Doctoral success?

Material Information

Doctoral success? negotiating a field of practice
Miller, Candice L
Publication Date:
Physical Description:
xvii, 361 leaves : ; 28 cm

Thesis/Dissertation Information

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:
Muth, Rodney
Committee Members:
LeCompte, Margaret D.
Golde, Chris
Ruiz-Primo, Maria Araceli


Subjects / Keywords:
Doctor of philosophy degree ( lcsh )
Academic achievement ( lcsh )
College dropouts -- Prevention ( lcsh )
Academic achievement ( fast )
College dropouts -- Prevention ( fast )
Doctor of philosophy degree ( fast )
bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )


Includes bibliographical references (leaves 354-361).
General Note:
School of Education and Human Development
Statement of Responsibility:
by Candice L. Miller.

Record Information

Source Institution:
|University of Colorado Denver
Holding Location:
|Auraria Library
Rights Management:
All applicable rights reserved by the source institution and holding location.
Resource Identifier:
435528817 ( OCLC )
LD1193.E3 2009d M54 ( lcc )

Full Text
Candice L. Miller
B.A., University of Colorado, Boulder, 1970
M.A., University of Colorado Denver, 1996
A thesis submitted to the
University of Colorado Denver
in partial fulfillment
of the requirements for the degree of
Doctor of Philosophy
Educational Leadership and Innovation

Copyright 2009 by Candice L. Miller
All rights reserved.

This thesis for the Doctor of Philosophy
degree by
Candice L. Miller
has been approved
tvfaj /r, f

Miller, Candice L. (Ph.D., Educational Leadership and Innovation)
Doctoral Success? Negotiating a Field of Practice
Thesis directed by Professor Rodney Muth
Across all disciplines, approximately one-half of American doctoral students
drop out before completing their degree. This issue entered center stage of the
national higher educational community in the 1990s and remains there, under scrutiny
from the Council of Graduate Schools, the Carnegie Foundation, and the National
Research Council (NRC), among others. As the issue of PhD departure is
idiosyncratic by individual, discipline, and site, the NRC recommended (1996) that
the research on doctoral students be conducted accordingly.
This study follows the NRCs recommendation, focusing on two doctoral
disciplines at one site to determine what builds student success in doctoral programs.
Research questions related directly to what facilitated and what hindered PhD student
success as well as what barriers might be reduced and how the program might be
improved to facilitate doctoral-student success. Methods involved observation, field
notes, and face-to-face interviews with 24 post-coursework PhD students, nine
graduate faculty, and two graduate staff. Additional data included PhD program-
completion information and various program documents.

I created and developed a conceptual framework based on the scholarship of
Pierre Bourdieu (student success is related to social and cultural capital), the socio-
cultural writings of Lev Vygotsky (students move through the zone of proximal
development), and the work of Lave and Wenger (students move from legitimate
peripheral participation to full participation in a scholarly community). In short,
students are transformed from novice to expert when their learning is assisted and
scaffolded by experts and by more capable peers.
Findings indicate that a programmatic culture of successincluding a pre-
screened matching of student applicants with faculty advisorsserved to facilitate
students moving through the PhD process. Another finding indicates that criteria for
student benchmarks and expectations need to be more explicit for all students to have
a level playing field. These findings suggest future studies, including doctoral-student
assessment and PhD benchmark development.
This abstract accurately represents the content of the candidates thesis. I recommend
its publication.
Rodney Muth

This work is dedicated to those who have earned a PhD and to those who attempted to
earn one but were unable to decipher the signposts in order to do so.

It is now clear to me why it requires a committee to complete a dissertation:
The process is simply too complex for one individual to navigate. I acknowledge my
entire committee for their commitment to improve American PhD education.
Academically, I am grateful for the insights and guidance of my committee members
Rodney Muth, Margaret D. LeCompte, Chris M. Golde, and Ayita Ruiz-Primo. As
well, I appreciate their patience with me while I sought to (and did) create a
conceptual framework and a process model for PhD education. Specifically, I
acknowledge Margarets (Markis) continual and collegial encouragement,
comments, and wisdom, all of which gave me direction and gave me motivation to
continue. Also, I thank Chris Golde for her leadership in the field of PhD completion
and non-completion, as it served to inspire me to work on a problem that I felt
mattered, but Chris led the way. I learned a great deal from the candid feedback that
Rod and Ayita gave me and the faith that they had in me. Thank you, Rod, for taking
me on.
To the students, the faculty, and the staff who willingly participated in my
study, I am deeply grateful. With piles of work and multiple academic challenges on
their own desks, these individuals jumped at the invitation to participate in my
dissertation study, then participated fully. The high quality of their engagement with
this topic allowed me to produce a better study.

This doctorate would never have been completed without the devoted support
of my husband. Kevin, whose steadfast confidence in me, strength, advice, and
doctoral experience contributed to my intellectual growth. Without the long-term,
loving support and inspiration from my mother (Darlene Miller) and my father (Alan
Miller), I would not have had the persistence to complete this PhD. I acknowledge
them with some sadness, as both of them passed away during my PhD journey.
Stalwart support also came regularly from my nieces Petra and Jana Miller (and their
parents Karen and Gregg Miller), as well as my dear friends Sussanna, Mary Ann,
Maureen, Chris, and Dona.
Additionally, colleagues in my PhD cohort and elsewhere often served as
mentors. Barbara Lovitts work, related to making the implicit explicit in PhD
education, gave me not only a pilot study in which to participate and an opportunity
to contribute to one of her book chapters, but she also gave me faith in myself so that
I could take the PhD one step at a time and earn the three magic letters. Barbara and I
have become friends, which further supports me in my work.
Finally, my two years of semi-retirement, which I took so that I could focus
full-time on my dissertation, were essential to my being able to finish it. It was
precious time indeed, during which time my constant companion, Nicky, contributed

Figures......................................................... xv
Tables.......................................................... xvi
1 RESEARCH FOCUS.................................................1
Significance of the Study................................. 1
Some History................................................2
A Look to the Past.......................................3
Indicators of Urgency....................................5
Competition and Research Productivity....................9
Approaching the Problem....................................13
2 FRAMEWORK AND EXPLANATORY MODEL...............................17
A Guiding Metaphor.........................................17
Problem Statement.......................................18
Central PhD Completion Issues..............................19
What is the Nature of a PhD?............................20
What Contributes to a Clearer Understanding
of the Nature of a PhD?.................................26
The CGS Completion-Attrition Kaleidoscope..................33

Elements of the CGS Kaleidoscope............................34
Critique of the CGS Kaleidoscope............................36
Conceptual Framework Student Progress through a PhD Program...40
Introduction to My Conceptual Framework.....................41
My Program Process Model.......................................50
Explicit Elements...........................................51
Implicit Elements...........................................52
3 METHODS............................................................62
Research Questions and Hypotheses..............................62
Research Questions..........................................63
Four Hypotheses.............................................64
Pilot Studies and Study Design.................................68
Two Pilot Studies...........................................68
Case-Study Design...........................................69
Site Selection.................................................70
Data Collection................................................74
Participant Selection.......................................78
Data Organization...........................................84

Data Analysis..................................................91
Identifying Patterns and Structures.........................91
Study Limitations..............................................99
4 GEOGRAPHY CASE....................................................101
Themes, Framework, and Model Revisited........................101
Findings and the Framework.................................101
Findings and the Model.....................................102
The Geography Program: Structure and Culture..................103
The Physical and Curricular Structure......................103
Program Structure: The Explicit Structure..................104
The Implicit Programmatic Culture..........................123
Culture: The Disciplinary Environment......................124
Expectations for Success...................................129
What Most Facilitated Success?................................135
What Hindered Geography PhD Student Success?...............145
Disillusionment and Alienation.............................149
Faculty Responses..........................................154
Facilitators and Hindrances Revisited.........................158
Student and Faculty Responses Overlap......................158
Facilitators and Hindrances of Success.....................160

Making the Implicit Explicit..............................161
Program Improvement.......................................162
Closing Remarks..............................................166
5 POLITICAL SCIENCE CASE...........................................169
Themes, Framework, and Model Revisited.......................169
The Explicit Program Structure............................170
Findings and the Conceptual Framework.....................174
The Political Science Program: Explicit Structure
and Implicit Culture.........................................176
The Explicit Structure....................................176
Program Curriculum........................................186
What Facilitates Student Success?.........................195
The Implicit Program Culture..............................206
Student Expectations of the Program.......................210
Desire for a PhD..........................................218
What Hinders Doctoral Student Success?....................235
Transformation of Student Learning........................250
Program Improvement.......................................251
Closing Remarks..............................................258
AND POLITICAL SCIENCE............................................260
Review of Methods and Questions..............................260
Case Study Findings Inform Revised Framework and Model.......261

Program Culture of Success..............................265
Program Structure of Success............................268
Transformation from Novice to Expert....................279
Unexpected Findings.....................................286
Program Improvement.........................................291
Need for Heightened Transparency........................292
Case-Study Analysis: What I Learned.........................298
Faculty and Staff.......................................303
Conclusions............................................... 304
What Facilitates PhD Student Success: Conclusions...........307
Revised Framework.......................................307
The Program.................................................308
The Student.................................................313
Social, Academic, and Adaptive Learning.................315
Implications for Prospective Students...................317
Implications for Doctoral Programs and Departments......320

Implications for Faculty Advisors.........................326
Institutional Program Elements............................326
An Ideal PhD Program......................................330
Redundant Reinforcements Enhance Doctoral Student Success... 333
My Contributions to the Research on Students Perspectives
of PhD Education............................................338
Doctoral Student Success? Negotiating a Field of Practice.339
A STUDENT INTERVIEW GUIDE........................................342
B LETTER TO STUDENTS.............................................348
C INTERVIEW TRACKING MATRIX......................................349
D DATA COLLECTION MATRIX.........................................350
E FACULTY INTERVIEW GUIDE........................................352

2.1 The CGS PhD Completion-Attrition Kaleidoscope........................34
2.2 My Conceptual Framework..............................................43
2.3 A Program Process Model..............................................51
7.1 The Original Conceptual Framework...................................309
7.2 Revised Conceptual Framework for PhD Student Success................310
7.3 A Learning Process Model for PhD Student Success....................312
7.4 PhD Student Success: Relational Elements............................329

3.1 Research Questions with Purpose.........................................73
3.2 Data and Evidence: Sources and Collection Methods.......................75
3.3 Faculty and Staff Interviewed...........................................83
3.4 Department of Geography Student Participants Overview (N = 9)...........87
3.5 Department of Political Science Participants Overview (N = 15)..........90
3.6 Data (Items) Merge into Themes and Categories...........................98
4.1 Geography Doctoral Student Cohort Tracking.............................123
4.2 What Facilitates Success?............................................ 141
4.3 Students Coping Strategies...........................................144
4.4 Obstacles: Types and How Participants Overcame Them....................146
4.5 Faculty Perspectives About What Facilitates and What Hinders Student
4.6 Geography Research Questions and Findings..............................161
5.1 Clusters of Student Characteristics....................................183
5.2 Students by Stages.....................................................184
5.3 Case-study Students Career Plans by Gender...........................195
5.4 What Facilitates Doctoral Student Success?.............................197
5.5 Political Science Research Questions and Findings......................201
5.6 Motivations for Earning a PhD..........................................223

5.7 Strategies for Doctoral Student Success............................225
5.8 Hindrances Clustered...............................................236
5.9 What Hinders Doctoral Student Success?.............................240
5.10 Overcoming Obstacles...............................................249
6.1 Cross-Case Study Findings: Salient Facilitators of PhD Student Success... 263

