .463** .567** .612** 1.00 Table 4.14 (cont.) **p < .01 LOL = love of learning, InMot = Intrinsic Motivation, Comp = Self-concept in terms of competence, Grow = Self-concept in terms of growth, and Purp = Self-concept in terms of meaning and purpose Results of phase 2 suggest that the love of learning instrument is reliable and that the 25 items selected to comprise the instrument were adequate. Mean comparisons among demographic variables were acceptable although the significant differences are somewhat problematic. Pearson's correlations among the love of 164

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learning construct and subconstructs hypothesized to comprise love of learning were strong, positive, and significant suggesting a great degree of conceptual overlap. Finally, an exploratory factor analysis was conducted to "determine whether item responses "cluster" together in patterns predictable or reasonable in light of the" theoretical structure of the love of learning construct (Crocker & Algina, 1986, p. 232). Patterns seemed reasonable. Phase 3. Construct Validity The third phase of the study was conducted to examine evidence of construct validity of the love of learning instrument. Crocker & Algina, (1986) stated that construct validation consists of compiling multiple layers of evidence. They specify four approaches. The first two approaches were accomplished in phase 2 as part of the examination of the internal structure of the love of learning instrument: the simple examination of the mean differences between various demographic groups, and an exploratory factor analysis to "determine whether item responses cluster together in patterns predictable or reasonable in light of the" theoretical structure of the love of learning construct (p . 232) . The third and fourth approaches were undertaken in this phase to further study the construct validity of the love of learning instrument. The third approach involved conducting a set of correlational analyses between the love of 165

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learning instrument and other scales measuring related constructs. The fourth approach involved examining a subset of the above correlational analyses according to Campbell and Fiske (1959) multitrait-multimethod matrix. Campbell and Fiske believed that the kind of measure could influence the validity of the measure. Examining similar constructs with contrasting measures and different constructs using similar measures provides insight regarding the effect of the type of measurement. From the two approaches conducted in phase 2 and the two approaches conducted as part of phase 3, evidence was accumulated to support construct validity . Data Collection Data collection for the love of learning survey was described in Phase 2. To examine construct validity, data collection was extended as follows. While maintaining each instrument's structure, six scales were combined on one form to simplify administration. Scales were organized with those measures expected to positively correlate with the love of learning construct preceding those measures expected to negatively correlate with the love of learning construct. Differences between the scales were pointed out (i.e., true-false versus 4-point Likert scale versus forced choice). Packets including the scales were distributed to volunteers either at the beginning or end of the class session. In five of the six institutions, each packet 166

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included a self-addressed stamped envelope. Volunteers were asked to complete the entire battery and mail their responses to me. In a sixth institution, the validation battery was completed in a classroom setting scheduled by me, and on the students' own time. Students signed up to participate. A total of 215 validation packets were distributed across about 15 classes within six institutions. Of those, 192 were returned for a response rate of 89%. Pariicipants A subset of students who participated in the reliability portion of this study was invited to participate in the validation process as well. This subset was comprised of students from the six institutions where I was allowed to visit specific classes. The validation study was explained to the students and participation was requested. Conditions specified by the Human Subjects Review Committee were followed, according to the specific institution if required, and in accordance with the University of Colorado at Denver. As such, each student was given a letter explaining the purpose of the study and providing assurance that his or her responses would be kept anonymous and confidential. Additionally, the letter emphasized that participation was voluntary (see Appendix D). Incentives for this portion of the study were provided but varied by institution. For classes at three institutions, completion of the validation battery of scales satisfied 167

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a course requirement. For classes at two institutions extra credit was awarded for completing this battery of scales. Students at four of the institutions were offered an extra incentive for participating in this phase of the study. The incentive was the chance to win two $25 gift certificates: one for the student and the other for his or her professor. This was accomplished by numbering surveys in a manner such that an instructor could find the student who had won. All students who wished to complete the survey were encouraged to do so, although only students in the 18to 25-year old range were included in the validation study. Of the 192 returned validation packets, 157 packets were sent from students in the 18 to 25-year old range. Participants included 106 (67.5%) women and 51 (32.5%) men. Most participants were single (146 or 93%), although 10 (6.4% were married, and 1 (.6%) was separated or divorced. All except one claimed to have at least completed high school (see Table 4.15). Fifty-four completed the survey at a community college and 103 completed the survey at a state college or university. One survey was discarded because it was incomplete. 168

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Table 4.15 Education level Less than high school High school Attended some college Associates degree Bachelor's degree Post college graduate 1 (.6%) 20 (12.7%) 127 (80.9%) 6 (3.8%) 2 (1.3%) 1 (.6%) Results Means, Standard Deviations, and Reliabilities Means, standard deviations, and internal consistency reliabilities were calculated for each instrument used (see Table 4.16). Correlational Analyses To explore the relationships between love of learning and constructs thought to relate strongly, weakly or not at all, a set of Pearson's correlations was conducted. Each correlational analysis provides a different perspective on the relationship 169

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between love of learning and other relevant constructs (see Table 4.17). All of the correlations were in the direction expected. All were significant except the correlation between love of learning and flexible thinking. Table 4.16 Means, standard deviations, and reliabilities of validation scales N Mean SD Cronbach's Number alpha of items Love of learning 447 96.76 12.23 .9270 25 Curiosity 156 59.95 8.71 .8997 20 Intrinsic enjoyment 156 5.65 1.82 .6049 9 Boredom 156 8.79 4.41 .7605 28 Test anxiety 156 19.87 8.31 .8788 5 Self actualization 156 44.06 5.42 .6390 15 Flexible thinking 156 45.4 5.14 .4953 10 170

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Table 4.17 Correlations among the scales and instruments used for construct validation LOL LOL Positive Models MCI .747** IES .339** Negative Models BP -.202* TA -.209** Borderline SISA .172* Contrary FT .132 *p<.05 **p<.Ol MCI .337** -.221 ** -.283** .255** .099 IES BP TA SISA -.214** -.172* .272 ** .221 ** -.347** -.437** .142 -.037 -.193* .223** LOL = Love ofleaming survey, MCI = Melbourne's Curiosity Inventory, IES = Intrinsic Enjoyment Scale, BP = Boredom Proneness Scale, T A = Test Anxiety Scale, SISA = Short Index of Self-Actualization, FT = Flexible Thinking Scale 171 FT

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M ultitrait-multimethod Campbell and Fiske (1959) developed the multitrait-multimethod technique to check the influence of measurement method on validity. The idea is to select two or more constructs to measure using two or more different methods. All of the scales selected were expected to correlate with the love of learning construct either strongly, weakly, or not at all, however, each is considered qualitatively different. Thus, one single construct was not assessed using more than one measure. As well, methods of measurement were not very distinct. All Were paper-and-pencil self-report survey scales. Test anxiety was assessed using a 7-point Likert scale of Very True of Me to Not Very True of Me. Both the Short Index of Self-Actualization and the Flexible Thinking Scale were assessed using a 6-point Likert scale of Strongly Agree to Strongly Disagree. On the other hand, the Melbourne Curiosity Inventory for trait curiosity used a 4-point frequency response format (Almost Always to Almost Never) and the Boredom Proneness scale both used a true-false format. Additionally, the Intrinsic Enjoyment Scale used a forced-choice format. Thus, slightly different measures were used for several constructs. This coupled with the fact that several constructs were assessed using similar methods suggests that the correlations among the measures can be looked at from a multitrait-multimethod perspective to a certain extent. Correlations were organized into two groups: similar methods and different 172

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methods. Four correlations comprised the similar method group and three correlations comprised the different method group (See Table 4.18). Reliabilities appear in parentheses along the primary diagonal. Note that the Flexible Thinking Scale (FT) reliability is rather weak, the Short Index for Self-Actualization (SISA) and the Instrinsic Enjoyment Scale (IES) are modest, and the Love of Learning Survey (LOL), Melbourne Curiosity Inventory (MCI), Text Anxiety Scale (TA), and Boredom Proneness Scale (BP) are strong. The weak and modest reliabilities may create some attenuation in the validity coefficients. Table 4 .18 Variation of the multitrait-multimethod matrix Similar Method Different Method LOL TA SISA FT MCI IES BP Similar Method LOL (.9270) TA -.209 (8788) SISA .172 -.437 (.6390) FT .132 -.193 .223 (.4953) 173

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Table 4.18 (cont.) Different Method MCI .747 -.283 .255 .099 (.8997) IES .339 -.172 .221 .142 .337 (.6049) BP -.202 .272 -.347 -.037 -.221 -.214 LOL = Love of learning survey, MCI = Melbourne's Curiosity Inventory, IES = Intrinsic Enjoyment Scale, BP = Boredom Proneness Scale, TA = Test Anxiety Scale, SISA = Short Index of Self-Actualization, Ff = Flexible Thinking Scale (.7605) Convergent validity is assessed with similar constructs using different methods. In a typical multitrait-multimethod study, convergent validity coefficients appear along the secondary diagonals of the correlational matrix. However, because the variables used to examine validity were not selected to fit a 3-by-3 matrix of three constructs and three methods, convergent validity coefficients are unusually located in the matrix. They are underlined. All are positive, significant, and higher than the one similar trait, similar method correlation between the Love of Learning Survey and the Short Index of Self-Actualization (.172). Some attenuation may have occurred because the SISA and IES reliabilities are modest. The discriminant validity coefficients are correlations between measures of different constructs using similar methods (heterotrait-monomethod coefficients) and 174