In this chapter, I review the problem of American PhD non-completion, the
significance and costs of the problem, my dissertation focus and motivation, and how
I approach the problem. Looking through the lenses of both PhD student and faculty
perspectives, the overall purpose of this study is to identify what facilitates and what
hinders student success by examining educational processes because that aspect of
doctoral education is under-researched (Golde, 2001; Lovitts, 2001). Throughout, I
seek to identify common themes that might contribute to the national discussion
related to doctoral education: Why do nearly half of our PhD students not graduate?
What program improvements might be made to facilitate their success?
Significance of the Study
This study examines what facilitates and what hinders doctoral student
success primarily from a student perspective because this perspective is mostly
ignored (Golde, 2001; Lovitts, 2001). When a PhD student flounders or drops out,
significant resources can be wastedthose of the institution, those of the faculty, and
those of the students because extensive resources go into educating and training each
doctoral student. Inasmuch as each doctoral student consumes resources both in terms
of faculty/advisor expertise, student time, and tuition and stipend costs (Bowen &
Rudenstine, 1992; Lovitts, 2001), a 50% average completion rate cannot be justified

if the institutional intention is to graduate students. Causes for such high rates of non-
completion are not well known or are unknown.
This study is significant for seven reasons. First, it adds to the knowledge
related to discipline-specific and institution-specific data around PhD student
completion, following the NRC (1996) mandate that calls for better data at these
levels. Second, it adds to the dearth of literature from a student perspective. Third, it
comes at a time when calls for higher PhD completion rates are emanating from
institutional and national sectors such as the Council of Graduate Schools (CGS,
2004). Fourth, it contributes to the literature around the necessity for programmatic
transparency and reinforces previous literature in this regard (CGS, 2004; Lovitts,
2001, 2007; National Research Council, 1996). Fifth, findings resulted in a new
perspective in terms of understanding the PhD: as a process over time, resulting in a
Learning Process Model for Student Success, as presented and discussed in Chapter
7. Sixth, this study raises new questions around what characterizes a good doctoral
student and what characterizes a good advisorissues that are under-researched
(Golde & Dore, 2001; Lovitts, 2001) in the context of PhD student completion.
Seventh, this study identifies characteristics of a program culture and structure of
success, providing suggestions for improvements that other programs might consider.
Some History
In 1996, the Office of Scientific and Engineering Personnel/National Research
Council (OSEP/NRC, henceforth the NRC) recommended that PhD non-

completion research be discipline- and institution-specific so that scholarship can
eventually describe broad aspects of the non-completion phenomenon. As more data
contribute to understanding comparably-sized and structured institutions, studies can
build one upon another. Further, when comparative measurements become
increasingly transparent and standardized, it may be possible for institutional
administrators/leaders to identify models for reducing doctoral student departure that
could be replicated at other sites. Thus, implementing effective models (Givres &
Wemmerus, 1988) may increase completion rates over time across a range of
institutions. In so doing, institutional, faculty, staff, and student resources could be
leveraged more effectively. Following the NRC recommendation, then, this study
contributes disciplinary data and may help researchers and program leaders
understand issues around PhD completion and non-completion.
A Look to the Past
In 1861, the first American student received an American doctorate in the
United States (Golde & Walker, 2006). Previously, all doctorate-seeking students had
studied and received their Doctors of Philosophy in Europe, most frequently in
Germany. Fast-forward to the 21st century, whenaccording to the Council of
Graduate Schools (CGS, 2004), the national association for graduate schoolstens of
thousands complete their doctorate each year in the U.S. Preparing PhD students is, in
essence, preparing them for research and teaching as future faculty, as most will take
places in the academy (Bowen & Rudenstine, 1992). What happens or does not

happen to PhD students during their programs is valuable information for American
universities because current PhDsif they graduatemay guide future generations
Of all graduate degrees awarded in the United States, 90% of them are
masters degrees (CGS, 2004). While masters degree completion does not appear to
be a major issue for graduate educators nationwide, non-completion of doctoral
degrees is (Lovitts, 2001). Averaged across all disciplines, approximately 50% of
those who seek American doctoral degrees in this country do not complete them
(Lovitts, 2001; NRC, 1996). Completion rates for some disciplines average as low as
30+%, and other disciplines average as high as nearly 65% (2001, 1996).
By themselves, these statistics mean little. However, in the context of growing
concerns about the value of graduate education in this country, these statistics mean a
great deal. The issue of high rates of non-completion in doctoral education is a topic
of concern for entities such as the PhD Re-Envisioning Project of the Woodrow
Wilson Foundation, the National Research Council (NRC, 1996; Ostriker & Kuh,
2003; Stewart, 2007), the Pew Charitable Trusts (Golde & Dore, 2004), and the CGS
(2004), the national council for graduate deans and senior administrators, both public
and private. Such growing concern suggests that the issue of non-completion grows
increasingly urgent.

Indicators of Urgency
Several indicators strongly suggest that low completion rates must be
addressed quickly and rigorously. First, the United States graduates an average of
50% of the talented individuals who begin the doctorate (Bowen & Rudenstine,1992;
Lovitts, 2001). Second, Western Europe, Australia, and China are developing
educational infrastructures that will serve their people at the doctoral level in
competition with the United States (CGS, 2004). Third, the Mantova Proclamation
(2003) declares that western Europe will develop graduate degrees (both masters and
doctoral) that are portable among countries in order to compete rigorously with the
United States by 2010.
In a CGS (2005, pp. 1-2) quarterly publication, significance of non-
completion is expressed in terms of decline in the United States pre-eminence in
research leadership, as measured by research funding awarded, innovations such as
patents and transfer technology applications, and research productivity. According to
the CGS, if American research productivity is compromised, the pre-eminence of
American research may decline.
Borkowski (2006) states that, while researchers have conducted studies on
attrition and completion over the past 40-50 years, no complete agreement exists on
either the definitions of attrition and completion or on the methodology appropriate to
study for measurement. During the early years of the 21st century, however, PhD
completion began moving closer to center stage in graduate education. Increasingly,

one sees calls for action, asking for a better understanding of and accountability for
the educational elements that give rise to such low completion (Borkowski).
Evidence for renewed attention to doctoral education in the 1990s could be
found in research ranging from preparing future faculty initiatives (Stewart, 2007)
resulting in a national movement followed that is now referred to as PFFto
studies that examined the number of American earned doctorates and time-to-degree
including doctoral student satisfaction (Zhao, Golde, & McCormick, 2005), to
surveys of doctoral students on a variety of topics such as the mismatch between
student expectations for a PhD and the reality of earning one (Golde & Dore, 2001),
to the nature of doctoral programs in disciplinary contexts (Bowen & Rudenstine,
1992; Lovitts, 2001). Regardless of the specific focus, nearly absent from these
publications are the voices of doctoral student related to their own experiences (Golde
& Dore, 2004).
Calls for Action to Re-envision, Review, Revise, and Restructure
In the late1990s and early 21st century, non-completion of the doctorate
surfaced (Lovitts, 2001; NRC, 1996) as a major topic for discussion at the national
CGS meetings from 2003 through and including 2007, followed by a brief, 25-page
publication CGS (2004). It developed out of a CGS white paper, which acknowledged
concerns around and a commitment to improving our knowledge of factors that are
most strongly coupled with low PhD completion rates and to providing model
interventions that can reduce attrition and increase completion (p. v). Another recent

study on completion/non-completion (Nettles & Millett, 2006) reviews findings of a
ten-year study on doctoral completion and non-completion. A salient finding was that
doctoral student perceptions of their interactions with faculty (teaching, access,
advising, and interest in students) are paramount in students making progress.
According to Golde and Dore (2004), as was the case in doctoral education
after World War II and again in the 1960s, heightened interest signaled a time of
stress and change within doctoral education. The increased interest in the past 15
years (Carnegie Perspectives, 2005; Cohen & Cherwitz, 2006; LaPidus, 2000), then,
may signal another cycle of stress and change.
One such call for action was Ernest Boyers (1990) groundbreaking special
report on reconsidering scholarship. It served as a turning point and called into
question much about PhD education that had been taken for granted. Boyer stated that
he wrote this report in part because of the profound educational and social changes
that had occurred in America in the last 350 years. Because of these changes, he
questioned issues of relevance related to the PhD when he asked,
Can Americas colleges and universities, with all the richness of their
resources, be of greater service to the nation and the world? Can we
define scholarship in ways that respond more adequately to the urgent
new realities both within the academy and beyond? (p. 3)
Recent research (Golde & Dore, 2001; NRC, 1996) indicates thatbecause of
non-comparability across institutions on this topicinternal institutional research
must be done that is both institution-specific and discipline-specific. Beginning in

1956, The Survey of Earned Doctorates (SED) has produced annual data related to
doctoral completion. However, while this information adds to our understanding in
terms of numbers of degrees completed, it does not add to our understanding of
completion rates for two reasons: (a) Information does not exist on how many
students left and (b) few institutions track these data (NRC, 1996). Discussion has
been lively about how the original number of students, cohorts, and transfers could be
calculated, but no consensus exists on how to classify and calculate total number of
students lost to the systems (Bowen & Rudenstine, 1992; Nerad & Miller, 1996;
Nerad, 2004).
Increased Call for PhD Assessment
One aspect of attention to doctoral education that has emerged recently is
doctoral assessment, with good reason, as Maki and Borkowski emphasized (2006):
Regional accreditors of graduate programs and even some state
legislatures in the United States are beginning to accord greater weight
to such measures in the assessment of doctoral programs, as the wave
of accountability that has already hit the shores of primary and
secondary education is just now reaching the shores of doctoral
education. Increasingly, pressure is being brought to bear on research
institutions to demonstrate that PhD students are learning, to
demonstrate accountability in terms of PhD outcomes, and to graduate
students in a timely fashion, (p. xii)
Examples of recent outcries for urgent change needed in PhD education in
higher education also range from the Woodrow Wilson Re-Envisioning the PhD
Project, to the Carnegie Foundation through the Carnegie Initiative on the Doctorate

(Golde & Walker, 2006) and to the Council of Graduate Schools call for an
overhaul of doctoral education.
Competition and Research Productivity
Calls for urgent change also result from increasing competition from
elsewhere. For example, forty-five European countries have signed The Mantova
Proclamation (2003), made possible by the consolidation of Western Europes
currency and enhanced multilateral diplomacy. Signed in 1999, the proclamation
allows graduate-degree portability among countries, such that a student could earn a
masters in Italy, for example, and continue a doctoral degree in Germany. A student
could also transfer standardized credits from one institution to another. In writing and
presenting to national audiences (CGS, 2004), the leaders of this initiative have made
it clear that they intend this system to be able to compete rigorously with the United
States for the best and the brightest students by 2010 (Mantova Seminar
Proceedings, 2003).
Given that global preeminence in research (CGS, 2004) may be at stake, one
would expect this issue to be thoroughly researched and documented. However, the
bad news is that non-completion is not well documented from the students
perspectives, from an opportunity/cost perspective, or from specific institutional
perspectives for the most part, although the frequency and number of publications on
doctoral completion issues are growing (Nyquist, 2002; Tinto, 1993).

Resources and Costs
In measuring the effectiveness of higher education nationwide, tying the
investment of resources to learning outcomes is increasingly discussed (Borkowski,
2006). Because resources to public higher education are diminishing, more attention
is being paid to what students, parents, and funding agencies receive for their dollars
and for their (or their childrens) degrees.
Costs of student departure. What are the costs of doctoral students departing
their studies? When a student drops out of their PhD programwhich nearly one-
third do in their first year (Bowen & Rudenstine, 1992; Golde, 1996)resources
related to admissions and first-year programmatic efforts are wasted. Demands for
making realistic estimates of the costsboth human and financialcan be found in
recent literature, as will be explored further in Chapter 2, which implicates a failure in
higher education to provide cultures for learning that maximize student success.
Kenneth Pruitt (2006), for example, states that, When goals are and incentives are
misaligned, a prime suspect is leadership failure (p. 24).
No national study or database synthesizes the total cost of doctoral students
departing their studies, expressed either in dollars and/or time (Bowen & Rudenstine,
1992; Golde & Dore, 2004; NRC, 1996). I need only to review my own doctoral
student process to recall the total cost to me in terms of both dollars and time. While
the net time (minus two stop-outs) for my doctoral journey required less than the
median time of 8.9 years for the completion of an American PhD (Lovitts, 2007), the

opportunity costs for completing my PhD will have been high. For example, time
spent on elder care and ultimately dealing with extensive paperwork related to the
passing of both of my parents, selecting a new topic and completing a second
literature search, replacing two committee members, and taking two years of semi-
retirement in order to complete the dissertation all took a toll on me in terms of
dollars, fatigue, and frustrations. Multiply my experience by hundreds or thousands of
individuals, and the tally would represent high costs indeed. Many students simply
cannot afford the extended time, manage the external circumstances, or have the
support that I have had. In this light, it may not be a surprise that only an average of
50% of students across the disciplines complete their PhDs.
Total costs to higher education (and ultimately the society at large) remain
invisible to this day (Nettles & Millett, 2006), as they remain undefined in terms of
lost human effort, undocumented in terms of reasons for departure and numbers of
non-completers, and unmeasured in terms of the financial resources wasted both
among the institutions and among the non-completers. As researchers from the NRC
(1996) tell us,
There are no national estimates to tell us how many students make the
decision each year to cease graduate work.... Reliable estimates of
graduate attrition are in the national interest because of their potential
to reduce the waste inherent in the premature departure of talented
individuals from advanced preparation in the sciences and humanities.
(p. vii)

Further, while no formal meta-study has been conducted on how non-
completion affects former students psychologically, Lovitts (2001) discusses the
apparent cost to the student in terms of disillusionment, anger, regret, and loss of
confidence, although these costs were not the focus of her study. The psychological
cost to doctoral students who do not complete and the impact(s) the departures may
have on the remainder of their lives is almost entirely unaddressed (Golde & Dore,
2004; Lovitts).
Systematically unaddressed. The message from current research and the
accelerating trend to identify specific causes of American doctoral non-completion
are clear: The problem has been known for nearly 45 years and not addressed in part
because it is invisible (Lovitts, 2001). As well, it has been unaddressed among
scholars in a systematic way (Bowen & Rudenstine, 1992) in part because of the
difficult conceptual and empirical issues related to completion and non-completion, in
part because data collection systems are not designed to collect such data, in part
because of disciplinary differences, and in part because attrition itself has not been
well defined. With previous studies sporadic and not comparable in terms of
measuring loss of research productivity, costs, time to degree, dropping
out/graduation by discipline, it is now clear that identifying comparable measures
among American institutions and disciplines is critical to having a consensus on valid
measurements of non-completion, although it will be a difficult and complex process
to accomplish (Bowen and Rudenstine: NRC, 1996).

Lovitts (2001) argues that students continue to leave their programs in high
numbers because universities have focused on student characteristics for admission
rather than on program culture and structure. Her findings show that entering
academic ability is not a predictor of completion, including for those entering with
low GRE scores. She concludes that this disconnection indicates that "criteria
currently in place to select students based on academic achievement are not good
predictors of success (p. 37).
As will be made clear in Chapter 2, some investigations are underway.
However, it is not yet clear whether current research will include in-depth
examinations of doctoral student successes and departures from the students
Approaching the Problem
How students experience a PhD and their related perspectives are a missing
link in the PhD completion literature (Lovitts, 2001; Golde, 1996). In order to
understand how students encounter and navigate a PhD, a better understanding of the
elements of a doctoral process may be helpful. For example, a clear understanding of
how students integrate socially, culturally, and intellectually into their academic
communities might be one way to examine the process. To do that, we must hear
from the students themselves.