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correlations between different constructs using different methods (heterotrait heteromethod coefficients). Focusing particularly on correlations with the love of learning instrument, both the heterotrait-monomethod coefficients (LOL with Ff and TA) and heterotrait-heteromethod coefficient (LOL with BP) are lower than the reliabilities and convergent validity coefficients. This is desirable. However, as previously mentioned, the correlation coefficient of LOL and Ff is particularly of concern because the reliability of the Ff scale is weak. Noticeably, correlations between the Mel and other measures nearly paralleled those of LOL and those same measures. Some correlation coefficients were stronger and other correlations were weaker. However, the concern that the love of learning instrument may be measuring trait curiosity emerges from the findings. This will be addressed in the next chapter. Summary During Phase 1, a framework of operational definitions was developed, test specifications were identified, and an item pool was generated. To select items for the initial love of learning survey, five subject matter experts participated in a modified Delphi method of consensus seeking to rate and provide feedback to each other about the items. Interrater agreement and reliability were examined for the 72-item pool and the resulting 25-item survey for two rounds using three techniques. Whereas 175

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percentage of agreement and average correlations were parallel and high, repeated measures ANOV As revealed small variances for items, and large variances for the rater-by-item interaction (error term). In phase 2, demographic means were compared, reliability was estimated, and the underlying structure of the love of learning instrument was examined through correlational and factor analyses. Mean comparisons revealed that differences by gender were not significant. However, married students scored significantly higher than single students and online studentS Scored significantly higher than face-to-face students. Although amount of education showed a significant difference among means overall, no one paired comparison was significant. Reliability was calculated using Cronbach's alpha. The result was .92. Item analysis also showed good consistency. Correlations among the love of learning construct and its subconstructs were strong, positive, and significant. Factor analysis revealed four factors accounting for a total of 53% of the variance. Factors seemed to reflect the theoretical understanding of the love of learning construct. Phase 3 focused on construct validity evidence. Pearson correlation coefficients were calculated between the love of learning instrument and six scales believed to correlate with the love of learning construct either strongly, weakly, or not at all. Finally, correlation coefficients were arranged into a hybrid multitrait multimethod matrix to examine convergent and discriminant validity coefficients. Convergent validity coefficients were high and discriminant validity coefficients were 176

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low. Of concern is that similar coefficients for the Melbourne Curiosity Inventory were also correspondingly high and low. The implications of this finding are presented in the next chapter. 177

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CHAPTER 5 DISCUSSIONS AND CONCLUSIONS Generally, the literature review, results of the survey administration, and analysis of the measurement's psychometric properties suggest that the love of learning as a theoretical construct exists and varies among young adults. Although several problems emerged and the study had several methodological weaknesses, most evidence supports the argument that the instrument developed as part of this study measures the love of learning construct. In this chapter, findings, problems, and weaknesses will be summarized and interpreted according to the research questions. Limitations of the study will be addressed. Connections to theoretical foundations will be drawn. Implications for practice and directions for future research will be provided. 178

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Summaries and Interpretations Question 1. What subconstructs comprise the overall construct of love of learning within the young adult (18 to 25 years) age group? Initially, literature searches revealed very little in the way of defining the love of learning construct. Extending the search to keywords used in context with love of learning uncovered a myriad of interrelated constructs. Those constructs which emerged most frequently in context with love of learning were included as part of a working definition of love of learning. Subconstructs included curiosity, intrinsic motivation, flow, interest, and self-concept in terms of competence, growth, and finding meaning. Extensive review seemed to confirm that these constructs most likely comprise love of learning. Operational definitions were developed for each subconstruct and a pool of items reflecting each operational definition was generated. A panel of experts convened face-to-face and online to rate each item according to how well it fit with the operational definition of the construct. With one exception, items with the greatest frequency of Fits quite well became the initial love of learning instrument. Interrater reliability was estimated using several methods. Generally, interrater agreement and reliability were adequate for two of the three techniques used. 179

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Combined interrater agreement was 38.9% in round one and 58.3% in round two for the 72-item pool and 60% in round one and 96% in round two for the 25-item survey. These percentages reflect sufficient agreement among the five raters. The average correlation coefficient showed r = .367 in round one and r = .413 in round two for the 72-item pool and r = .80 in round one and r = . 86 in round two for the 25-item survey. These correlations also reflect adequacy of interrater reliability. However, results of the repeated measures analyses of variance method showed that rater and error variance were greater than item variance for both the 72-item pool and the 25item survey. Since item variance supports interrater reliability, the repeated measures ANOVAs revealed a lack of consistency. The lack of item variance may be attributable to several causes. First, the panel of experts may have varied considerably because each had limited expertise in the broad range of literature from which the love-of-Iearning operational definitions were drawn. Most had some experience in a few of the areas, such as intrinsic motivation, but none were experienced in all research areas . However, this may have been true for any panel of experts gathered for this particular task. Thus, rater and error variances may have occurred because the panel members had limited expertise or, more generally, love of learning as an area of research is in its infancy. Second, in reflecting the constructs they defined, the operational definitions were overlapping in conceptual meaning. Overlapping conceptual content may also account for rater and 180

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error variances exceeding item variances. In summary, because the repeated measures ANOV A showed relatively larger rater and error variances than item variances, further examination of the instrument seems warranted. Research might consist of a replication study using the 72-items pool and a different group of experts. Additionally, a study of a sorting task using the items and subconstructs might provide useful insights. Internal consistency using Cronbach's alpha was high. Item analysis showed that the each item contributed to the high internal consistency reliability. Thus, there is evidence to support the internal consistency reliability of the love of learning instrument. The factor analysis showed a single factor with an eigenvalue of 9.22 and the scree plot (see Figure 4.1) showed a dramatic drop after the first factor. However, the single factor solution accounted for 36.9% of the variance whereas the four factor solution, in which each factor had an eigenvalue of greater than 1, accounted for 53% of the variance. The four factors reflected coherent groupings and were named self improvement, successful challenges, enjoyment of learning, complexity in learning. Implicit in the way items grouped together into these four factors is the overlapping nature of the sub constructs originally hypothesized to comprise love of learning. The initial conceptual framework (see Figure 1.1) defined the love oflearning construct in terms of three areas: three objective areas of psychological research 181

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(curiosity, intrinsic motivation, and interest), the subjective experience of flow, and self-concept in terms of competence, self-improvement, and finding meaning. All seven sub constructs were grouped into these three areas. However, the factor analysis suggested a four-factor solution, which reflected the overlapping nature of the seven subconstructs. Figure 5.1 shows the four-factor structure and illustrates how the response data characterize the love of learning construct. None of seven subconstructs uniquely re-emerged in factor analysis, although more research using a confirmatory factor analysis could be conducted to study this in more depth. However, the patterns that emerged suggest two possibilities. First, perhaps these factors are meta-themes showing specifically how the areas of research overlap. For example, successful challenges are part of the competence, intrinsic motivation, and flow research. This factor connects those three areas of research, i.e., those three subconstructs. Another interpretation of the four-factor solution shows that the three areas defining the self concept circle of the initial conceptual framework are reiterated as three of the four factors. Successful challenges is equivalent to self-concept in terms of competence. Self-improvement is equivalent to self-concept in terms of finding meaning and purpose and self-concept in terms of self-improvement. Finally, complexity in learning captures the remainder of self-concept in terms of growth and self improvement. The fourth factor is enjoyment of learning, which would in effect encompass intrinsic motivation, interest, and flow. Items did not map to factors this 182

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clearly; nonetheless, the conceptual framework defining the love of learning has changed. The revised conceptual framework to define love of learning has four factors as shown in Figure 5.1. Notably, complexity in learning has two items and is smaller than the other factors. Research to address this new framework might determine if complexity in learning should be included in the definition of love of learning, to illuminate the relationship among these newly formed components of the love of learning construct, and to further explain the conceptual underpinnings of love of learning. Correlations between love of learning and each subconstruct were significant statistically (a = .05) and positive, ranging from .76 to .84. These correlations were all higher than the correlations among the various subconstructs themselves. This finding suggests that the subconstructs do comprise a love of learning construct. Based on the literature review as well as the reliability, factor analysis, and correlational analyses of the love of learning instrument, the subconstructs initially hypothesized to comprise love of learning -curiosity, intrinsic motivation, flow, interest, and self-concept in terms of competence, growth, and meaning very likely do comprise love of learning. Could the love of learning construct be comprised of more than the initially identified subconstructs? Yes. Perhaps further research will reveal other subconstructs that will increase the variance accounted for in this instrument (53%). However, the strong correlations between the present 183

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Figure 5.1 Revised conceptual framework defining the love of learning /,----. . ./ -...., .. , / Complexity "\ __ inLeamillg ,1 Self.ifill)rovement Enjoyment of Leaming Successful Challenges '} subconstructs and the love of learning score, and the overlapping nature of these subconstructs with each other, suggest that additional subconstructs may, in fact, not add a new dimension to the definition. As Skinner and colleagues' (1999) summary showed, one problem with scholarly work for the purpose of conceptualization is that 184