Student Success
Student success emerges from student involvement in the discourse around
PhD education, which requires an orientation not only to intellectual craftsmanship
(Mills, 1959) but also to social and cultural skills (Rogoff, 1990). Where does a
student learn how to navigate the complexities of a doctoral program if a student is
not immersed and socialized in the context? Part of the educational process, then,
could involve not only a higher order kind of thinking (Donald, 2002), but also a
more sophisticated orientation, involvement, and guidance related to academic,
social, and cultural awareness. By immersion and guidance, then, students may be
enabled to interpret socio-cultural meanings (Geertz, 1973), allowing them to be full
participants (Lave & Wenger, 1991) in doctoral learning communities.
A Socio-Cultural Approach
Learning is a social endeavor and does not as traditionally argued occur in the
mind alone (Lave & Wenger, 1991). Rather, learning occurs through participation
with other learners and experts, according to Lave and Wenger. Because a student
moves from the role of novice to that of expert through co-participation with experts
and/or more capable peers (Vygotsky, 1978), the path to the PhD grows visible and
can be navigated successfully through increasingly full participation in a disciplinary
learning community.
Cultural contexts. I selected a socio-cultural approach for my research
because acquiring a PhD involves a complex learning process that occurs within

multiple, interactive cultural contexts. A socio-cultural approach examines
relationships between human action on the one hand and the cultural, institutional,
and historical situations, in which [actions] occur, on the other (Wertsch, Del Rio, &
Alvarez, 1995, p. 11), with human action as the unit of analysis. In the case of
doctoral education, then, socio-cultural practice occurs at the intersection of the
activity of the student and the mediation of the mentor and advisors. That is, activities
of a culture provide a prototype of a culture (Bruner, 1996, p. 151), which students
must integrate to become members of their chosen culture. They must learn to know
by learning to do as it is appropriate within their disciplinary culture (Donald, 1997;
Hawley, 1993). To succeed, a PhD student must have a depth and breadth of
knowledge in a particular domain (Bowen & Rudenstine, 1992; CGS, 2004).
A Student Perspective
Students are the best judges of their own learning experiences. Because of
this, I approached the problem of completion/non-completion of the doctorate by
looking primarily at students perspectives in two doctoral programs at one
Students may provide new insights. Based on understanding these experiences
across two programs, student views, experiences, and preferences might suggest ways
to re-envision and re-structure doctoral processes. By allowing students to talk about
their own educational processes, it may be possible to gain insight into what is
effective and what might be more effective in doctoral education (Lovitts, 2001).

Gaining these insights may eventually provide bases for conserving resources and
increasing completion rates. Said another way, it may allow more students to succeed
in reaching their goal of earning a PhD.
Components of social learning. What are the components of social learning
that could help scholars better understand why students leave and why they remain in
their programs? In this study, I seek to understand aspects of completion and non-
completion from a socio-cultural perspective (Bourdieu, 1977; Bruner, 1996) from
the student perspective.
This study focuses on the process of the PhD as seen primarily through the
experiences and observations of the students themselves. Because so little is written
about the social and cultural aspects related to completion, especially from the student
perspective, I address these perspectives in my study. In Chapter 2,1 discuss the
socio-cultural concepts that inform the completion/non-completion literature, along
with some lessons learned from recent relevant studies.

Although no hard core data exist around PhD student completion (NRC,
1996), the overall national rate of PhD completion is estimated at 50 percent (Lovitts,
2001). Breneman (1977) compares PhD attrition rates with those of professional
schools, when he states that a 50 percent attrition rates would be a scandal in any
professional school, but seem to be accepted in doctoral education as part of the
natural order (p. 18). According to CGS President Debra Stewart (CGS, 2004), the
most urgent issue related to American PhD reform revolves around successfully
graduating high numbers of students that programs admit and being able to
demonstrate outcomes. While she did not state an optimal number of PhDs that might
be graduated, she stated that the CGS membership is committed to understanding
factors related to low PhD completion rates and to providing model interventions
that can reduce attrition and increase completion. Although non-completion issues are
otherwise treated sporadically in the literature, several highly relevant studies
informed this study.
A Guiding Metaphor
When a student enters a doctoral program, he or she engages in learning
through interacting with others in a particular settinga particular culture and
structure. The structure and culture may be murky, and this lack of transparency may

hinder a students success. Consider a guiding metaphor: that of a PhD student (call
her Paula) driving a car. Paula has a destination in mind and, in order to arrive safely
at the destination in a timely fashion, she must observe and understand the signposts
along the way. As well, she must understand the language in which they are written.
If, for example, she is traveling in Mexico and she does not understand that salida
means exit in Spanish, she may miss her turnoff. If she understands the language,
observes and understands the explicit signposts, she should follow appropriate
directions and get to her destination.
Problem Statement
While each students process toward the PhD is idiosyncratic, each student
must navigate many cultural and structural elements to succeed and earn the three
magic letters (Nettles & Millett, 2006). In order for higher numbers of PhD students
to succeed, processes around earning a PhD must be better understood.
The data reveal that many seem to have entered the pursuit of the
doctorate blindly. Once enrolled, many appear to receive little
guidance about how to navigate the process. Key features that are
critical to their success remain murky to them throughout their time in
graduate school. (Golde & Dore, 2001, p. 29)
Back to Paula. Paula must understand the norms of the activity, such as the
rules of engagement, driving rules, and laws in order to navigate successfully toward
her goal. She must learn to understand the nature of a process. Rather than simply
understanding that Paula drives from one point to another, I wanted to understand the
process that she undertakes as she drives to her destination. Likewise with a PhD

student. When a student enters a doctoral program, a student begins interacting with
the constraints of practices and expectations related to a PhD program and either
learns to navigate them or not. Part of learning to navigate them is learning that a PhD
is a process. Thus, learning the rules of the road in doctoral education is essential to
understand the doctoral process and reaching a PhD destination.
Central PhD Completion Issues
Most studies on PhD student attrition consist of input-output analysis of
institutional and/or student characteristics, most often attempting to identify what
characteristics are causal (usually blameworthy) in student departure (Lovitts, 2001).
They do not examine the social and cultural complexities of dissertation learning and
scholarly development, which my dissertation addresses. In order to examine doctoral
student success (or not) with my framework and model, I sought out anthropological
research, such as Bourdieus (1977), and sociological research, such as Goffmans
(1959). These served me well to better understand the socio-cultural dynamics
inherent in doctoral education.
Findings of this study are consistent with the completion/attrition literature in
terms of the critical nature of the advisor-advisee, mentor/mentee relationship.
Rather, much research supports its importance and criticality (OSEP/NRC, 1996;
CGS, 2004; Golde, 1998; Golde & Dore, 2004; Lovitts, 2001; Nettles & Millett,
2006). While studying this problem, it became clear that my research could not
provide a next building-block to the extant research for several reasons because a

research foundation was not in place. However, several relevant touchstones provided
a pathway (albeit not well trodden) and thus a direction for investigating PhD
completion issues. I learned that students do not understand the nature of a PhD in
many cases. Said another way, a PhD process is not transparent to prospective
What is the Nature of a PhD?
How one views education, professed or otherwise, Bruner (1996) notes, is a
function of how one conceives of the culture and its aims. Examining PhD education
is a way of understanding how American Academe reproduces itself by training
future faculty members and by socializing them for purposes of training and research
(Golde, 1996) in a field of practice. From my reading, I identified four issues: (a)
students are unclear about what a PhD is (Golde & Dore, 2001; Golde, 2004), (b)
student expectations and program expectations are often mismatched (Golde & Dore,
Hawley, 1993), (c) PhD non-completion is an invisible problem (Lovitts, 2001), and
(d) the lack of transparency in the PhD process hinders student success (Lovitts,
2001; 2007). Reviewing these four issues, it is not surprising that students may not
understand well the nature and process of a PhD.
As Bourdieu (1977) notes, education across all grades is designed to sort
students at higher and higher levels based on norms, behaviors, and assumptions of
the dominant culture. Bourdieu also states that students are sorted systematically from
the day that they enter elementary school. Further, he states that members of the

dominant culture are the ones who accrue the benefits of the system, as it was created
by the dominant culture. Thus, students who have been reared within the context of
the dominant culture may better understand how to fit seamlessly into the
expectations of that culture orin this case, the universitythan those who have not
been reared within that culture. Because the educational system is designed to
reproduce the value of the dominant groups culture (Bourdieu) in order to retain
power (Freire, 2000), marginalized groups, that is, members of non-dominant
cultures, may not succeed.
Central to the notion that programs reflect and reproduce the dominant culture
is the notion that the culture shapes the mind and the mind shapes the culture as a
continual, recursive process (Wertsch, 1998). Because educational institutions and
practices reflect the respective culture within which they are situated (Bruner, 1996),
it is the function of education to reproduce the culture that supports itnot only
reproduce it, but further its economic, political, and cultural ends (p. 67). Further, it
is the dominant culture that shapes how institutions come to exist and operate, and
how they organize departments and programs (Bourdieu, 1977), and those reflect
both the disciplinary culture and the culture at large (Donald, 2002). Thus, PhD
education shapes a student and, when the student emerges and becomes a member of
the academic community, that individual then repeats the cycle (Bruner, 1996).

Students Lack of Clarity on the Nature of a PhD
Students are often unclear about what a PhD is, about the nature of it, and
students lack of clarity impedes their ability to succeed. (Golde & Dore, 2001;
Golde, 2004). At Cross Purposes, primarily funded by the Pew Charitable Trust,
was completed by Golde and Dore (2001). This study also focused on doctoral
education from the student perspective because, the researchers argued, seeing PhD
education through the students eyes provides a different vantage point. This
snapshot study (N = 4,114) consisted of a national survey with questions related to
why students wanted a PhD, how a PhD related to their career paths, student
expectations, and program transparency vis-a-vis knowledge and skills preparation.
Back to Paula again. Learning is a situated process (Lave & Wenger, 1991)
within a defined doctoral program in which social interaction, negotiating meanings
and understandings which allow for higher-order learning over time (Wenger, 1988).
PhD activities grow more complex as Paula proceeds along her PhD journey, and she
must acquire and apply an understanding of the PhD process in order to succeed. In a
PhD context, if she is motivated, understands the rules of engagement (the curricula,
research and participation opportunities, expectations), observes the signposts
(support or critiques from her advisor/mentor and peers), is able to seek help when
she needs it (is proactive), and negotiates the terrain better as she develops
academically and cognitively (moves from novice to expert), she will arrive at her
PhD destination in a timely fashion (graduate).

Another study contributed knowledge regarding students lack of clarity
around the nature of a PhD. From Golde and Dores 1991 study, one of two major
findings stated (a) that many students do not understand what they are undertaking
when they begin a PhD, and (b) that students do not understand how a doctoral
program works and thus they do not understand how to navigate it effectively.
Mismatch of Students and Program Expectations
Because students do not understand the nature of a PhD, they enter a doctoral
program with unrealistic expectations (Golde & Dore, 1991; Hawley, 1993). Two
findings from the Golde and Dore study revealed a mismatch between how students
are trained in a PhD program and what students is expected from the training. The
first major finding is that the training doctoral students receive is neither what they
want nor what potential employers want. The second major finding is (a) that many
students do not understand what they are undertaking when they begin a PhD, and (b)
.that students do not understand how a doctoral program works and thus they do not
understand how to navigate it effectively. Highly relevant for the study I wanted to
conduct, the Golde and Dore 2001 study influenced conceptual components such as
student expectations and program transparency for my study framework. Findings
from their 2001 study provided confirmatory evidence to Golde and Dores previous
efforts (Golde & Dore, 1999) and, ultimately, my study confirms aspects of their