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many terms may be used to describe one concept or parts of it. To bring together the disparate perspectives in a coherent manner requires the creation of some boundary. The boundary drawn for the love of learning construct seems adequate at this point. Additionally, the new conceptual framework provides a new perspective for investigating the love of learning construct. Question 2. What are the relationships among the subconstructs of the love of learning construct within the young adult (18 to 25 years) age group? The correlations among the subconstructs hypothesized to comprise love of learning were positive and strong. The set of correlations among the subconstructs were all statistically significant and ranged in size from .43 to .64. All correlations among subconstructs were lower than the correlation between each subconstruct and the overall love of learning scores. These correlations show the overlapping nature in conceptual meaning and the operational definitions of the subconstructs hypothesized to comprise the love of learning. From one perspective this is desirable. The literature showed a great deal of conceptual overlap among the constructs (Ainley, 1986; Ainley, 1987; Bergin, 1999; Beswick, 1974; Csikszentmihalyi, 1988a; Day, Berlyne, & Hunt, 1971; Deci, 1975; 185

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Deci, 1980; Deci, 1998; Deci & Ryan, 1985; Hamilton, Haier, and Buchsman, 1984; Malone & Lepper, 1987).) In this study, the correlation between scores on the Melbourne Curiosity Inventory (MCI) and scores on the Intrinsic Enjoyment Scale (IES) was .337, which further supports conceptual overlap between curiosity and intrinsic motivation. Occasionally, scholars distinguish among various subconstructs (Hidi, 1990; Hidi & Anderson,1992; Hidi & Harackiewicz, 2000; Rheinberg, 1998), pointing out how they differ. Thus, although occasionally scholars have pointed out specific differences among the subconstructs, more frequently they have drawn conceptual connections among these subconstructs. From another perspective, are there other reasons the correlations among sub constructs are so positive, strong, and significant? One explanation is that the love of learning items are not measuring subconstructs distinctively. Nonetheless, the operational definitions were written in accordance with the accepted definitions for each subconstruct in the literature. Similarly, items were generated to embody those definitions and were rated according to how well they actually fit. Because conceptual overlap among subconstructs appears in the literature, the operational definitions and items reflected conceptual overlap as well. Thus, the strong positive correlations among subconstructs demonstrated the conceptual overlap and supported the hypothesis that the love of learning construct exists and is comprised of these subconstructs. This problem seems to be small unless future research shows 186

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conceptual overlap among the various sub constructs is not as strong as the correlations within the love of learning measure suggest. A second probable explanation for the strong, positive, and significant correlational overlap among subconstructs is that participants used a positive bias when responding to the love of learning instrument. The range of possible scores for the love of learning survey is 25 to 125, and the mean in this study is 96. This implies that many participants were using the upper end of the response scale. However, the scores were normally distributed approxiinately and the standard deviation was 12. Thus, the general structure of the love of learning disposition based on responses to the love of learning instrument seems normal. Nonetheless, response set represents a potential weakness of this study, and therefore, the overlapping nature among the subconstructs hypothesized to comprise the love of learning bears further investigation. Question 3. What are the relationships between the love of learning construct and constructs that should have strong correlations with the love of learning construct within the young adult (18 to 25 years) age group? Specijically, for positive model validity (Krathwohl, 1993): (a) What is the convergent relationship (Campbell & 187

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Fiske, 1959) between scores on the love o/learning measure and scores on a curiosity measure? (b) What is the convergent relationship (Campbell & Fiske, 1959) between scores on the love 0/ learning and scores on an intrinsic enjoyment measure? Both the correlation between the love of learning measure and the Melbourne Curiosity Instrument (MCI) (.747) and the correlation between the love of learning measure and the Intrinsic Enjoyment Scale (IES) (.339) were positive and significant. These results imply that strong conceptual overlaps exist between love of learning and curiosity and love and learning and intrinsic enjoyment. Because curiosity and intrinsic motivation were hypothesized to comprise love of learning, strong positive correlations were anticipated. The correlation between the MCI and love of learning measure was stronger than the correlation between the IES and the love of learning measure. This difference may be attributable to two causes. First , curiosity may be a stronger defining subconstruct for the love of learning. For instance, MCI items are worded to create a learning opportunity out of many every day situations. IES items encompass enjoyment across a broad spectrum of activities, including work, and contrast extrinsic vs. intrinsic motivations. Thus, the IES seems to capture a broader scope of day-to-day activities. Second, the response format of the MCI instrument is more similar to the response format of the love of learning survey than is the IES response format. The 188

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Mel has a 4-point response of frequency (Almost Always, Often, Sometimes, Almost Never). The love of learning instrument has a 5-point response format of agreement (Strongly Agree, Somewhat Agree, Neutral, Somewhat Disagree, and Strongly Disagree). The IES has a forced-choice response format. This represents a potential weakness in measurement. Further research is recommended to explore the relationship between love of learning and curiosity and love and learning and intrinsic motivation. In spite of the qualifications, the findings provide evidence for construct validity. Specifically, for negative model validity (Krathwohl, 1993), (a) What is the discriminant relationship (Campbell & Fiske, 1959) between scores on the love of learning measure and scores on an anxiety measure? (b) What is the discriminant relationship (Campbell & Fiske, 1959) between scores on the love of learning measure and scores on a boredom measure? The statistically significant negative correlations with constructs hypothesized to correlate negatively with love of learning represent a second area of evidence for construct validity. The negative and significant correlations with the Boredom Proneness Scale (-.202) and Test Anxiety Scale (-.209) suggest that love of learning does not include and is opposite to feeling either bored or anxious. The negative relationship with the Boredom Proneness Scale suggests that the more a person is boredom prone, the less he or she is likely to love 189

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learning. Likewise, the negative correlation with the Test Anxiety Scale suggests that the more anxious a person is, particularly about taking tests, the less he or she is likely to love learning. These findings are in keeping with the literature regarding curiosity, intrinsic motivation, and flow being connected to a physiological optimal state of arousal. Boredom occurs when the individual is not aroused enough, and anxiety occurs when the individual is overly aroused. Neither one is associated with love of learning, whereas curiosity, intrinsic motivation, and flow have been conceived of as being associated with an optimal state of arousal for learning. Although the Boredom Proneness Scale gives us a generalized picture of what it means for a person to have a tendency to become easily bored, it does not tell the full story. Some individuals may manage their arousal states better than others, and thus may adjust subconsciously when they begin to feel bored. The BPS suggests a negative correlation, but other boredom scales exist that assess different dimensions of boredom. To understand more fully the nature of the relationship between love of learning and boredom, more research needs to be accomplished. For example, correlating scores on other boredom surveys and scores on the love of learning survey would further define the relationship between love of learning and boredom. Also, interviews might be conducted with participants about boring or fun learning experiences and how each affects one's attitude toward learning . Finally, an experiment using interesting or fun learning activities following up with the love of 190

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learning survey could also be conducted. Similarly, the Test Anxiety Scale of the Motivated Strategies for Learning Questionnaire (MSLQ) does not measure anxiety in general but measures test anxiety only. This mayor may not be the best anxiety measure to compare with love of learning. Perhaps one's love oflearning is associated by test anxiety because of factors that differ from the relationship between love of learning and a more general anxiety. One would expect that test anxiety is part of a more general anxiety and that therefore love of learning would have a negative correlation with anxiety in general. However, this question needs to be addressed in future research. Studies similar to those suggested for boredom may be conducted using variables such as difficulty of task or anxiety rather than boredom. Question 4. What is the relationship between the love of learning construct and a construct that may and likely should have an intermediate correlation with the love of learning construct within the young adult (18 to 25 years) age group? Specifically, for borderline validity (Krathwohl, 1993): What is the relationship between scores on the love of learning measure and scores on a self-actualization measure? The correlation between the love of learning scores and the scores on the Short Index of 191

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Self-Actualization (SISA) was positive and significant but not strong (.172). This finding makes sense. The construct of self-actualization essentially means the discovery of the real self and includes self-expression, self-growth, and optimizing potential (Maslow, 1943). Specifically, the Short Index of Self-Actualization has five factors: autonomy, self-acceptance and esteem, acceptance of emotions and freedom of expression of emotions, trust and responsibility in interpersonal relations, and facing vs. avoiding undesirable events in life. Thus, self-actualization measured with this instrument is a construct interconnected particularly with the love-of-Iearning subconstruct of self-concept in terms of competence, growth, and meaning. However, self-actualization does not necessarily correspond to other subconstructs comprising the love of learning. Thus, only a moderate correlation was anticipated. A drawback of this finding is that research with SISA consistently reports only modest reliabilities. Jones and Crandall (1986) reported a Cronbach's alpha of .65 and a 12-day test-retest reliability of .69. Richard and Jex (1991) reported a Cronbach's alpha of .65. The internal consistency of the SISA in this study was .64, also using Cronbach's alpha. These reliability figures are modest. Jones and Crandall explained this consistency figure by stating that the SISA was developed to assess a broad range of behaviors and attitudes, thus they expected low reliabilities. However, these modest reliabilities may also explain the moderate correlation with the love of 192