An Invisible Problem
Another study conducted from the student perspective was the Leaving the
Ivory Tower study (2001) conducted by Barbara Lovitts. In this, she examined the
causes and consequences of departure from doctoral study. She described the problem
of PhD non-completion as an invisible problemnot because it was not known, but
because it had not been addressed. For large segments of the American faculty and
administrators, the problem of non-completion does not exist because it is largely
invisible (p. 1). As Lovitts notes, faculty she interviewed were often amazed and
surprised at the high rates of student departure in their and other departments.
As I conducted my dissertation study, I mentioned the current understanding
that approximately half of the PhD students do not graduate to one of the teaching
scholars at the institution that I studied. He said that he was not aware of this
number. Indeed, the actual numbers are not known (NRC, 1996) nationally and are
often unknown within ones own department. No one tends to keep such data.
Lovitts (2001) examined 816 PhD students (511 who had completed, 305 who
had not), who, between the fall of 1982 and 1984, entered one of two universities in
nine departments: biology, chemistry, economics, English, history, mathematics,
music, psychology, and sociology. All had attended American colleges and
universities as undergraduates and all were enrolled full-time in PhD programs.
Lovitts concluded that, if graduate students were responsible for their own departure,
the departures would be idiosyncratic. However, a pattern does exist suggesting the

structural and socio-cultural nature of departures (p. 21). Graduate student non-
completion is, she asserts, a function of graduate program structures, that
opportunities for integration and cognitive development within those structures, and
that causes of non-completion are deeply embedded within the organizational
culture, the structure, and the PhD educational process.
Lack of Program Transparency
Too often, success in education is the result of guess my rule (Lovitts, 2001,
2007), meaning that the rules are not transparent to the students who must follow
them. One recent study (Lovitts, 2007) goes a long way toward making more explicit
the current lack of program transparency; specifically, she addresses performance
expectations for the dissertation, addressed in further detail below. From this study,
she concludes that faculty from each discipline, who met in coordinated focus groups,
said essentially the same things related to judging the quality of dissertations.
Ironically, faculty also said that the purpose of a dissertation is to contribute original
and significant work. However, faculty said that they did not expect many students to
make these contributions. For example, at one institution, psychology faculty said that
they had not seen an original dissertation for 20 years. If faculty expect an original
or significant contribution to be the result of a dissertation, why do these kinds of
dissertations occur so infrequently? Lovitts (2007) also reinforces the notion that
dissertation-writing can be used as formative development, not as a template with
check-boxes. In other words, each dissertation is to be judged on its own merits. Her

work contributes to the transparency of PhD education by demystifying performance
expectations for dissertations in 10 disciplines.
What Contributes to a Clearer Understanding
of the Nature of a PhD?
In 2001, Debra Stewart (CGS president) summarized concerns related to
reform in PhD education. A major research effort around PhD completion comes
from the CGS and is one of the principal long-term efforts focusing on PhD education
from a doctoral student perspective. CGS members efforts over the past 15 years
resulted in a white paper (2004). This paper included a conceptual framework that
influenced my framework, which I present shortly. In collaboration with the Sloan
Foundation and the National Science Foundation, CGS members then engaged with
key stakeholders in a national discussion to address this issue. One outgrowth was a
major, long-term project: The PhD Completion Project. According to Stewart (2007),
because of a dearth of studies on the topic, the Project is taking a first step toward a
first phase in finding out where to put a baseline on completion/non-completion.
Results of this major ten-year study will be released in 2010.
Student Perspectives Central to Research Questions
While the student perspective is crucial, it does not exist within a vacuum, and
it is within the context of the program that the students doctoral process occurs. Most
studies are conducted from the institutions or faculty perspectives. Nearly missing in
the literature are student-centered studies (Golde, 1996; Golde and Dore, 2001;
Lovitts, 2001). Assuming that an understanding of a student-centered PhD process

has value (CGS, 2004; Golde, 1996; Golde & Dore, 2001,2004; Golde & Walker,
2006; Lovitts, 2001, 2007), understanding conceptual components of the process in
which a student attempts to navigate a PhD also has value.
Without an understanding of the process on the ground, no statistical
measurements or longitudinal studies could represent the changing realities and
attendant opportunities for American PhD education in the 21st century. Because this
perspective is nearly missing in the national conversation around PhD completion, I
wanted to include that perspective. If scholars are to better understand the dimensions
of students progress in a context of PhD education, the student perspective is a
crucial perspective to be considered.
Student Motivation and Persistence
While approximately half of the PhD students depart studies, approximately
half do not. For those students who continue and earn their PhDs, their motivation
and persistence play a part, and may be significant student characteristics. As will
become clear in the case-study findings, motivation and persistence were indeed
crucial to students success.
The motivation and persistence literature is helpful in understanding how
these may be important student characteristics. For example, motivation toward
earning the PhD can be of two kinds: intrinsic and extrinsic (Pintrich & Schunk,
1996). Pintrich and Schunk define intrinsic motivation as self-generated and internal,
while they state that extrinsic motivation comes from external sources. For example, a

doctoral student may be motivated internally by delight related to a chosen
dissertation topic, while at the same time be motivated externally by faculty and peers
to study for comprehensives exams or to discuss exam issues with members of their
intellectual community. How a program structure influences students motivations is
not well understood (Tinto, 1993), but having students learn as a member in a
community of learners appears to be a motivator (Rogoff, 1990; 1993). Examples
would be a learning group, a research study group, or a doctoral seminar. A condition
for learning and motivation, then, includes participation (Dweck, 1986; 1990, Rogoff,
An intellectual community also motivates the process of PhD education
(Golde & Walker, 2006). A learning community can be considered a field of
practice (Bourdieu, 1977), a field in which a student participates with others. Said
another way, when a student enters a doctoral program, a student enters a
community of practice (Wenger, 1998) and learns from faculty, peers, and
experiences. Membership within such a community is not automatic; rather, an
individual must recognize the existence and the value of the community, must seek to
be a member of it, and must be invited into it and, as Lovitts (2001) states,
participation in an intellectual community provides students with ruleswhether
explicit or implicitfor how to navigate the doctoral process.
Bowen and Rudenstine (1992) investigated PhD education trends in
completion rates, and they concluded that those deep-seated differences in

completion rates reflected fundamental aspects of the content and organization of
graduate work in various fields of study. Further, they stated that, given the
extraordinary amounts of [resources] students are expected to invest to earn
doctorates, it is wrong not to first understand the factors responsible for current
norms, then look for ways to do better (p. 3). Although the answer to why so many
PhD students depart studies is unknown, Bowen and Rudenstine also speculated that
the level of trauma in obtaining a PhD is significant enough that PhD-holding
researchers do not wish to revisit the topic, and thus do not wish to conduct research
on the issue.
In a recent study, Lovitts (2007) concluded that, if dissertation-performance
expectations could be made explicit, and if faculty (and students) could see doctoral
education from a formative perspective, perhaps such learning could improve PhD
education. Funded by the Alfred P. Sloan Foundation, Lovitts (2007) examined
dissertation performance expectations across 10 disciplines in what she termed the
making the implicit explicit study or MIE. She identified study coordinators at
nine geographically-distributed institutions and investigated one aspect of the PhD
the dissertation. In this study (N = 276), she worked with coordinators at nine
institutions and I was fortunate to be one of the coordinators. A facilitator and I
interviewed high PhD-producing faculty (identified by the departmental Chair) in 74
departments of 10 disciplines in order to examine standards and criteria forjudging

dissertations. Participating in the MIE study served as a pilot study for this
dissertation study and influenced my choice of topic and methods.
Building Relationships in Community
Scholars of completion/non-completion research (CGS, 2004; Lovitts, 2001;
Nettles & Millett, 2006; Rogoff, 1990) state that relationships can enhance learning
through an apprenticeship model. Building relationships is the key for a doctoral
student in order to be insulated from the most negative aspects of the political strife
(Donald, 1997) that comes with any graduate education program. How students build
relationships, how they integrate into a community, how effective they become in a
setting, is determined by what they have previously acquired in terms of social,
cultural, and linguistic capital (Bourdieu, 1977). For example, if a student does not
comprehend the critical importance of developing ongoing working relationships with
faculty and peers (Lovitts, 2001), perhaps believing that faculty expect students to
work alone when they refer to students working independently, that student may
remain uninformed and unnoticed. She states that working alone can isolate a student;
working independently can be working by oneself or with others, but suggests a
student who is integrating guidance and conducts scholarly efforts as an emerging
Over time, successful students build relationships that help them learn and
develop appropriate cultural behaviors (Donald, 1997; Hawley, 1993). Such students
build relationships in peer/faculty/professional networks (Golde & Walker, 2006) that

help them move forward in their doctoral program. Sometimes, a student is not
successful in making progress. At times, a student becomes invisible and simply
leaves a program in silence (Lovitts, 2001), having been unable or unwilling to do
what is necessary to complete a PhD.
Social and cultural nature of student success. By means of academic, social,
and cultural engagement, if all goes well, a student meets all expectations and
succeeds (graduates), having transformed her or his identity (Goffman, 1959) from
novice to expert (Lave & Wenger, 1991). Because disciplines are cultures (Donald,
1997), and they determine the discourse within the culture, if one wishes to
understand how students engage in their doctoral process, it is important to
understand that a student who succeeds integrates successfully into the culture of the
respective discipline, in addition to having adapted successfully to the academic
culture writ large. Bourdieu (1977) refers to an arena within which individuals learn
and develop as a field of practice (program structure and culture) and students
integrate into their community (Rogoff, 2003). In its strictest sense, a structure
represents both physical (the physical environment and resources) and explicit
requirements of a PhD program. A structure, then, is visible and explicit to a student.
Cultural characteristics are more implicit.
Learning occurs in community. Lave and Wenger (1991) state that effective
learning does not occur in ones head; rather, it occurs within community (a field of
practice), by means of interaction and negotiated meanings. Because a learning

community is a joint enterprise, it functions through mutual engagement (Rogoff,
1990), and has a shared repertoire of communal resources, such as artifacts,
vocabulary, and expectations. In such communities, a learner engages in creating,
refining, communicating, and using knowledgeall of which allow an individual to
become a member of a particular community (Rogoff). In a community, learning is
thus situated.
As a student adapts to a discipline (Donald, 2002), a student also adapts to the
larger learning communities (Rogoff, 1990), such as a PhD program or a professional
disciplinary society. The notion of community, then, as depicted by Donald and
others, can develop as a student engages, integrates into a culture, and produces
knowledge valued by that culture. In earlier stages of engagement, a student (novice)
is a legitimate peripheral participant (Lave & Wenger, 1991). As a student integrates
into an intellectual community of scholarsa PhD programa student gradually
becomes a full co-participant (expert).
For a developing scholar, this community is the foundation for the core work
of doctoral education: building knowledge (Walker, Golde, Jones, Bueschel, &
Hutchings, 2007). Another way of saying this is that, in order for a novice PhD
student to negotiate the transition (transformation) to becoming an expert, he or she
develops within a field of practice. Doctoral students want to be surrounded by
others who share their passion (Walker et al., 2007), and a disciplinary group

whether it be in a seminar, a lab, the program itself, or a research groupcan be such
a venue, a community.
Because a students power to learn in a community setting is partially
determined by a persons social, linguistic, and cultural capital, or habitus (Bourdieu,
1977; Bourdieu & Passeron, 1977), it is reasonable to suggest that those whose
habitus is more congruent with the mainstream values and structures would succeed
more readily than those for whom it is not. If a student does not participate in a
chosen field of practice, for whatever reason, a student easily can be submerged and
drown in powerful currents such as multiple, simultaneous expectations and deadlines
of the academic process. At other times, a student who may appear to be at a
disadvantage socially, culturally, or intellectually, may emerge successful through
personal motivation to overcome obstacles such as overwhelming family demands.
Key issues around PhD completion and non-completion are represented graphically in
the following section.
The CGS Completion-Attrition Kaleidoscope
I introduce two representations: one from the literature (the CGS
Kaleidoscope, Figure 2.1) and my conceptual framework that I developed as I
reviewed the literature and undertook this study. While not undergirded by a specific
theory (personal communication, CGS staff, January, 2006), the selected factors of
the CGS kaleidoscope are derived from the literature.

Elements of the CGS Kaleidoscope
The CGS model represents three embedded contexts as concentric circles: the
individual, the institutional, and the social. The first, the individual, includes student
qualities, which are embedded in the secondthe institutional. This includes student
selection, mentoring, funding, program environment, and processes and procedures.
The institution is further embedded within a larger social context. The CGS notes
that, at the next social level, are socio-demographic factors (such as race/ethnicity,
citizenship, age, and gender).
Figure 2.1. The CGS PhD Completion-Attrition Kaleidoscope

Student Qualities
Central to the CGS kaleidoscope is the student; thus, the innermost circle
represents student qualities. A student works within and among multiple contexts,
including social and cultural ones. These contexts successively overlay the daily
academic activities of the student (Golde, 1998) with the additional complexities of
social and cultural elements and expectationssome of which are not transparent.
Institutional Factors
The CGS kaleidoscope also includes a mid-level viewthat of the
institutioncritical to consider for our deepest understanding of the forces at work
within a doctoral program (Lovitts, 2001), which itself exists and operates at the
departmental level (CGS, 2004; Golde, 1996; Tinto, 1993) within the institution.
Layers of social, institutional, and individual influences cannot be distinguished
cleanly, and the distinctions can blur. It is important to bear in mind that these
layers represent a complex system of dynamic tensions (Senge, 1990). The CGS
framework illustrates a complex process with an elemental figure. Interactivity or
relationships among elements, for example, is not represented.
Socio-Demographic Factors
The CGS Kaleidoscope includes socio-demographic factors as age,
citizenship, race/ethnicity, and gender. One way to divide up social issues is to look at
both the individual and social factors (Wertsch, 1998), which this kaleidoscope
includes. That is, if one attempts to comprehend the individual in society, one might

give primacy to the individual, whereas another might give primacy to the cultural,
historical, and institutional. As Wertsch reminds us, the key to dealing with the
individual in/versus society antinomy may be to recognize that the relationship
between them is not an either/or.
Critique of the CGS Kaleidoscope
The CGS kaleidoscope served as the primary model that influenced the
development of my conceptual framework and my model, which will be presented
and discussed shortly. While Figure 2.1 served as a building block for this
dissertation because it represents the student as central to the issue of completion and
non-completion, this representation of PhD education has shortcomings. In this
kaleidoscope, the PhD is illustrated as a highly generalized, static universe in which
the student is central, but elements such as mentoring, processes, and program
environment are imprecise. Although the CGS representation is simplistic, it
contains elements thatwhen investigatedled to a more in-depth investigation of
the elements of the PhD. First, I discuss the shortcomings of the CGS kaleidoscope,
then the elements that I believe should be retained.
Does not include culture. The CGS kaleidoscope does not include culture or
represent it. It illustrates mode of field, although it is not clear whether this means
that humanities are library-based and sciences are lab-based or that the mode
represents discipline. In either case, further detail would enhance an investigators
understanding of the reasoning behind the figure. Because cognitive development

occurs in a social context (Rogoff, 1990), it is important to include the element of
culture in any graphic representation of a PhD education. Further, culture shapes the
minds of individuals in particular ways and influences a learners meaning making
(Bruner, 1996).
Does not include learning. The purpose of a doctoral program is to train
students in the context of a knowledge domain to conduct research, to teach, to
publish, to engage with a learning community throughout the process of earning a
PhD, and to continue to work in a learning community over the long-term (Lovitts,
2001). What happens in each program varies, of course, but not to represent the
concept of learning is not to address the core of the process. In order for a student to
move from a novice to an expert (Lave & Wenger, 1991), a student must have a
guide. Guided participation by a faculty member (Rogoff, 1990) can enhance learning
by providing a student with appropriate challenges step by step. With such guidance,
a student can learn more effectively than if a student is learning alone (Vygotsky,
Does not represent a process. A salient deficiency is that the CGS
Kaleidoscope over-simplifies a PhD and in so doing does not represent the PhD is a
process. For example, program environment does not specify the nature of the
environment. In particular, it does not distinguish between the implicit and the
explicit aspects of the PhD, which are key parts of my conceptual framework. One of
the issues in the literature relates to transparency of process. If a student does not

understand the process, a student cannot succeed. In order to represent a student
succeeding, it is important to represent an overall PhD process and clear steps in that
process that lead to success.
Elements that Should be Heeded
Several aspects of the CGS model reflect the literature and should be
examined by researchers. These include taking a program view, addressing the
embedded contexts of PhD education, and considering program factors
(institutional factors in the CGS terminology).
Program factors. Because the program is the heart of PhD education, it is a
critical element for the framework I developed. Of the CGS kaleidoscope institutional
factors, my framework retains the discipline (CGS mode of field), processes and
procedures, mentoring, and program environment. Because a student finds an
intellectual home within a discipline, the disciplinary program represents the
crossroads of disciplinary scholarship, whether within one program or across similar
disciplinary programs (Lovitts, 2001). Teaching and learning happens within a
disciplinary program (Golde & Walker, 2006). In order to better understand doctoral
teaching and learning phenomena, in behooves scholars to better understand the
nature of a PhD program.
Embedded contexts. The CGS Kaleidoscope incorporates social-cultural
contexts in order to address adequately both the social-cultural and the embedded
nature of the PhD (CGS, 2004; Donald, 1995; Hawley, 1993; Lovitts, 2001).Because

a PhD student (one context) conducts research within a program within an institution,
one context (a program context) is embedded within another context (an institutional
context). These contexts (individual, program, institution) are located within
professional disciplinary societies and the society at large. The PhD process, then,
occurs within embedded contexts (CGS, 2004; Golde, 1996).
Student qualities as central. The CGS Kaleidoscope illustrates that the student
or student qualities are central to the PhD process. While this may seem obvious, the
student perspective is often overlooked. Similar to the CGS, my conceptual considers
the student at the center of the PhD.
Back to Paula once more: What is not included in the CGS Kaleidoscope that
I do include in my conceptual framework are student qualities related to background
(habitus), motivation, and capital (social, cultural, political, intellectual, linguistic).
Although sometimes qualities that students need to succeed are implicit, sometimes
they can be developed. For example, if Paula discovers that her level of motivation is
insufficient to the tasks of earning a PhD, she may realize this and generate additional
motivation. If she does not realize it, she may not succeed because she is operating
somewhat blindly. These valuable qualities may be especially invisible to individuals
whose cultural capital (Bourdieu & Passeron, 1977) is not congruent with the culture
of the educational institution. Paula is operating within a context that has rules, but if
the rules are implicit, established by the culture first, by the institutions, and by the
disciplines, she may succeed, depart, or flounder in an unwritten guess my rule

game (Lovitts, 2001,2007). Successful navigation through the PhD process, then,
does not happen for all students, and the playing field is sometimes not even. Thus,
PhD students are engaged in a process rife with external pressures that are often
undefined (Lovitts, 2001).
Conceptual Framework
Student Progress through a PhD Program
Lev Vygotsky (1978) discusses relationships between learning and
development. In this work, one of his notions is that the transformation of an
interpersonal process into an intrapersonal one is the result of a long series of
developmental events (p. 57). Guided learning from an expert, he believed, could
accelerate and/or raise the quality of a students learning. This kind of guidance he
referred to as scaffolding. If a teacher (expert) can help a learner (novice) move
from one level of understanding to another, Vygotsky explains that this student is
scaffolded by the teacher.
From this general notion, Vygotsky developed his zone of proximal
development (ZPD), Vygotsky maintained that, when a student is scaffolded, that
student is able to progress more successfully than a student who attempts to learn
independent of such guidance. Vygotsky described this ZPD phenomenon:
The zone of proximal development is the distance between the actual
developmental level as determined by independent problem solving
and the level of potential development as determined through problem
solving under adult guidance or in collaboration with more capable
peers, (p. 86)

A major theme of Vygotskys (1978) theoretical framework stated that social
interaction plays an elemental role in cognitive development. It should be noted that,
while Vygotskys insight was new at the time and its importance cannot be
minimized, those who followed him were the ones who clarified the concept and the
insight and applied them. For example, Lave and Wenger (1998) built upon
Vygotskys ZPD concept and insight by connecting issues of sociocultural
transformation with the changing relations between newcomers and old-timers in the
context of... shared practice (p. 49). Through ZPD in a community of shared
practice, then, the newcomers, or legitimate peripheral participants, learn through
active engagement with the old-timers. If all goes well, the newcomers become
members of the intellectual community through shared practice.
Introduction to My Conceptual Framework
Parsons (1961) makes a fundamental distinction ... between the
morphological analysis of the structure of systems and the dynamic analysis of
process (p. 31). A PhD process is fundamentally dynamic (Golde, 1996). The
process is dynamic because it occurs over time. However, the process has various
participants, occurs within a cultural and institutional context, and each of the
participants and institutions brings assets, liabilities, and expectations to the process.
Because of the multiplicity of processes affecting doctoral education, I needed to
develop a conceptual framework.

My framework defines the participants, the programs embedded within
institutions, the context, the component factors that influence the processes and their
relationships to the overall process. For my purposes, the program is the unit of
analysis, and the process of attaining a PhD is part of the conceptual framework.
Further, the process is related structurally to the components presented in the
Figure 2.2 (p. 43) presents my conceptual framework which represents a PhD
students evolution; specifically, it illustrates that evolution as a process. The element
of time in the framework supports the notion of process. So, once a student enters a
PhD program, the student begins a journey within a learning community, an existing
set of social, learning-oriented relations. My framework provides a macro view of
the PhD process, representing what happens before a student enters, a students
learning process over time, and possible outcomes. Yet my framework also represents
the relationship of this process with the context in which it occurs: embedded
contexts such as program culture and structure, student and faculty participants, and
the students assets and liabilities.



Capital (ocial cultural,
political, linguistic, and
intalloctuai savvy)
Motivation (porslstoneo &
(what a PhD program is)
Figure 2.2. My Conceptual Framework
I also propose a Program Process Model that represents this dynamic process
of completion in greater detail. It opens a window into what is only a single arrow in
Figure 2.2. The Program Process Model reveals that process as really two, one
explicit and one implicit, and it identifies in more detail the components of each of
these explicit and implicit processes. Next, I explain both the frameworkthe
macro viewand the model, the micro dynamic view.

Framework Description: Factors that Affect Students Learning over Time
In order to understand how a PhD student learns over time, I examined the
literature related to learning, to student success, capital (savvy), student motivation,
and student expectations. These areas are discussed below as student characteristics,
program structure and culture, and student navigation through a program.
Faculty. This arrow represents the faculty pre-admission process. Students are
screened based on doctoral program criteria, and qualified students are admitted
(Lovitts, 2001). While different programs may have different criteria, these steps are
the overarching ones.
Student characteristics. Student characteristics in PhD programs include a
students background or habitus (Bourdieu, 1977). Background includes all
influences on a student up to the point of entering a doctoral program, such as
education, family, and social influences. A second characteristic included in the
framework is capital: the social, cultural, intellectual, and political nature of
masteryin this case, mastery learning (Dweck, 1986). Social and cultural capital
refer to a students abilities to navigate socially and culturally within a PhD process.
Intellectual capital represents a students intellectual ability and adaptability. Political
capital represents a students ability to continue making progress while being able to
navigate within a political arena.
A third framework element is student motivation (Pintrich & Schunk, 1996;
Tinto, 1991, 1993), as a students self-directed learning (Knowles, 1975) influences a

students progress. This includes persistence and perseverance. Persistence is time
spent on a task and is important because much learning takes time and success may
not be readily forthcoming. Persistence relates directly to the sustaining component in
the definition of motivation ... and greater persistence leads to high
accomplishments (Pintrich & Schunk, p. 15).
The fourth element, student expectations, relates to what a student expects a
PhD to be and the effects of those expectations (Golde & Dore, 2001; Passeron &
Bourdieu, 1977) on their progress.
Program structure and culture. Concepts related to structures and cultures are
incorporated into my framework (Golde & Walker, 2006; Lovitts, 2001, 2007),
because something deeper than individual agency is at work when nearly half of the
PhD students in the United States do not complete their studies (2007). Illustrated in
my framework, when a student enters a PhD, that student encounters a program
structure and culture. Structurally, a student is required to meet the specified
academic requirements (CGS, 2004; Lovitts, 2001). These are relatively
straightforward and are specified in the next section. While some research discusses
the importance of program structure (Golde, 1996; Lovitts, 2001), a dearth of
literature exists on the impact(s) of a program culture on a PhD student.
When a student encounters a program culture, a student encountersand
engages withnorms, attitudes, relationships, and the program environment. Each
disciplinary program embodies cultural characteristics including norms, shared

language (terminology), spaces (labs, classrooms, social events), assumptions
(academic curricula, theories), student composition (male/female), expectations (often
not explicit), and ways of behaving, such as presenting research (Donald, 2002).
Thus, disciplines are cultures (although the growth in interdisciplinary work has
blurred these distinctions somewhat) in which knowledge in the discipline is
validated through internal consistency in terms of testing a model or an interpretation,
coherence, and precision (Donald, 1997, p. 32).
Bruner (1996) considers culture to be a system of values, power, opportunities
(obligations or otherwise), interactions, and rights. The academic culture could be
considered a macro culture. When one examines the micro side, one can see how
the cultural system affects those who operate within itthe PhD student in this case.
Constraints are managed based on cultural agreements and the educational system
that they institute (Hawley, 1993). Disciplines determine the parameters or domains
of knowledge, the conceptual and theoretical structures, and the lines (or modes) of
inquiry (Bruner, 1996) and are embedded within cultures, which are embedded within
programs, further embedded within institutions.
Because practice is the key to constructing a new identity (Bourdieu &
Passeron, 1977), one observes, learns, and practices the norms, behaviors, and ways
of thinking about a domain over and over and internalizes them through participation.
For those whose backgrounds are aligned with the dominant culture, practice comes
more easily than for those whose backgrounds are not (Bourdieu, 1977), because

some of the norms are already understood by the former and perhaps not by the latter.
As the university reflects the dominant culture, those who must overcome their lack
of belonging to the dominant group may struggle (Lovitts, 2001).
Both structure and culture, then, influence and shape a students participation
and engagement in a doctoral program. Regardless of the discipline or the institution,
then, program culture and structure informs and shapes a PhD education (Golde,
1996; Lovitts, 2001) to evolve step by step to assume the mantle of independent
thinker, researcher, and scholar. As such, they are considered core parts of this
Learning process over time. How a student progresses in this process will be
determined (in part) by habitus, or background, (Bourdieu, 1977); by a
comprehension of the embedded cultures in which the student operates, which is the
result of educational, social, and cultural background; and by how well he or she
navigates the process (Golde & Dore, 2001). As illustrated in the framework, to be
successful, a student learns in a situated setting within embedded contexts (CGS,
2004; Golde, 1996; Lave & Wenger, 1991). A successful student also learns to pro-
actively navigate the explicit and the implicit aspects of a doctoral program.
Scaffolded by advising and more capable peers (Vygotsky, 1978; Lave &
Wenger, 1991; Wenger, 1998), a student (if all goes well) transforms from being a
legitimate peripheral participant (novice) through cognitive scholarly development to
being a full co-participant (expert). Scholars have found that it was the conversations,

the interactions, and the shared struggles of sustained discussions that led to
generative ideas (Bruner, 1996; John-Steiner, 2000). Apprenticeship, guided
participation, and participatory appropriation correspond to personal, interpersonal,
and community processes (Wertsch, Del Rio, & Alvarez, 1995). These processes are
inseparable, and in the process of socially structured activities and practice, a student
becomes better prepared for later participation in related events (Vygotsky, 1978,
1986). Learning and cognitive development occur within learning communities when
learners have opportunities for inter-dependence and autonomy. It is, then, from
guided participation within a learning community that students gain ground, learn
deeply, and develop their own insights through generative thought.
Because a PhD student navigates in a field of practice where the stakes are
high (students help faculty build their academic reputations and create academic
reputations of their own), Donald states that a doctoral student may also get caught in
political cross-fire, such as having to negotiate among committee members who
dislike one another. An example of this is discussed in Chapter 5.
Learning Process Over Time: from Novice to Expert
Developing a scholarly identity as a member of such a community requires
practice in a complex setting involves multiple skills and often a steep learning curve,
which incorporates mentoring/apprenticing, coaching, reflection (Austin, 2008), and
scholarly practice (research, writing, presenting research). Because it is through the
scaffolding of guided participation that a PhD student makes progress. The guidance

may come from faculty or from a more capable peer (Lave & Wenger, 1991).
Progress is made when a student, under expert guidance (guided participation), meets
expectations and requirements in order to become a full participant in the learning
community (Lave & Wenger, 1991). When a PhD student is advised, mentored, and
guided successfully, that student can learn as an apprentice in the presence and with
the help of an expert (Rogoff, 1990,2003).
In a well-scaffolded environment, skills are acquired and roles appropriated
(Rogoff, 2003) as part of the doctoral education process, over time. Mastery of skills
and the ability to assume a variety of roles is required for a learner to participate
successfully in a learning community culture (Bruner, 1996; Hawley, 1993; Rogoff,
1990). Being bright is not enough (Hawley). Faculty talk about skills that successful
students exhibit (Lovitts, 2001), although it is arguable that they may also be
considered attributes: being bright, independent, self-motivated, hard-working,
dependable, talented, resourceful, mature, articulate, and having good social skills
(p. 281). Not all successful students have all of these skills and characteristics; many
simply blossom over time with some guidance (Lovitts).
Four outcomes are illustrated in the framework. A student earns a PhD and
graduates, a student drops out, a student leaves ABD, or a student flounders. If all
goes well, a student graduates. If various circumstancesa student transfers, decides
not to earn a PhD, or has interfering circumstancesa student may depart studies. If a

student loses direction, has insufficient guidance (Donald, 1994; Lovitts, 2001;
Nettles & Millett, 2006), a student may flounder and may or may not succeed. A
student may also complete requirements for an ABD status, but not finish a PhD.
Next, I introduce my program process model, which illustrates more specific
elements of the PhD process.
My Program Process Model
In order to understand better the formal (explicit) and the informal (implicit)
aspects of doctoral education (CGS, 2004; Lovitts, 2001, 2007), I propose a model,
Figure 2.3, below, that illustrates the learning process post-coursework through
graduation (or not). It is a close-up of both the explicit program structure and the
implicit program culture. Developing this model helped me understand the basics of a
program, the basics of a process, and served as a type of anchor for me. That is, I used
the evolving model as an anchor against which to compare my ongoing findings.