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learning measure. The literature supports a positive, but perhaps not strong, relationship between love of learning and self-actualization. Maslow (196811982) defined self-actualization as an "episode, or a spurt in which the powers of the person come together in particularly efficient and intensely enjoyable way, and in which he is more integrated and less split, more open for experience, more idiosyncratic, more perfectly expressive or spontaneous, or fully functioning, more creative, more humorous, more ego transcending, more independent of his lower needs" (p. 97). Such an experience may occur occasionally when learning, but it is not the exclusive domain of learning even though it may lead to a transformed life. Nor does this definition suggest that learning is the primary means through which a self-actualization experience is gained. Yet Maslow (1971) stated that self-actualization is about self-growth. He thought that the ultimate goal of education is to help the person fulfill his or her potential as a human being. These perspectives of self-actualization imply that self-actualization may overlap with love of learning. How might self-actualization conceptually overlap with love of learning? In studying well-being, Ryff (1989) defined the ideas of self-acceptance, autonomy, environmental mastery, purpose in life, and openness to experience. Her conceptualizations of self-acceptance and autonomy both included self-actualization. 193

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Thus, Ryff interconnected pieces of this study's portrayal of self-concept with self actualization. Maslow (1968) defined self-actualization in terms of 15 components: (a) accurate perception of reality, (b) acceptance of self and others, (c) spontaneity, (d) task-centeredness, (e) enjoyment of solitude, (f) self-reliance, (g) appreciation of newness, (h) meaningfulness of experience, (i) kinship with humankind, G) intimacy of friendships, (k) democratic treatment of others, (1) strong ethical orientation, (m) philosophical sense of humor, (n) creative, and (0) transcendence of culture. Without defining each component, one can see that there may be conceptual overlap with only several: acceptance of self and others, task-centeredness, self-reliance, appreciation of newness, meaningfulness of experience. These components are also similar to Ryff's definitions of self-acceptance and autonomy. However, what is important here is how many of these 15 components seem irrelevant to the love of learning, such as democratic treatment of others and philosophical sense of humor. As is implied by Maslow's definition, scholarly research, and the present study, love of learning may be only part of the self-actualization process, as self-actualization seems to be captured by some of the subconstructs comprising love of learning. More research would clarify further this relationship. What would be particularly interesting to examine is whether there is causality in this relationship. 194

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Question 5. What is the relationship between the love of learning construct and a construct that may and likely should have low or no correlation with the love of learning construct within the young adult ( 18 to 25 years) age group? Specifically, for contrary validity (Krathwohl, 1993), what is the relationship between scores on the love of learning measure and scores on a flexible thinking measure? The relationship between love of learning scores and scores on the Flexible Thinking measure was low and not statistically significant (.132). From one point of view, it might be expected that flexible thinking would be positively correlated with love of learning. However, this implies that individuals who are inflexible or rigid in their thinking do not love to learn. This implication is probably not accurate. Several questions arise. Was the correlation low because the two constructs really are not related? Are there intervening variables? Was there a lack of variability in the Flexible Thinking Scale to adequately measure the relationship of flexible thinking with love of learning? Jausovec (1994) went beyond flexible and rigid thinking to models of knowledge. He thought that knowledge could be classified as everyday and theoretical knowledge. He defined everyday knowledge as rigid but diverse and effective in action. He described theoretical knowledge as abstract, mobile, and far 195

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from reality. He proposed that rather than flexible thinking, mobility in thinking, represented "the ability to create different viewpoints within the systems of knowledge" (p. 36). This helps explain why people who love to learn may be either flexible or rigid in their thinking and why flexible thinking may not be related to love ofleaming. Jausovec assumed that flexible thinking involves intelligence, the ability to transfer training, and creativity. He pointed out that most research in problem-solving and intelligence shows individual differences in ability, he suspected that the individual difference may be accounted for in flexibility in thinking. Additionally, one of Schank's (1982) four memory structures is Thematic Organization Points (TOP) which are structures that allow humans to abstract and transfer learning across domains and represent flexible thinking. Third, in developing the Structure-of Intellect (SOl) model, Guilford (Guilford, 1971; Guilford, Wilson, & Christenson, 1952) identified five creative thinking factors, three of which reflect flexible thinking: divergent production of semantic classes, divergent production of transformations, and flexibility of closure. Two of these represent forms of transfer of training, and the third is rather creative productivity of ideas. Torrance (1974) used some of these findings to define flexibility as a person's ability to produce a variety of ideas, to shift from one approach to another, or to use a variety of strategies. Thus, flexible thinking seems more related to intelligence, transfer of training, and creativity than to love of 196

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learning. These mental abilities may be intervening variables and at this point no connection has been drawn between any of these and love of learning. Sa, West, and Stanovich (1999) defined flexible thinking as a multifaceted construct that encompasses the cultivation of reflectiveness rather than impulsivity, the seeking and processing of information that disconfirms one's beliefs, and the Willingness to change one's beliefs in the face of contradictory evidence. They developed the flexible thinking scale used in the study to assess their definition of flexible thinking. However, Stanovich and West (1997) reported a Flexible Thinking Scale split-half reliability of.49 with a Spearman-Brown correction, and Cronbach's alpha internal consistency of .50, which are rather low. Likewise Cronbach's alpha for the Flexible Thinking Scale in this study was also low, at .50. These low reliabilities may account for the low correlation between love of learning and flexible thinking. Although common sense may suggest that perhaps a relationship between love of learning and flexible thinking exists, this study found no such relationship. Intervening or moderating variables may be intelligence and problem-solving ability, the ability to transfer knowledge across domains, and creativity. These seem to reflect the essence of flexible thinking. None of these variables were initially considered part of the love of learning. They are important components of creativity and learning. 197

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Research could definitely examine the relationships among this constellation of variables in more depth. Also, correlating different measure of flexible thinking with the love of learning might reveal different results. A subset of the above correlation coefficients were examined in a hybrid form of Campbell and Fiske's (1959) multitrait-multimethod approach to construct validation. The correlations pertinent to the love of learning instrument were as expected. The two correlations representing monotrait-different methods (love of learning with curiosity [.747] and love of learning with intrinsic enjoyment [.339]) were higher than the correlation representing heterotrait-monomethod (love of learning with test anxiety [-.209]) and heterotrait-heteromethod (love of learning with boredom proneness [-.202]). These results support construct validity, however, this result needs qualification and closer examination. Limitations Three methodological weaknesses in this multitrait-mltimethod study are notable. First, all of the measures used were paper-and-pencil self-report surveys. A stronger statement regarding the validity of this instrument could be made had more diverse methods, such as outside observations, peer ratings, etc., been used. For the most part, the love of learning instrument was administered at a separate time than the f 198

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battery of scales for validation. Usually, the love of learning instrument was completed during class and the battery of scales for validation was completed on the students ' own time. One exception is that in one state college, 52 participants (or about 33% of the total validation sample) completed the love of learning survey during the same sitting as the battery of scales for validation. They were separated only by consent letters and paper clips. The second weakness is related to the first. Those paper-and pencil self-report surveys categorized as similar traits using different methods (monotrait heteromethod) varied only in regard to response formats. For example , the 20-item trait scale from Melbourne Curiosity Inventory (MCI) (Naylor, 1981) consisted of a 4-point frequency response set: Almost Always, Often, Sometimes, and Almost Never. This response format differs only slightly from the 5-point agreement response format of the love of learning instrument. Arguably, the MCI could be considered a monotrait-monomethod comparison . Thus, some of the high correlation may be attributable to similar measurement methods. The Intrinsic Enjoyment scale from the Intrinsic Enjoyment and Boredom Coping Scales (Hamilton, Haier, & Buchsbaum, 1984) has nine forced choice items. This response format is quite a bit different from a 5-point agreement format. Thus, this comparison is more defensible as a monotrait heteromethod convergent correlation. 199

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As with the convergent validity variables, the discriminant validity correlations using different traits and either similar or different methods, varied only in regard to response format. For instance, the 5-item Test Anxiety Scale, from the Motivated Strategies for Learning Questionnaire (MSLQ) (Pintrich, Smith, Garcia, & McKeachie, 1991) is based on a 7-point Not True At All to Very True Of Me scale and was selected as a heterotrait-monomethod discriminant validity measure. As well, the Boredom Proneness Scale was categorized as a heterotrait-heteromethod discriminant validity coefficient, and consisted of 28 true and false items (Farmer & Sundberg, 1986). As an aside, had either the Flexible Thinking Scale (Sa, West, & Stanovich, 1999) or the Short Index of Self-Actualization Scale (Jones & Crandall, 1986) been chosen for the multitrait-multimethod study, they would have been considered heterotrait-monomethod discriminant validity coefficients, because their response formats were both in terms of agreement, as is the love of learning scale, differing only in point spread. Both of these correlations are smaller than the monotrait heteromethod correlations, which is desirable. These weaknesses suggest that although the correlations in the multi trait multimethod matrix . show evidence of construct validity without error due to measurement, they should be interpreted with caution. One cannot conclude that sufficient construct validity evidence has been demonstrated using all paper-and pencil self-report measures differing only in response formats. A stronger approach to 200

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study construct validity would be to use other than paper-and-pencil measures for assessing love of learning, For example, love of learning scores of students nominated by peers or identified by instructors as having a strong love of learning or as having a little love of learning could be Such an approach exemplifies a method different from a paper-and-pencil measurement. A third limitation pertains to the generalizability of the findings. Seemingly, students in the 18to 25-year old range vary on love of learning as a trait or disposition. However, this sample mayor may not be representative of the young adult population in the 18to 25-year-old range. The survey was administered to college students at a variety of different types of higher educational settings. It is not certain whether similar results would be obtained in other settings, such as work or the military, other geographical areas of the country, etc. Second, the selection of institution was not based on a random process, but was based on which institutions agreed to participate in this research . Likewise, participants were not randomly selected, but rather volunteered to participate, sometimes for an incentive and sometimes not. Additionally, although sample sizes were adequate, more detailed demographic information would shed light on the representativeness of the sample and the generalizability of the results. Finally , the non-significant mean difference between male and female college students was encouraging, however, the reasons for significant difference for educational level, marital status, and online versus face-to201

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face class settings are unclear and call for further research. In spite and in light of the limitations of this study, the love of learning measure offers an adequate working definition for the love of learning construct for several reasons. First, there is evidence of overlap among the constructs hypothesized to comprise love of learning. Second, second an exploratory factor analysis showed four factors that may be reasonably interpreted as defining for the love of learning. Third, correlations between and among various other instruments are of the expected strength and the appropriate direction. Fourth, the multitrait-multimethod set of correlations hold the appropriate strengths with one another to suggest that measurement is not a serious problem. Theoretical Foundations, Implications for Practice, and Further Research The results of this study provide evidence that a love of learning construct exists. They support Bronzaft's (1996) belief that love of learning is rooted in natural childhood curiosity. They parallel and extend the love of learning and academic interest factors identified by Guglielmino (1977). Michael, Smith, and Michael (1984), and Michael, Denny, Ireland-Galman, and Michael (1986). They add a new dimension to the theoretical research in the areas of curiosity, intrinsic motivation, interest, flow, and self-concept in terms of competence, growth, and meaning. In 202

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effect, the results suggest that these subsconstructs are conceptually interrelated. As previously mentioned, the literature showed a great deal of conceptual overlap among the constructs. Scholars identified overlaps between curiosity and intrinsic motivation (Beswick, 1974; Day, Berlyne, & Hunt, 1971; Malone & Lepper, 1987), among intrinsic motivation, perceived control, and felt need for competence (Deci, 1975; 1980), among intrinsic motivation, curiosity, control, and challenge (Malone & Lepper, 1987), between flow and intrinsic motivation (Csikszentmihalyi, 1988a; Deci & Ryan, 1985), between curiosity and interest (Ainley, 1986; 1987; Bergin, 1999), and between intrinsic motivation and interest (Deci, 1998; Hamilton, Haier, & Buchsman, 1984). Occasionally, scholars distinguish among various subconstructs. For example, Hidi and Anderson (1992) pointed out that curiosity's relationship to Berlyne's (1974) collative variables forms an inverted U, whereas the relationship between interest and the collative variables is monotonic. Further, Hidi (1990) pointed out that interest extends beyond the variables that define curiosity. Rheinberg (1998) argued that intrinsic motivation is inherent to a given activity, whereas interest is activity-indifferent. Hidi and Harackiewicz (2000) suggested that the two constructs may be recursively related to each other. Overlapping subconstructs and their relationships to love of learning and each other remains an area to explore further. Finding new constructs that mayor may not relate to love of learning is another possibility. 203

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Love of learning is a construct that could be studied by a variety of disciplines, such as psychology, education, and sociology. For example, developmental psychologists may want to know how love of learning conceptualized at different ages. Another question is how does love of learning develop across the lifespan. Further, combining psychometrics and developmental psychology, a question to research is whether or not the love of learning instrument developed as part of this study is useful for older adults, adolescents, or grade school children? What age differences might emerge? Does love of learning differ for people who are not in school? Educators may wonder how to foster a love of learning in their students. Some scholars have suggested how love of learning might be fostered, but with a better conception of what love of learning is, educators may be able to develop more effective methods, curriculi, and relationships with students and the community for fostering a love of learning. Educators may want to explore, too, whether love of learning is useful within the educational milieu to improve the teaching and learning process as compared with other models of motivation. Sociologists may be interested in how the demographicallandscape affects love of learning among people. Extensive demographic data were not collected as part of this study. Additional demographic information may be needed to fully understand the nature of love of learning. Second, further research to examine the 204

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relationship between love of learning scores and educational attainment would help clarify the relationship between those two variables. Comparing love of learning scores among various ethnic groups and economic classes would provide information on whether the love of learning instrument is free of test bias or whether love of learning varies according to those kinds of demographic variables. Of note was the significant difference in mean scores between online students and traditional classroom students. Was this difference due to methodological differences in instrument administration or is there a difference in love of learning between these two groups? This question bears further investigation. Love of learning seems to encompass affect and motivation, plus the behaviors and mental processes that reflect them. What theories exist today within which love of learning might fit? They are legion. Most likely any theory of affect or motivation would explain to a certain extent love of learning. For example, love of learning may be explained by expectancy value theory or self-determination theory. Optimal arousal theory may also explain love of learning. Of particular note is Izard's conceptualization of human emotions. When Izard (1977) described human emotions in terms of interest-excitement and intrinsic motivation, his descriptions included almost all of the subconstructs used to define love of learning in this study. Interest excitement and intrinsic motivation include curiosity and wonder, as described by Dougall (1912). They include epistemic curiosity defined by Berlyne (1954a) and the 205

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motivation inherent in information processing described by Hunt (1971). They include functional autonomy (i.e., self-concept) as conceptualized by Allport (1955) and effectance as introduced by White (1959). Finally, the urge to discover as explained by Murphy (1958) is not just curiosity butfreeing of intelligence from cultural clamps and moving forward in a positive way activated by a thirst for contact with the world and for understanding and making sense of it" (p. 19). The urge to discover is part of the human emotions of interest-excitement and intrinsic motivation, and also captures self-concept in terms of growth and meaning. Because the love of learning construct is just being defined, discovering out how various theories add to the construct would be desirable. A final area of research and practice that may benefit by the introduction of a love of learning construct is the area of adult education. The love of learning is found in the pioneering work of Houle (1961) in adult education. He interviewed twenty two adults because they were perceived by others as being deeply engaged in learning. They themselves regarded continuing education as an important part of their lives. Houle found three kind of learners: (a) the goal-oriented learners, who have a purpose or goal, which initiates educational endeavors; (b) the activity-oriented learners, who use learning as a means to a different end such as to socialize; and (c) the learning-oriented learners, who are interested in personal growth and possess a desire to know. The later work of Sheffield (1964) and Boshier (1971; 1985) basically 206

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confirmed Houle's initial study. Tough (1968, 1969, 1979), too, has examined reasons why adults begin and continue to learn (Tough, 1968). Of the thirteen reasons he uncovered, six reflect love of learning: to resolve a puzzlement-curiosity-question, for the satisfaction of being knowledgeable, for the enjoyment of learning, for the enjoyment of mastering a skill, for the feeling of learning successfully, and for the pleasure of learning itself (Tough, 1969). Tough (1979) reported that about 90 percent of all women and men initiate and conduct at least one major deliberate learning effort a year (five on average). Only 20 percent of those are for professional or economic goals. Contextualized with these early adult education researchers, love of learning may find a place alongside other useful adult learning and education theories and practices. If educators are to make progress in facilitating a disposition towards a love of learning in students, then they need to have a clear understanding of what this construct means. The research reviewed, the measure developed, and the results obtained help by suggesting a definition of the love of learning construct. Deci (1995) stated that "the strivings for competence and autonomy together propelled by curiosity and interest are thus complementary growth factors that lead people to become increasingly accomplished and to go on learning throughout their lifetimes" (p. 71). Such a description reflects love of learning as defined in this study. Love of learning probably provides the impetus to learn throughout our lives, which with the 207

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increasing complexity and globalization of today's world should be considered invaluable. 208

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APPENDIX 209

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APPENDIX A Premises and Principles of the Leamer-centered Model 210

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Premises of the Leamer-centered Model 1. Learners are distinct and unique. Their distinctiveness and uniqueness must be attended to and taken into account if learners are to engage in and take responsibility for their own learning. 2 . Learners' unique differences include their emotional states of mind, learning rates, learning styles, stages of development, abilities, talents, feelings of efficacy, and other academic and nonacademic attributes and needs. These must be taken into account if all learners are to be provided with the necessary challenges and opportunities for learning and self-development. 3. Learning is a constructive process that occurs best when what is being learned is relevant and meaningful to the learner and when the learner is actively engaged in creating his or her own knowledge and understanding by connecting what is being learned with prior knowledge and experience. 4. Learning occurs best in a positive environment, one that contains positive interpersonal relationships and interactions, that contains comfort and order, and in which the learner feels appreciated, acknowledged, respected, and validated. 5. Learning is a fundamentally natural process, learners are naturally curious and basically interested in learning about and mastering their world. Although 211

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negative thoughts and feelings sometimes interfere with this natural inclination and must be dealt with, the learner does not require "fixing." 212