Figure 2.3. A Program Process Model
Explicit Elements
The two arrows in this figure are parallel, representing a parallel process that
occurs among explicit and implicit elements of the PhD process. The top arrow
represents the explicit aspects of doctoral education. Explicit structures include such
items as institutional rules, organizational charts, and curriculum. They also include
requirements that represent benchmarks in PhD education: completing the
coursework, passing comprehensives, defending a prospectus, conducting a study and
gathering/sorting data, analyzing and synthesizing the data, writing up the data,
defending the dissertation, and completing rewrites. If and when a student

satisfactorily passes these benchmarks and meets all of the dissertation committees
expectations and requirements, a student graduates.
How might a doctoral student meet performance expectations if those
expectations are not explicit? Explicit dissertation rubrics have only recently been
developed (Huba, Schuh, & Shelley, 2006; Lovitts, 2007), to which both (national)
faculty and prospective or current students can refer in order to better conceive of
what may be expected (Lovitts). If expectations are transparent, if a student can
access and integrate into the academic community at the level of doctoral
performance, and if a student can find a champion-advocate advisor/mentor, then a
student may have a good chance of succeeding. Clearly, some PhD students earn their
degrees without these transparent facilitators, but a lack of transparency is perhaps
one reason that the American average completion across disciplines is approximately
50% (CGS, 2004; Lovitts, 2001).
Implicit Elements
It is often incumbent upon the student to understand the implied expectations,
to read the air, to understand the subtext in conversations, and to engage fully with
the challenges of finding out what is expected. It could also be incumbent upon the
program to be more explicit (Lovitts, 2001).
Implicit Expectations Drive Implicit Elements
In Figure 2.3 above, implicit expectations drive the implicit process arrow and
represent the fact that much of the PhD process is not transparent. Rather, many

expectations are implicit (CGS, 2004; Lovitts, 2001; Golde & Walker, 2006), whether
by accident or design is unknown. At times, a students expectations are unclear
(Golde, 2001; Golde & Dore, 2004); at times, the faculty/program expectations are
unclear. Implicit expectations also influence other implicit elements, including values,
norms, and political elements that are present but not communicated. As illustrated in
the model, implicit process elements include being socialized into the department;
building relationships; learning to navigate socially, politically, and culturally; coping
with personal circumstances; participating in research groups; expanding networks;
and meeting all implicit expectations.
Socialize into department. Socialization (Bourdieu, 1977; Rogoff, 1990)
includes the process by which a student adapts and/or acquires the attitudes, beliefs,
skills, knowledge, values and beliefs of a particular domain. Doctoral students learn
by immersion in a doctoral culture an structure (Donald, 1994, 2002), through social
and intellectual engagement with peers and faculty (Bourdieu, 1977; Lave & Wenger,
1991; Vygotsky, 1978), and transform through practice (Rogoff, 1995), through a
transformation of participation. As PhD students persist by motivating themselves in
their tasks toward completion (Pintrich & Schunk, 1996; Tinto, 1993), through trial
and error, confusion and struggle, engagement and exhilaration, a successful doctoral
student will gradually become socialized within the implicit culture. Said another
way, Wertsch (1998) notes one aspect of the Vygotsky-Luria school, namely, that the

origins of conscious activity occur not in the recesses of the human brain or in the
depths of the spirit, but in the external conditions of life (p. 8) such as practice.
Vygotsky stated that social relations or relations among people ... underlie
all higher functions and their relationships (Cole, 1996, p. 111). Through these
processes of socialization, a willing student can transition from thinking and
performing as a beginner to thinking and performing as an evolving expert. Being
socialized into the program means for the student to be integrated into and navigate
socially within the program. That is, an individual learns to present herself or himself
by incorporating and exemplifying the officially accredited values of a society
(Goffman, 1959).
Build relationships To navigate difficult implicit territory, a student must
depend upon the cultural expertan advisor, other faculty, or more capable peerin
order to navigate the PhD process (Lave & Wenger, 1991; Rogoff, 1990). A doctoral
student learns to communicate with faculty and peers in a way that strengthens ones
own work (Bourdieu & Passeron, 1977). These opportunities for practice in multiple
areas, then, may represent significant challenges because a PhD student often must
learn several of them simultaneously (CGS, 2004).
Apprenticeship, the signature pedagogy of doctoral education (Walker,
Golde, Jones, Bueschel, & Hutchings, 2008, p. 89), provides one means of this
transformation. Through practice and social engagement, a students identity
transforms in that an individual conceptualizes and thinks in new ways, is able to

organize and synthesize information better, and is able to communicate consistent
with the values and norms of the culture (Walker et al.). When a learner emerges as
an expert, participation is transformed (Rogoff, 1990). That is, previous ways of
being, joining in community, participating, speaking, and thinking give way to new
forms of the same practices (Rogoff, 1991).
Learn to navigate social, political, and cultural elements. To navigate implicit
process elements, a student must have capital (Lave & Wenger, 1991; Vygotsky,
1978) or cultural savvy. A student who has the appropriate social and cultural capital
is better able to read the implicit aspects of the culture than one who does not.
Whether or not a student navigates successfully through the community of complex
program structures and culture(s) of a PhD depend partly on a students capital (Lave
& Wenger, 1991), adaptive ability, an ability to learn, an ability to transform oneself
in the face of pressures and challenges (Baird, 1992; Benkin, 1984; Dolph, 1983).
Cope with personal circumstances. While coping may appear obvious or
mundane, unexpected personal circumstances can serve as major barriers to student
success (Lovitts, 2001). During my own doctoral processand for other students
during the studyI overcame multiple personal circumstances in order to graduate.
These ranged from family deaths to job loss, from lack of funding to changing labs
and advisors. As will be clear in later chapters, other students encountered multiple
barriers and coped with personal circumstances in order to make progress.

Participate in research groups. While the form of this varies, participating in
an intellectual community includes interacting with faculty and peers around research
(Lovitts, 2001). Such participation may include discussing research questions with
ones advisor, discussing journal articles in a doctoral seminar, or presenting research
at a conference. Without such participation, a student may easily become invisible
Expand networks. This includes making connections through fieldwork,
developing personal contacts made at conferences, comparing notes with others in the
field around similar research (Donald, 1994; Rogoff, 1990), or finding out who is
focusing on what in ones field of practice.
Meet all implicit expectations. While some students meet some or most
implicit expectations, it is incumbent upon students to identify all expectations. One
implicit expectation may be for the student to make what is implicit explicit by
ferreting out, for example, what is expected for a dissertation (Lovitts, 2007). The
nature of a PhD is developmental and, as a student progresses, the student develops
characteristics and behaviors of the discipline. As one becomes a member of the
community, one begins to reflect it (Golde & Walker, 2006).
These elements, then, comprise the implicit expectations within a PhD
program, as illustrated in my model. Based on my research reported in Chapters 4
through 6,1 present a revised, post-study model that is informed by my study in
Chapter 7.

Cognitive Scholarly Development: Novice to Expert
As part of understanding a PhD as a process, my conceptual framework
{Figure 2.2, p. 43) shows a students cognitive scholarly development through time.
A students identity transforms through the development of higher concepts from
lower ones (Vygotsky, 1978; Bruner, 1996; Wertsch, Del Rio & Alvarez, 1995). As
learners master knowledge, they gain new vantage points and become able to learn in
a new light. As a student transitions, he or she understands and integrates the norms
and values of the culture (the discipline) at increasingly more sophisticated levels,
and an academic identity (Golde & Walker, 2006) emerges.
Novice to expert. In this way, learning transforms a student from being a
novice to an expert over time. As the doctoral process proceeds, then, a student
gradually acquires or assumes the identity of their profession (Nettles & Millett,
2006). Yet transformation occurs slowly. That is, in the process of meeting both
explicit and implicit program process elements, a student transforms from being a
novice to being an expert, through transformation of participation (Rogoff, 1990) and
identity formation (Goffman, 1959). The emerging identity is, then, one of
identification with the scholarship of a discipline within the academic community.
Remember Paula? If she understands her role as a driver, she understands
what skills she needs to acquire to drive well. As such, she joins a learning
community of drivers, she takes courses from and engages with others who
understand the skills better than she does. She learns the requirements and

expectations she needs to know in order to perform well, and practices to develop
those skills. Gradually, she is given (and may proactively assume) more responsibility
in terms of driving more complex roads and driving independently.
Shift to the context of PhD education. In a doctoral context, Paula learns to
conduct inquiry within accepted disciplinary methods and to present her research at
disciplinary conferences, learns the difference between a peer-reviewed and a non-
peer-reviewed journal, and learns how to meet expectations. Gradually, she constructs
an academic identity that is more expert than novice and, in so doing, will be able to
negotiate successfully in the disciplinary culture and profession of choice.
If all goes well, Paula becomes increasingly self-correcting and self-
generating (Pintrich & Schunk, 1996; Tinto, 1993), transforming from a dependent
learner to an independent learner (Vygotsky, 1978) through practice, and expressing
an academic identity (Bruner, 1996; Donald, 2002; Golde & Walker, 2006). Through
this transformation of participation, Paula gradually constructs a new identity from
being a legitimate peripheral participant (novice) to a full co-participant (expert)
(Lave & Wenger, 1991). Said another way, social discipline allows a mask of
manner to be held in place from within (Goffman, 1959), in that the practice
becomes internalized and gradually becomes authentic to, and part of, Paula. Through
the process of earning a PhD, then, a learner moves from learning to do (such as
learning how to write academically, how to present research to a professional
audience, how to publish) to learning to be (Bruner, 1996). For example, learning to

do research evolves into being a researcher. Learning how to present ones research to
others sharpens presentation skills over time, and a learner becomes a persuasive
scholarly presenter and writer.
Evolution of doctoral education in the twenty-first century. A national
initiative also proved relevant to my study. In the context of preparing future stewards
of the discipline, The Carnegie Initiative on the Doctorate (CID, 2006) represented a
fresh perspectivethat of re-examining the purpose(s) of an American PhD and
envisioning a future of doctoral education. While the CID results emphasized
different disciplines (chemistry, history, education, English, mathematics, and
neuroscience) than the ones in my study (geography and political science), CID
findings were useful in that the study goals and findings are centered squarely on
students. Incorporated into the design of the CID were the students, and they were
included on planning committees, discussion committees, and presented to various
constituencies at participating institutions.
The CID discusses that the needs of doctoral education have changed although
the nature of an American PhD has not. The four core assumptions of this initiative
include grounding the work in disciplines in that the disciplinary experts took the
lead, not the Carnegie Foundation, and grounded the work in the academic
departments as they are the nexus of the discipline and the institution. A third
assumption that drove the initiative was that ideas are more powerful incentives to
change than lists of best practices or even financial incentives, thus re-envisioning

the PhD made sense. The fourth and final assumption was that disciplines have much
to learn from one another. The CID proposes that the central purpose of a PhD
education is to produce stewards of the discipline. To that end, CID scholars say this:
Responsibility for student-centered doctoral education is a shared responsibility of
the faculty, students, and administrators of the university and the practicing members
of the discipline (p. 421).
What facilitates and what hinders doctoral student success? Even with
research on the topic, it is still not well understood how a student knows what is
expected and/or knows how a student transforms from a novice to an expert. Also not
well understood in terms of what facilitates and hinders a PhD student are how to
characterize the role of a good PhD student and the role of a good advisor. Themes on
these two topics have not emerged in the research on doctoral studies, partly because
research has yet to examine such questions, and partly because success related to
PhD completion is a yes-no switch: successful students graduate and unsuccessful
ones do not. Motivated by the framework and the model, my research questions
address what facilitates and hinders a PhD students success, and what program
barriers exist and how they can be minimized to help facilitate success.
The CGS Kaleidoscope served as an influence in the development of my
conceptual framework and my model by helping me understand the conceptual,
embedded layers of doctoral education. Developing my own conceptual framework

and model allowed me to adjust my model as my findings emerged. Because of this,
the framework and model reflect actual findings based on theory and the literature.
Under any circumstance, navigating a PhD is complex because a PhD student
earns the degree (or not) within culturally and socially embedded contexts, within a
variety of agendas (politics), and within a structure in which dominant values prevail.
Regardless of individual habitus (Bourdieu, 1977), social capital, circumstances,
motivation or mentoring, a combination of complex factors interact for the student to
graduate, to leave ABD, to drop out, or to flounder. Regardless of the complexity,
one aspect is certain: The process needs more transparency (CGS, 2004; Golde, 2001,
2004; Lovitts, 2001, 2007; Lovitts & Miller, 2007). A lack of information is one of
the critical factors for doctoral students, a fact that has been considered the heart of
darkness (Nettles & Millett, 2006) of doctoral education. The next chapter, Chapter
3, describes the research questions and hypotheses and the methods used in the study,
which are directed toward a better understanding of this heart of darkness.