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Metacognitive and Cognitive Factors Principle 1: The nature of the learning process. Learning is a natural process of pursuing personally meaningful goals, and it is active, volitional, and internally mediated; it is a process of discovering and constructing meaning from information and experience, filtered through the learner's unique perceptions, thoughts, and feelings. Principle 2: Goals of the learning process. The learner seeks to create meaningful, coherent representations of knowledge regardless of the quantity and quality of data available. Principle 3: The construction of knowledge. The learner links new information with existing and future-oriented knowledge in uniquely meaningful ways. Principle 4: Higher-order thinking. Higher-order strategies for "thinking about thinking"--for overseeing and monitoring mental operations--facilitate creative and critical thinking and the development of expertise. Affective Factors Principle 5: Motivational influences on learning. The depth and breadth of information processed, and what and how much is learned and remembered, are 213

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influenced by (a) self-awareness and beliefs about personal control, competence, and ability; (b) clarity and saliency of personal values, interests, and goals; (c) personal expectations for success or failure; (d) affect, emotion, and general states of mind; and (e) the resulting motivation to learn. Principle 6. Intrinsic motivation to learn. Individuals are naturally curious and enjoy learning, but intense negative cognitions and emotions (e.g., feeling insecure, worrying about failure, being self-conscious or shy, and fearing corporal punishment, ridicule, or stigmatizing labels) thwart this enthusiasm. Principle 7: Characteristics of motivation-enhancing learning tasks. Curiosity, creativity, and higher-order thinking are stimulated by relevant, authentic learning tasks of optimal difficulty and novelty for each student. Developmental Factors Principal 8: Developmental constraints and opportunities. Individuals progress through stages of physical, intellectual, emotional, and social development that are a function of unique genetic and environmental factors. 214

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Personal and Social Factors Principle 9: Social and cultural diversity. Learning is facilitated by social interactions and communication with others in flexible, diverse (in age, culture, family background, etc.), and adaptive instructional settings. Principle 10. Social acceptance, self-esteem, and learning. Learning and self-esteem are heightened when individuals are in respectful and caring relationships with others who see their potential, genuinely appreciate their unique talents, and accept them as individuals. Individual Differences Principle 11: Individual differences in learning. Although basic principles of learning, motivation, and effective instruction apply to all learners (regardless of ethnicity, race, gender, physical ability, religion, or socioeconomic status), learners have different capabilities and preferences for learning mode and strategies. These differences are a function of environment (what is learned and communicated in different cultures orother social groups) and heredity (what occurs naturally as a function of genes). Principle 12: Cognitive filters. Personal beliefs, thoughts, and understandings resulting from prior learning and interpretations become the individual's basis for 215

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constructing reality and interpreting life experiences. 216

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APPENDIXB Definitions of Curiosity, Intrinsic Motivation, and Interest 217

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Definitions of Curiosity, Intrinsic Motivation, and Interest Author/ Curiosity Intrinsic Motivation Interest Definition Ainley, M. D. (1987) Breadth and depth of interest Bergin, D. A. (1999) Involves positive affect, preference for, and autotelic activity; either person-or situation-centered; synonyms are attention, curiosity, engagement Berlyne (1950, 1954a, (1950) Drive-stimulus-producing (1971) Motivation "aimed at 1954b, 1960, 1971) response certain internal consequences that tv 00 (1954a) Curiosity is a drive which constitute intrinsic reinforcements is reduced by receiving and or reward" (p. 188) rehearsing knowledge. (1954a, 1954b,1960) Noveltyseeking and epistemic, information seeking, externally stimulated Beswick, D. G. (1974) Curiosity may be understood as a Curiosity is commonly taken to be predisposition to create, maintain the prototypical example of and resolve conceptual conflicts (p. intrinsic motivation (p. 15) 16) Camp & Dietrich (1985) As a trait, an enduring interest in acquiring new information. As a state or contextually focused activity, it is the desire to seek specific knowledge. Csikszentmihalyi (1988) Flow has become a technical term in the field of intrinsic motivation" (p. 3). Research on intrinsic motivation has mostly

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focused on behavior while flow is subjective experience. Day, H. I. (1971) 1) reacts positively to new, strange, incongruous or mysterious elements in the environment by moving towards them, exploring or investigating them, and/or expressing interest in them 2) tends to persist in such positive reactions gaining information in the process DeCharms (1976) The desire to be the origin of one's own actions tv 10 Deci (1975) Like White, curiosity (1975) Curiosity; competence, (1992) consists of following subsumed within realm of all personal autonomy, effectance components: Person -match intrinsically motivated behavior (1980) The reward is the activity between persona and environment; experiential -attention, delight, itself; optimal level of positive feelings (intrinsic physiological and psychological motivation); dispositional stimulation and felt need for competence. It is purposive and component -enduring desire to engage in an activity (narrow or self-directed. broad); activity -includes an (1995) Being wholly involved object to anchor optimal relation with an activity; the desire to be with person. the origin of one's own actions Fowler (1965) Instinct, drive, and response to novelty, change, and complexity Freud A derivative of sex drive Harlow (1950, 1953) Exploratory behavior First to use intrinsic motivation: inherent in activity itself

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Hebb (1955) A natural tendency to make sense of the world evoked by violated expectations Hunt, D . E. (1971) Student-directed learning Hunt, J. M. (1971) "motivation which is inherent in information processing and action " (p. 1), evoked by incongruous stimuli, violated expectations James (1890,1950) Scientific inquiry and novelty seeking (p. 430) Kagan (1972) Epistemic curiosity is one of four basic motives: the motive to resolve uncertainty Krapp, Hidi, Renninger Usually conceived as person(1992) environment interaction. May be dispositional or process-oriented Lepper & Malone (1987) Involves challenge, competence, effectance, mastery, curiosity, incongruity, discrepancy, perceived control, and selfdetermination Livson, N. (1967) curiosity is a tendency, or motive, to acquire or transform information under circumstances that offer no immediate adaptive value for such activity (p. 77) Loewenstein, G. (1994) Information-gap Malone (1981) Desire to bring better form to one's knowledge structures .

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Malone & Lepper (1987) Most direct intrinsic motivation for Fun, captivating, enjoyable learning activity that people engage in for its own sake Maw, W. H. (1971) 1) reacts positively to new and strange, incongruous, or mysterious elements in his environment by moving toward them, by exploring them, or by manipulating them. 2) exhibits a need to know or a desire to know more about himself and/or his environment. 3) scans his surroundings seeking new experiences. 4) persists in examining and exploring stimuli in order to know more about them Penney & McCann 1) tendency to approach and (1964) explore relatively new stimulus situations 2) tendency to approach and explore incongruous complex stimuli Prenzel (1992) Selective persistence by a person with an "object" which corresponds to developing self-regulation Schmeck & Ribich Curiosity is positively correlated to (1977) the synthesis-analysis, study methods, and elaborative processing scales of the Inventory of Learning Processes. It was not

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N N N St. Augustine (1943) Starr (1992) Suchman (1971) Wlodkowski & Jaynes (1990) White (1959) correlated to the Fact Retention Scale. Certain vain and curious longing for knowledge (p.54) Information seeking and experience seeking Motivation to master one's environment or effectance or competence Activity prompted by internal conditions such as doubts, discrepancies , and contradictions triggered by external stimuli. Closure motivation is related to finding solutions. Opensure motivation is related to exploration. Desire to learn, perseverance in learning, the value of learning because learning is a satisfying and rewarding activity in and of itself .

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APPENDIXC Psychometric Information about Various Curiosity Instruments 223

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Psychometric Information about Various Curiosity Instruments Author(s) and Dates Title of Description Sample Reliability Validity Instrument Penney & McCann Children's Revised to 40 true4tn, 5tn, 6tn grades Test-Retest: Mixed: 6Ut grade scores (1964) Reactive false items plus a 102 weeks: .67 to positively correlated to Curiosity Scale item lie scale .91, p < .01 originality, 4th grade scores did not Penney & Reinehr StimulusAdults: Test-Retest: Positive correlation (1966) Variation Males = 128 Males = .84 with perceived moveSeeking Scale ment , sensation Females = 155 Females = .87 seeking, and originality. No correlation with anxiety, authoritarianism, scholastic aptitUde Garlington & Shimota Change Seeker Revised 95-items Adults: Split half = .85 Positive correlation (1964) Index College males = 105 (N = 80) with Graves Art Judgment Test, Welsh College females = Test-Retest: Revised Art Test 137 7-10 days = .91 No correlation to Soldiers = 60 (N = 48) intelligence, ShipleyHartford Institute of 3 months = .77 Living Scale. Inversely (N =44) correlated (slightly) with age Zuckerman (1964) Sensation Revised 34-items Adults: Split half: Positive correlation Zuckerman et al. (1978) Seeking Scale Undergraduate males Males = .68 with field independence =268 in Embedded Figures

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Undergraduate Females = .74 Test. females:: 277 No correlation with plus various Howard's Stimulus unspecified sample Seeking Maze. sizes Negative correlation with anxiety from Multiple Affect Adjective Checklist. Cross-cultural support Pearson (1970) Novelty 90 items Adequate Appropriate Experiencing correlations with Scale Sensation Seeking Scale, Edwards Personality Inventory for change, Activities Index for change, and Personality Research Form for change. Day (1969) Ontario Test of 110 items : KR-20 : Appropriate Intrinsic 90 true-false .87 .95 correlations with Motivation achievement, 10 diversive curiosity personality , mental 10 lie scale health, anxiety, aesthetic judgement, creativity Leherissey (1971 a , State Curiosity Adults 1971b) Scales, renamed a= .87, .89 Positive correlation State Epistemic Curiosity Scale with OTIM (r = .43. P < .05) Negative correlation with State-Trait Anxiety Inventory

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(STAI) (A -State) (r =-.36, p < .01) Positive correlation with OTIM (r = . 37, p < Undergraduate a = .81 .96 .01) females = 152 Negative correlation with STAI A-State (r = -.34 to -.75, p < .05) Naylor (1981) Melbourne 40 Likert items: High school and posta = .84 .93 Principal Components Curiosity 20 State secondary students Test-Retest: Analysis support , Inventory n = 98 339 Positive correlations 20 trait 25 days = .83, with five occupational 103 student areas in the Strongteachers Campbell Interest 5-weeks = .77 for Inventory, positive correlations with verbal 82 high school but not numerical males ability Vidler & Rawan (1974; Scale of 80 true-false items Adults: Split half = .88 Insignificant positive 1975) Academic College students = KR-20= .87 correlation with W AIS Curiosity Digit Symbol test. 170 significant positive correlation with Associations III test of convergent thinking Positive correlations Odd-even split with final biology exam, final biology N=611 half with grade, GPA, Davis Spearman-Brown Reading Test , ETS

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N N '-l prophesy correction = .87 English test. Factor analysis = 5 factors, 24% of the variance

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APPENDIXD Contact and Consent Letters Letter of Request to Departmental Chairs Letter of Consent to Participate in Love of Learning Survey Research Letter of Consent to Participate in Love of Learning Validation Research 228

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Departmental Dean or Chair Colorado College or University City, Colorado Dear Sir or Madam, Date I am writing this letter to request permission to solicit participation by your students in a research project conducted in collaboration with the University of Colorado at Denver's School of Education as part of my doctoral dissertation. I am a doctoral candidate at CU-Denver and am interested in investigating the love of learning as a trait in young adults. The purpose of the study is to describe love of learning and explore the relationships among love of learning and other concepts such as curiosity, boredom, and self-actualization. This study consists of survey research. I will ask students to complete a 30item self-report survey, which includes demographic information. This will take about 15 minutes. Some students will be invited to participate in the validation portion of the study, which involves completing six more surveys. This will take about 30 more minutes. All responses and demographic information will be kept confidential and anonymous. Student participation is completely voluntary and will be greatly appreciated. Results will be used to understand how the love of learning develops in an individual's life. I have obtained the appropriate approval from the Human Subjects Review Committee at the University of Colorado at Denver. I hope you decide to allow me to solicit participants from classes in your department (school). I will call you or email you, if you prefer, to discuss the matter further. My telephone number is (303) 904-4542 and my email is tmcfarlane@ceo.cudenver.edu. Thank you very much for your consideration. Sincerely, Terry McFarlane, Doctoral Candidate School of Education, University of Colorado at Denver 229

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Date Dear Student, I am writing this to request your participation in a research project conducted in collaboration with the University of Colorado at Denver's School of Education as part of my doctoral dissertation. I am a doctoral candidate at CU-Denver and am interested in investigating the love of learning as a trait in young adults. The purpose of the study is to describe love of learning and explore the relationships among love of learning and other concepts such as curiosity, boredom, and self-actualization. This study consists of survey research. You are asked to complete a 25-item self-report survey, which includes demographic information. This will take about 15 minutes. I ask that you respond honestly. All of your responses and demographic information will be kept confidential and anonymous. Your participation is voluntary and will be greatly appreciated. Completion of this survey implies that you give your consent to participate in this study. Results will be used to understand how the love of learning develops in an individual's life. I hope you decide to participate. Thank you very much. Sincerely, Terry McFarlane, Doctoral Candidate School of Education, University of Colorado at Denver 230

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Date Dear Student, I am writing this to invite you to participate in a research project conducted in collaboration with the University of Colorado at Denver's School of Education as part of my doctoral dissertation. I am a doctoral candidate at CU-Denver and am interested in investigating the love of learning as a trait in young adults. The purpose of the study is to describe love of learning and explore the relationships among love of learning and other concepts such as curiosity, boredom, and self-actualization. This study consists of survey research. You are asked to complete a 93-item survey, which includes several different questionnaires, subscales, and demographic information. This will take about 40 minutes. Please respond honestly. Send the completed questionnaire to me in the provided, self-addressed and stamped envelope. As an incentive to complete this survey, I have two $25 gift certificates to Amazon.com. You should keep the blue strip of paper with the questionnaire number on it. The numbers of all returned questionnaires will be put in a hat and one will be drawn at the beginning of December. Although I will not know who that individual is, I will be able to tell what school and class he or she was in when the surveys were distributed. I will forward the two gift certificates to the instructor who will match the number to the individual. One gift certificate goes to the student and the other to the instructor. Since I plan to collect no more than 100, participants have about a one in 100 chance of winning! Your participation is voluntary and greatly appreciated. All of your responses and demographic information will be kept confidential. Your identity will not be revealed in the results. Some group comparisons will be made and reported in summary form. Completion of this survey implies that you give your consent to participate in this study. If you decide to participate in this project, keep this sheet for your information. If you have any questions about the research, you may contact me at any time. 231

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My phone number is (303) 904-4542. My email is tmcfarlane@ceo.cudenver.edu. If you have any questions about your rights as a research participant, you may contact the Office of Academic Affairs, CU-Denver Building, Suite 700, (303) 556-2550. Results will be used to understand how the love of learning develops in an individual's life. I hope you decide to participate. Thank you very much. Sincerely, Terry McFarlane, Doctoral Candidate School of Education, University of Colorado at Denver 232

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APPENDIXE Love of Learning Items and Sources List of 72 Items by Subconstruct List of Sources of 72 Items 233

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List of 72 Items by Subconstruct Curiosity I very much like to discover new ideas that I can further explore on my own. I am usually on the lookout for opportunities in which I can learn something. I spend a lot of time asking questions to satisfy intellectual puzzlements I frequently find myself asking questions to get more information. I like to think of unusual ways to solve puzzles. I could spend hours seeking knowledge. I enjoy the process of intellectual enrichment. I like to try new things, even if I'm not sure how they will turn out. I often enjoy searching for answers. Intrinsic Motivation I enjoy taking things apart to "see what makes them tick" It's fun to try to solve problems. I like to apply existing theories to new things I'm learning to see how it works. Learning is worthwhile for its own sake. Learning is fun. I loved to read as a young child. As a young adolescent, I read a lot more than my peers. I like to learn just for the sake of learning . 234

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It's fun to develop new ways of categorizing, classifying, and understanding things. Learning is worth doing for its own sake. Interest I have about as much fun learning about things as I do in my recreation time (shopping, sports, entertainment, etc.) Learning is my favorite free time activity I often use my free time learning about things. I usually persist in learning about something until I am satisfied. When I become engaged in a puzzlement, I can become absorbed in learning about it for hours. I frequently become interested in puzzling phenomena. I often find what I learn very interesting. I allow plenty of time to learn about things of interest to me. I prefer to fill my spare time learning about things. I obtain more pleasure in learning than I do from most other things that I could be doing instead. I would rather read a new book on a subject that interests me than to participate in an enjoyable recreational activity. I am persistent in my learning. Flow I can often totally concentrate when I am learning. I usually feel that my abilities allow me to meet the challenge of a learning opportunity. I usually feel a sense of control of the learning process. I usually am aware of how well I am learning When I become absorbed in learning, I forget about outside distractions. 235

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I find it enjoyable to become engaged in learning about most things. I love the feeling I get with most learning experiences and want to capture it again and again. Learning experiences usually leave me feeling great. I can focus my attention entirely on what I am learning. I engage in most learning experiences without having to think about it. I occasionally become so absorbed in learning that I lose track of time. I occasionally become so absorbed in learning that I lose my self-consciousness. Self-concept in terms of Competence I enjoy the learning process more when I set specific learning goals. In most learning situations I know what I want to achieve. If there is something I want to learn, I can figure out a way to learn it. I plan to learn throughout my life. Learning helps me to interact within my environment more effectively. Learning helps me to solve problems I encounter. I can usually handle questions requiring the comparison of different concepts. I can usually draw inferences. I can usually state the underlying message of films and readings. Learning gives me a sense of competence. I feel that I am successful as a learner. I feel competent enough to meet the demands of most learning situations. Self-concept in terms of Growth and Complexity I spend my free time attending workshops or lectures for personal growth. I learn to grow as a person. 236

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I learn to improve myself. I like dealing with questions where there is not one right answer. Learning better prepares me to deal with a complex and changing world. I learn because I enjoy becoming more familiar with different things. Learning gives me a sense of fulfillment. I get a kick out of thinking of many different ways to resolve a puzzlement. I learn to improve my ability to understand complex issues. I enjoy looking at problems from different points of view. Self-concept in tenns of Meaning and Purpose I learn to satisfy a deep curiosity about life and ideas. I learn to improve my understanding of life. I find learning to be personally meaningful in some way. Learning gives me opportunities to create new meanings in my life. What I gain from learning gives me a feeling of deep personal satisfaction. I enjoy being a seeker of knowledge. Learning has become a way of life. Learning gives me a sense of fulfillment. One of my aims in life is to discover my own philosophy and belief system and to act in accordance with it. I have a strong desire for enlightenment. I enjoy probing deeply into things. 237