My research questions and hypotheses emerged from my framework in a
recursive fashion as a result of two pilot studies. That is, I literally began to draw my
conceptual framework as I participated in the pilot studies, as 1 read the non-
completion literature, and as I drafted various research questions before I identified
my final ones. In this process, I altered both my questions and my framework until I
determined that I was asking questions that would get to the core of what I wanted to
know. Further, based on NRC recommendations (OSEP/NRC, 1996), I constrained
my questions to two social science PhD programs at a single site.
Research Questions and Hypotheses
As the goal of this study is to understand what facilitates and what hinders
PhD student success, one approach might be to identify barriers to success by looking
at those students who left and why. Nationally, however, those types of databases do
not exist consistently among academic programs across or within institutions (Bowen
& Rudenstine, 1992; Stewart, 2007), so I could not use extant databases. I looked in
the literature for what was missing and found that the student perspective was
missing, thus I determined to conduct a study from that perspective.
Two of my research questions relate directly to the student and two relate to
the program. Related to the student, I wanted to know if essential elements could be

identified that would clarify facilitators and hindrances to doctoral student success. If
essential facilitators could be identified, perhaps more of these elements could be
incorporated into doctoral education generally. If essential hindrances also could be
identified, perhaps some of these elements could be further examined, clarified, or
eliminated in order to improve a students opportunities for success.
Research Questions
My four research questions include:
1. According to doctoral students, which factors facilitate completion of the
dissertation in geography and political science at Western University (WU)?
2. According to doctoral students, which factors hinder completion of the
dissertation in geography and political science at WU?
3. What is implicit in the doctoral student program process that can be made
more explicit in order to facilitate doctoral students completion?
4. Which barriers to completion could be reduced from both the students and
the institutions perspectives?
In order to understand why students depart studies, one would have to find
and interview those individuals who left. While a few of those studies have been
conducted (Golde, 1996; Lovitts, 2001), little systematic data are available; neither
have professional societies nor national agencies gathered systematic disciplinary
information (Bowen & Rudenstine, 1992; OSEP/NRC, 1996; personal
communications at WU, spring, 2005). Thus, I needed to address another aspect of

PhD education, one where data did exist, and I developed my research questions and
hypotheses out of an intention to better understand the PhD as a process.
Four Hypotheses
My four hypotheses evolve from my research review as well as the framework
and model that I built and discussed in Chapter 2. If barriers or facilitators in a
students progress could be better understood by both students and faculty, perhaps
interventions might be designed to facilitate increased completion rates. My first
hypothesis is that student fit, or integration into, a programmatic structure and/or
culture is a critical factor in facilitating completion. Second, student motivation
(especially persistence) facilitates or hinders doctoral student completion. Third, a
students personal relationships, especially with her/his advisor, are a critical factor
contributing to completion, and fourth, transparent program expectations also
facilitate completion.
Hypothesis 1. My first hypothesis involves how well a student fits with the
structure/culture of a programhow student expectations of the program culture
dovetail with program expectations of the studentto facilitate or hinder a doctoral
students progress through the field of practice (Golde, 2001; Golde & Dore, 2004).
As such, it may be the program culture itself that explains why some students do well
and others do not (Bourdieu, 1977; Bourdieu & Passeron, 1977; Bruner, 1996).
According to this hypothesis, a student who is able to read social and cultural
cues within the PhD program will make progress toward the degree more easily than

a student who is not. As well, the longer students do not assimilate into the academic
culture of the discipline, the more they will be prone to leave their doctoral program.
Being bright is not enough (Donald, 1997; Geertz, 1983; Hawley, 1993). Rather, a
student must be able to comprehend the socio-cultural environment in order to
navigate it successfully.
Hypothesis 2. The second hypothesis is that a students motivation affects how
successfully he/she navigates an academic program. Characteristics of persistence and
intrinsic motivation (Donald, 1994; Dweck, 1986; Pintrich and Schunk, 1996; Tinto,
1991, 1993) contribute to doctoral student success. For example, an adaptive or
mastery-oriented student behavioral pattern is characterized by a high level of
persistence in the face of obstacles or significant challenges and an additional
adaptive behavior is that of seeking challenges (Dweck, 1986; Pintrich & Schunk,
Following this hypothesis, an intrinsically-motivated student will seek
challenges such as doctoral work and will persist until the challenge is met and the
student graduates. In this context, if all goes well, a highly motivated student will
move through the program, gain self-confidence in the process (Hawley, 1993;
Rogoff, 1990), grow in mastery (Lave & Wenger, 1991), and manage intellectual
tasks such that a student unfolds in a culturally appropriate way (Hawley, 1993). A
student also may grow to assume more and more the role of an agent, a generator, an
initiator (Vygotsky, 1978) and an expert (Lave & Wenger), and may self-regulate

(Donald, 1994, 2002) increasingly in order to move more into the role of teacher
(expert) from that of a student (novice).
Hypothesis 3. This hypothesis relates to the advisor/advisee relationship and
to Vygotskys (1978) Zone of Proximal Development (ZPD). As ZPD assumes a
perspective that mastery is a process, not just a yes/no switch, a skillful advisor will
sense and/or understand both where the student is cognitively, and how he/she can
guide that particular student in order for the student to progress optimally. The notion
is that, if an advisor/advisee relationship is managed skillfully, an advisee will more
quickly learn doctoral-appropriate ways of thinking, writing, and being (Donald,
1994; Hawley, 1993). If an advisee ignores what the advisor offers, it could hinder an
advisees progress. Guidance or scaffolding (Vygotsky, 1978; Wertsch, 1998) for an
advisee to move from a novice to an expert could be compared with climbing a set of
stairs: An advisor guides an advisee in such a way that the latter progressively reaches
higher and higher steps. In the context of a PhD process, this guidance or scaffolding
would (hopefully) allow an advisee to increasingly develop cognitively, step by step.
According to this hypothesis, the more efficacious the relationship between
advisor and student, the greater will be a students assimilation into a discipline and
the easier it will be for the student to succeed. Vygotsky (1986) states that scaffolding
precedes independent accomplishment and effective scaffolding leads to mastery,
which builds confidence, self-efficacy, and motivation (Vygotsky, 1978; Pintrich &
Schunk, 1996). This guidance-learning relationship (scaffolding) may especially

facilitate a student completing the doctorate during a students most difficult times.
The obverse of this hypothesis is that, without scaffolding, the student can feel alone,
discouraged, and leave the program in silence (Lovitts, 2001).
Hypothesis 4. The fourth and final hypothesis examines the degree of
transparency in each of the disciplinary program cultures in this study as expressed
through program expectations (Hawley, 1993). If these are transparent and explicit to
the student, the student can more easily meet the program expectations than if they
are not (CGS, 2004). Transparency can relate to several aspects of a doctoral
program. For example, it can include interactions within the department, relationships
among faculty/students (or students/students) within their doctoral program, modes of
communication, and how norms (principles, practices, behaviors) are conveyed to the
student within that doctoral program (Donald, 2002; Hawley, 1993).
According to this hypothesis, the more transparent the expectations are to the
student, the more the student has an opportunity to fulfill those expectations and to
succeed. As Hawley (1993) notes, the obverse of this is that if a student is not privy to
the unwritten rules or expectations, that student may not be as successful as a student
who understands that unwritten rules and expectations exist, and understands what
they are in their doctoral program. Understanding these rules and expectations allows
some students to have the inside track.

Pilot Studies and Study Design
Two pilot studies preceded my dissertation study: One emerged internally as a
project of the graduate school in which I worked, while an external researcher
originated the other as part of a national study. Both studies allowed me the time and
the opportunities to explore methods of inquiry, which heightened my interest in
research related to non-completion, and both informed my research questions and my
Two Pilot Studies
The first pilot study (2001) began as an initiative of the graduate school in
which I worked, and related to the assessment of doctoral programs. Several of us,
representing institutional research and the graduate school, met with the more than 50
department chairs, asking them about barriers they saw to increasing graduate
students, both masters and doctoral. After a one-year series of interviews, we found
unsurprising results. The single element that served as a departmental/programmatic
barrier to furthering graduate educational development was lack of resources,
especially funding and space.
The second pilot study (2005-2006) came from an external source. That is,
Barbara Lovitts, a researcher/program evaluator in Maryland, contacted deans at
research institutions in geographically distributed states. She invited WU to
participate on a research project funded by the Alfred P. Sloan Foundation.
Specifically, the research dealt with dissertation performance expectations. As kind

fate would have it, when our graduate dean asked if I would like to manage the
project on our campus, in addition to your other responsibilities, fortunately I said
yes. This study resulted in a book (Lovitts, 2007) related to dissertation
performance expectations and rubrics. Two pilot studies, then, preceded the
instrument design for my dissertation study; the instruments, methods, and procedures
that I learned about through those two pilot studies informed my study design.
Case-Study Design
In order to pursue my four research questions, I chose to use case-study
methods (Yin, 2003). While I had considered other alternativesethnographic
research and ethnographic case studiesI chose in-depth case studies. My goal was
to identify a design in which I could capture directly the comments of the students
themselves, as I wanted a student-centered study. Because of the dearth of research
related to doctoral student success as discussed in Chapter 2 and because of the
NRCs (1996) recommendations for researchers and scholars to study specific
programs at specific research sites, I focused on two specific social science programs
at WU, political science and geography.
I selected a case-study research strategy because a case study is the best
research strategy to use when how (How can doctoral students succeed?) or why
(Why are doctoral students hindered in their success?) issues are the focus, when the
study does not require control of behavioral events, and when the topic focuses on
contemporary events (Yin, 2003). Additionally, because a case study is an empirical

inquiry that investigates an existing phenomenon within its real-life context (in this
case an academic context), especially when the boundaries between phenomenon
(some doctoral students dropping out of their programs) and context (the doctoral
program) are not clearly evident (Yin).
My case studies are predominantly exploratory and descriptive. They are
exploratory because little is known about student perspectives on American PhD
program experiences (CGS, 2004; Golde, 1996; Lovitts, 2001), little is known by
discipline and institution (NRC, 1996). By selecting two disciplines at one institution,
then, I am exploring the topic using case studies as a strategy for approaching my
research. They are descriptive because I examine, partly by description, embedded
contextual aspects of the programs, and describe specifics related to individual
student facilitators and hindrances.
Consistent with case-study methods, my study employs triangulation, a
process by which multiple sources of information are sought and investigated in order
to compare and contrast findings. In so doing, I could thus build a story (Krathwohl,
1997; Spradley, 1979) from my findings and interpret them. If findings contrasted, I
rechecked them. If multiple sources did not contradict one another or others, I
considered that aspect of the story confirmed.
Site Selection
I selected one site for several reasons, but the predominant reason was
accessaccess to the campus, to faculty, to students, and to staff. I was familiar with

the campus, a research-comprehensive campus, which served my interests well
because of the strong research focus of the campus. I also wanted access to programs
with large enough PhD cohorts that I would have sufficient student participation in
the study, and sufficient variability among students to examine interview responses
from multiple individuals.
The single study site is Western University (WU), which is a member of the
Association of American Universities. With a graduate student population of
approximately 4,500 (both masters and doctoral), WU hosts students from nearly
every comer of the globe who conduct research in academic departments, programs,
institutes, and centers. Embedded within WU are doctoral programs in more than 50
Although both of my focus disciplines (geography and political science) are
within the social sciences, each disciplinary culture is quite distinct. That is, each is
situated within well-established knowledge boundaries (what counts as knowledge),
evolved within an historic processes (evolution of the discipline), and is guided by
specific principles and practice, major streams of research, agreed-upon top-tier
publications, and annual conferences specific to the discipline (Donald, 1995;
Hawley, 1993). As such, each discipline represents a set of norms, values, and an

understanding about the nature of reality as filtered through that discipline (Bruner,
1990, 1996; Donald).
Because the department/program is the heart of the PhD, is a doctoral
students academic community, and is the nexus of the discipline and the institution
(Golde & Walker, 2006, p. 8), my research examined student processes within these
programs as well as the program itself. Also because of this, one of four sections of
my interview guide contained questions related to the program.
As I designed my study, I examined elements that I wanted to incorporate into
the semi-structured interview. I started with research questions and the purpose of
each question (Table 3.1, p. 73). I created a preliminary matrix of research questions
and possible interview questions. I then developed a 43-question semi-structured
interview guide to allow for both similar interviewing structure and open-ended
questions and elicitation of responses (Spradley, 1979). My interview guide
(Appendix A), based on prior research as found in the completion and non-
completion literature, included four sections in this sequence: (a) doctoral process and
leadership, (b) student characteristics (CGS, 2004), (c) program structure and culture
including implicit and explicit elements (Lovitts, 2001; Golde, 1998), and (d) career
plans and demographics. Appendix D summarizes some elements of the preliminary
matrix and associates research questions with semi-structured interview questions.