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List of Sources for 72 Items Learning Process Questionnaire and Study Process Questionnaire Instruments Biggs, J. B. Dimensions of study behavior: Another look at AT!. British Journal of Educational Psychology 46, 68-80. Biggs, J. B. (1987). Learning Process Questionnaire manual. Melbourne: Australian Council for Educational Research. Biggs, J. B. (1987). Study Process Questionnaire manual. Melbourne: Australian Council for Educational Research. Education Participation Scale Boshier, R. (1971). Motivational orientations of adult education participants: A factor analytic exploration of Houle's typology. Adult Education Journal 21 , 3-26. Dimensions of Self-Concept (DOSC) Caracosta, R., & Michael, W. B. (1986). The construct and concurrent validity of a measure of academic self-concept and one of locus of control for a sample of university students. Educational and Psychological Measurement 46, 735744. 238

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Activity Experience Report Chan, T. S. (1998). An experimental adaptation of the flow theory in studying motivation in computer-assisted instruction environment. Paper presented at the Annual meeting of the American Educational Research Association , April, 1998, Montreal, Canada. Purpose in Life Test Crumbaugh, J. C. & Maholick, L. T. (1981). Purpose in life test. Murfreesboro, TN: Psychometric Affiliates. Ontario Test of Intrinsic Motivation (OT/M) Day, H.I. (1969). A progress report on the development of a test of curiosity. Paper presented at the National Seminar on Adult Education Research, February 911, 1969, Toronto, Canada. (ERIC Document Reproduction Services No.ED 026610) Lifelong Learning Skills Scales Dunlap, 1. C. (1996). The relationship of problem-based learning to life-long learning. University of Colorado at Denver. Dissertation Abstracts International (DAI) 58 , 01A, 0071. Learning OrientationiGrade-Orientation (LOGO) Scale Eison, J. A. (1981). A new instrument for assessing students' orientations towards grades and learning. Psychological Reports 48,919-924. 239

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Aberdeen Academic Motivation Inventory Entwistle, N. J. (1968). Academic motivation and school attainment. The British Journal of Educational Psychology 38, 181-188. Student Attitudes Questionnaire Entwistle, N. J. & Entwistle, D. (1970). The relationships between personality, study methods, and academic performance. The British Journal of Educational Psychology 40, 132-143. Boredom Proneness Scale Farmer, R., & Sundberg, N. D. (1986). Boredom Proneness The development and correlates of a new scale. Joumal of Personality Assessment 50, 4-17. My Class Inventory Fisher, D. L. & Fraser, B . J . (1981). Validity and use ofthe My Class Inventory. Science Education 65, 145-156. Junior Index of Motivation (JIM Scale) Frymier, J. (1965). Junior Index of Motivation (JIM) Scale (TC004021). Princeton, NJ: Educational Testing Service. 240

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Change Seeker Index Garlington, W. K., & Shimota, H. E. (1964). The change seeker index: A measure of the need for variable stimulus input. Psychological Reports 14, 919-924. Typical Intellectual Engagement Scale Goff, M., & Ackerman, P. L. (1992). Personality Intelligence Relations: Assessment of Typical Intellectual Engagement. Journal of Educational Psychology 84, 537552. Children's Academic Intrinsic Motivation Inventory (CAIMI) Gottfried, A. E. (1982). Relationships between academic intrinsic motivation and anxiety in children and young adolescents. Journal of School Psychology 20, 205-215. Effective School Battery Gottfredson, G. D. (1986). Using the Effective School Battery in School Improvement and Effective Schools. Paper presented at the 67ili Annual Meeting of the American Educational Research Association (San Francisco, CA, April 16-20, 1986). (ERIC Document Reproduction Services No. ED 273 041) Self-Directed Learning Readiness Scales Guglielmino, L. (1977). Development of the self-directed learning readiness scale. University of Georgia. Dissertation Abstracts International 38, 6467 A. 241

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Intrinsic Enjoyment and Boredom Coping Scales Hamilton, J. A., Haier, R. l, & Buchsbaum, M. S. (1984). IntrinsiC enjoyment and boredom coping scales: Validation with personality, evoked potential and attention measures. Personality and Individual Differences 5, 183-193. Perceived Self Questionnaire (PSQ) Heath, D. H. (1968) . Growing up in college: Liberal education and maturity. San Francisco CA: Jossey-Bass. Learning Climate Inventory (LCI) Hoyle, J. R. (1973). Are open-space high schools more open? Journal of Educational Research 67, 153-156. Multidimensional Life Satisfaction Scale for Children Huebner, E. S. (1994). Preliminary Development and Validation of a Multidimensional Life Satisfaction Scale for Children. Psychological Assessment; 6, 149-158 Flow Scale Jackson, S. A., & Marsh , H. W . (1996). Development and validation ofa scale to measure optimal experience: The Flow State Scale. Journal of Sport & Exercise Psychology 18, 17-35 . 242

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Short Index of Self-Actualization Jones, A. & Crandall, R. (1986). Validation of a Short Index of Self-Actualization. Personality and Social Psychology Bulletin 12, 63-73. State Curiosity Scale or State Epistemic Curiosity Scale Leherissey, B. L. (1971). The development of a measure of state epistemic curiosity. (ERIC Document Reproduction Services No. ED 053 549) Styles of Living Preference Scale Maul, G., & Maul, T. (1986). Beyond limit: Ways to growth andfreedom. Glenwood, IL: Scott, Foresman and Co. Study Attitudes and Methods Survey (SAMS) Michael, W. B., Denny, B., Ireland-Galman, M., Michael, 1. J. (1986). The factorial validity of the Studies Attitudes and Methods Scale (SAMS). Educational and Psychological Measurement 45, 647-653. Melbourne Curiosity Inventory (MCI) Naylor, F. D. (1981). A state-trait curiosity inventory. Australian Psychologist 16, 172-183. Novelty Experiencing Scale Pearson, P. H. (1970). Relationships between global and specified measures of novelty seeking. Journal of Consulting and Clinical Psychology 34, 199-204. 243

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The Children's Reactive Curiosity Scale Penney, R. K., & McCann, B. (1964). The Children's Reactive Curiosity Scale. Psychological Reports 15, 323-334. Motivated Strategies/or Learning Questionnaire (MSLQ) Pintrich. P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A Manual/or the Use o/the Motivated Strategies/or Learning Questionnaire (MSLQ). Technical Report No. 91-B-004. Ann Arbor, MI: Regents of the University of Michigan. Inventory 0/ Learning Processes Schmeck, R. R., & Ribich, F. D. (1977). Development of a self-report inventory for assessing individual differences in learning processes. Applied Psychological Measurement 1, 413-431. Orientation to Learning Scale Shapiro, S. A. (1985). Orientation to learning (ETS 015412). Princeton, NJ: Test Collection, Educational Testing Service. Learning Activities Survey Sheffield, S. B. (1964). The orientations of adult continuing learners. In D. Solomon (Ed.), The continuing learner, pp. 1-22, 65-78. Chicago: Center for the Study of Liberal Education for Adults. 244

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Classroom Environment Scale Trickett, E. J., & Moos, R. H. (1973). Social Environment of Junior High and High School Classrooms. Journal of Educational Psychology; 65, 1,93-102 Semantic Differential for Attitudes towards, School, Self, Learning, Teachers, etc. Wilson, F. S., Langevin, R., & Stuckey, T. (1972). Are pupils in the open plan school different? Journal of Educational Research 66, 115-118. Sensation Seeking Scale Zuckerman, M., Kolin, E. A., Zoob, I. (1964). Development of a sensation-seeking scale. Journal of Consulting Psychology 28,477-482. Readings Bronzaft, A. L. (1996). Top of the class: Guiding children along the smart path to happiness. Norwood, NJ: Ablex Publishing. Csikszentrnihalyi, M. (1996). Creativity: Flow and the psychology of discovery and invention. New York: Harper Collins Csikszentrnihalyi, M. (1999). If we are so rich, why aren't we happy? American Psychologist 54,821-827. Houle, C. (1961). The inquiring mind. Madison, WI: University of Wisconsin Press. Scitovsky, T. (1992). Thejoyless economy: The psychology of human satisfaction. New York: Oxford University Press. 245

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Suchman, J. R. (1971). Motivation inherent in the pursuit of meaning: Or the desire to inquire. In H. I. Day, D. E. Berlyne, & D. E. Hunt (Eds.), Intrinsic motivation: A new direction in education (pp. 61-72). Minneapolis MN: Mine. Tough, A. (1969). Why adults learn: A study of the major reasons for beginning and continuing a learning project. Paper presented at the National Seminar on Adult Education Research, Toronto, Canada. (ERIC Document Reproduction Services No. ED 025 688) Love of learning items generated in two graduate level tests and measurements classes, Summer, Fall 1999 246

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