Table 3.1
Research Questions with Purpose
Research Question Question Purpose
From the students perspectives, what facilitates
PhD completion in Geography and Political
From students perspectives, what hinders PhD
completion in Geography and Political Science?
What is implicit in the students PhD process that
can be made more explicit to facilitate students
What barriers to completion could be reduced
from students &/or the institutions
To understand features of each PhD program, such as how
program dept & PhD students interact & communicate
To understand how 2 different PhD programs compare/
contrast re: assisting students toward PhD completion
To understand what kinds of barriers to success students
To understand how 2 different PhD programs compare or
contrast in how they slow students progress to degree
To understand what specifically is unclear to students in
their process of earning a PhD
To understand how the PhD process can be made more
transparent to students
To understand how the PhD process could be simplified to
facilitate degree completion; specifically, how programs
might be improved
This interview guide also served as a way to initiate and then revisit certain
topics. For example, early in the interview, I asked students what they thought
facilitated and hindered success. Later, I asked them again but asked them to list the
facilitators and hindrances in their perceived order of importance. Doing this helped
me aggregate responses as well as identify patterns and themes.
I organized the four sections of interview questions around conceptual themes
(doctoral process and leadership, student characteristics, program and program
culture, and career plans and demographics) so that I could continually refer back and
compare/contrast interview responses to my framework and model. I also found it
useful to compare my incoming data with my research questions and hypotheses.

Such recursive review assisted me in discovering if the study elements (research
questions, hypotheses, theory, concepts, findings) were congruent.
Data Collection
The main sources of data were students, faculty, program staff, and myself.
Sources of evidence included interviews, documentation, archival records, and direct
observation. Documentation was exclusively in the form of emails. Archival records
included graduation and outplacement records, program documents, information from
websites, and various announcements. Direct observation consisted of photographs,
maps, and drawings that I made and various fieldnotes. Collection methods are
described in the text below. Table 3.2 (p. 75) summarizes data sources, sources of
evidence, and collection methods used for each.
Several months of fieldwork preceded the conduct of interviews and
document collection. During these months, I spent time in the departments of interest
and nearby to observe and listen to student comments. I shagged around
(LeCompte & Schensul, 1999a) before I began my study. For example, I sat on the
steps of both the geography and the political science buildings, simply observing
students and listening to their conversations as they walked in and out of the building.
I spent time in a campus coffee shop next to the political science building and heard
some of the students comments about their activities. I also examined the Web sites
of the two programs. These sites allowed me to understand the breadth and depth of
the academic activities within the department, admissions expectations, as well as

recent and current research conducted by faculty and doctoral students within the two
PhD programs.
Table 3.2
Data and Evidence: Sources and Collection Methods
Data Sources Sources of Evidence Collection Methods
Students Interviews Documentation: emails Direct Observation: field notes Record electronically and transcribe interviews Exchange emails with students Take field notes during interviews
Faculty Interviews Documentation: emails Direct Observation: field notes Archival Records: graduation records Record electronically and transcribe interviews Exchange emails with faculty Take field notes during interviews Collect graduation records
Program staff Unstructured interviews: notes of conversations Documentation: emails Archival Records: program documents, outplacement records Make notes of conversations Exchange emails with program staff Collect copies of and take notes from documents and records
Self Archival Records: Website printouts and notes from website, seminar program announcements, commencement program announcements Direct Observation: Fieldnotes describing site, seminars, student behavior, and program activities, photos, maps, and drawings, journal of reflections and reactions Search, collect, print or make notes on website Collect, copy announcements & handouts Observe and take field notes of site, seminars, students, activities Take photographs Make drawings, draw or collect maps Keep personal journal
This fieldwork resulted in fieldnotes (Sanjek, 1990), which included such
items as what I found in display cases or impressions of interactions that I described
and recorded in my field notebook. I recorded observations of the physical
environments and working conditions in which PhD students conducted research. I
hung out or shagged around (LeCompte & Schensul, 1999a) campus student
gathering areas, such as a nearby coffee shop and the student union. I listened for

anything that I thought might relate to my study and noted it in my fieldnotes
(Sanjek); I include several of those details in Chapters 4 and 5. Daily, I reviewed and
re-reviewed my data as I worked through it inductively and deductively, seeking to
discover categories of responses and, ultimately, themes, as illustrated in an example
from my fieldwork journal:
Geography staff is small, but those in the main office, especially one,
are eager to help. I used this eagerness to [my] advantage because I
wanted access to graduation records. The only way to access them was
with assistance from staff, and Im grateful that they were so eager to
help me, such as volunteering to make copies of previous Friday
Colloquia programs for me. Actually, the Colloquia seems to be
emerging as a theme because it is important to the department, the
staff seem to be proud of the seminar program, and the doctoral
students continue to mention them as important for them [the students]
to see prospective faculty give job-talks, to see how their advisor and
other faculty participate, and to initiate participation themselves.
While I was collecting and recording data over the course of six months, I was
also systematically observing and examining the data for patterns and relationships. I
also shagged around in the two case-study program buildings in order to see and hear
faculty-student and/or student-student interactions, to immerse myself in the
disciplinary cultural milieu as much as possible prior to the interviews. This
background proved useful because, when I began interviewing students and faculty, I
was not interviewing them blind; that is, without having a sense of them in the
context of their environment. Because of these activities, I could conduct the
interviews less as a stranger and more as someone who understood aspects of the

I attended departmental colloquia, doctoral discussion groups, and a
recruitment presentation, and I attended one or two of the students dissertation
defenses. I observed student labs, the hallways, the departmental areas such as
displays, and visiting speaker/reception events. I listened to student discussions and
noted cultural-specific language, cultural artifacts, the departments Web sites, and
handouts. These documents and observations served as data to help me triangulate
other data I collected. For example, contrasts I discovered in each of the two
departments environments reflected, and later reinforced my early impressions of the
program cultures. For example, the stark emptiness of the political science hallways
(few people, no displays, no art) contrasted with the casual, laughter-filled, friendly,
and comfortable (inclusion of chairs, tables, benches, bulletin board and cabinet
displays) hallways of the geography department. I return to these observations in later
I introduced myself to staff so that I would not be a strange face in the
building. Sometimes I would sit in a departmental hallway chair or bench taking notes
and remain relatively unobtrusive. Sometimes, I simply drew a picture or made
abbreviated notes. For example, I drew a basic floor plan of each floor in order to
clarify which areas belonged to students and which to faculty. I also sketched items
that were posted or hung on walls and made lists of what I saw displayed in display
cases. As the study progressed, I focused more on the interviews, and on analysis and
synthesis, than on fieldnotes. The latter eventually served as a third point of

triangulation (Yin, 2003), the others being the interview data and the documents. As
detailed more in Chapters 4 and 5, these early impressions and students responses
seemed to reinforce one another.
Participant Selection
For this study, I originally hoped to interview 15 students, but I interviewed a
total of 24 (15 in political science, 9 in geography); nine faculty (4 from political
science, 5 from geography); and two staff members (one from each discipline). While
I selected case-study methods, ethnography informed this study, through its emphasis
on cultural interpretation (Geertz, 1973), thick description (Geertz, 1983; Wolcott,
2001), inductive and deductive analysis (Spradley, 1979), as well as the use of semi-
structured interviews (LeCompte & Schensul, 1999b), and fieldnotes (Sanjek, 1990).
Determining who I would interview required several steps. I sent emails to the
department chairs and when they responded set up a meeting with each chair to
discuss my research intentions and my need for their assistance in various ways.
During my meetings with the two chairs, I asked each of them which other faculty
they would recommend I interview, and they recommended the previous chair, the
graduate chair, and suggested I email several others, all of which I did. This was the
same for both programs. When I grew familiar with a department and its activities, it
was clear that the staff member who worked with the PhD studentsthe graduate
assistantwas a key contact in order to access student records. While I spoke

casually to several others, one staff member (Kara, geography) was key to my work.
(All names are pseudonyms to protect confidentiality.)
In the Department of Geography, for example, I established a relationship
with both Jim Oakley (current Geography Chair) and Bill Peterson (Graduate Chair).
I scheduled meetings with them, discussed my study with them, and received their
endorsement to proceed with my study. In the Department of Political Science, I
emailed the current chair and did not meet with him. I met with Paul Mason (previous
department Chair, geography), and David White (Graduate Director), who also
endorsed my study.
In addition to meeting with current department and graduate chairs, I met with
their former position counterparts, because I thought that their previous experiences
as chair would enrich my understandings of the programs structure, culture, and
political environment. At these meetings, we discussed how I would approach
potential participants and we agreed that the department would first contact
prospective doctoral student participants. After that, I would send a follow-up email
to those who expressed interest. With their concurrence, I drafted an email from the
chairs to potential student participants and sent this to the chairs who then approved
the email text.
After this methodology was decided, the chairs instructed their staff to send
me lists of eligible PhD student names. I reviewed the list of PhD students with the
chairs and sent the approved email to potential PhD student participants. With all

Human Research Committee (HRC) proposals and Consent Forms approved, I
selected the students from both departments.
I wanted to select students who were in different stages of their PhD (Bowen
& Rudenstine, 1992), as well as those who were finished with their coursework
(Lovitts, 2001). Working with the graduate and departmental chairpersons in
geography and political science, I identified potential post-coursework participants
for this study. Because early PhD coursework is not highly differentiated (Lovitts)
from coursework at the masters level (or in some cases at the undergraduate level), I
focused on post-coursework students for this study. In this regard, I identified four
stages of student progress post-coursework: (a) preparing for comprehensives and
may or may not have a research topic; (b) post-comprehensives with topic selected
and study launched, (c) gathering and/or analyzing data, (d) writing up the data/pre or
post-defense/post-final defense rewriting.
Conducting Interviews
My original intention was to identify and interview a total of approximately
15 student participants in both programs (seven or eight in each), with two
participants in each of four post-coursework stages as of Fall 2007. However,
participants did not fall neatly into these stages, as I discuss in Chapters 4 and 5. The
primary data that I ultimately used for this study were the interview data from 24
students, nine faculty, and two staff members. Although my plan was to schedule
only one semi-structured interview per day in the morning so that the afternoon could

be set aside for listening to the tape, reviewing and consolidating notes, and making a
backup, security copy of the tape. I often confirmed two interviews per day and my
consolidation activities occupied the following day. To minimize participant concern
about being taped (and my time as a researcher), I contacted each participant by email
prior to conducting an interview in order to reconfirm time, location, and the fact that
I would tape the interview. I did not encounter any interviewee concerns about being
Length. Interviews averaged 45 minutes to one hour in length. I promised the
student that the interview would not be longer than 45 minutes. However, I also asked
for an opportunity to re-contact her or him if we exceeded that time, and all of them
agreed to this condition. Nearly all of the interviews reached 45 minutes, but the
students decided to continue at that time and not schedule a follow-up interview. The
longest interview lasted one and one-half hours and the shortest was 40 minutes.
Notwithstanding the in-depth nature of these interviews, I did re-contact several
students by email to clarify statements from their transcripts. Throughout the data
analysis process, I remained in email communication with about half of my study
interviewees, including faculty, staff, and students. I did not remain in
communication with the ones who had or were preparing to graduate soon.
Privacy. One criterion for the semi-structured interviews was privacy, so that
the student did not feel self-conscioussuch as feeling too visible to other students
and so that the student felt secure that the process would be confidential. Interviews

usually occurred in a closed conference room at the student union or in a students lab
cubicle. When I interviewed faculty and staff, I met with them in their offices.
Faculty interviews. In both departments, faculty either rotate service as chair,
being graduate chair, or having other major roles in the department such as serving as
outplacement director. All nine faculty members were eager to participate in this
study, gave me approximately one and one-half hours of interview time apiece, and
gave considered responses. Oakley requested a copy of my dissertation in order to
understand how students perceive their experiences in the Department of Geography
PhD program.
The nine faculty membersfour from political science and five from
geography)are tenured and have been at WU for at least five years. Both staff
members have been graduate program assistants at WU for at least 13 years (Kara,
geography), with Elsa (political science) having worked at WU for nearly 20. Karas
position is responsible for only PhD students and Elsas position manages some day-
to-day operations for the department chair as well as serves as a resource for graduate
students, both masters and doctoral. Table 3.3 summarizes the faculty interviewed
from each program.

Table 3.3
Faculty and Staff Interviewed
Geography Faculty and Staff Political Science Faculty and Staff
Role and (Number of Years at WU) Role and (Number of Years at WU)
Jim Oakley, current chair (13 yrs overall, 2 as
chair, and associate graduate chair for 3 yrs)
Kent Farley, previous chair for 3 yrs and
graduate chair for 2 (8 yrs overall)
Bill Peterson, graduate chair for 3 yrs (11 yrs
Bill Mark, located in both campus department
and institute (17 yrs)
Alice Chan, Assistant Professor (5 yrs)
Kara, Graduate Program Assistant (13 yrs)
David White, current director of graduate
studies (4 yrs)
Paul Mason, previous chair (28 yrs)
Susan Campbell, Outplacement Director
(30 on WU campus overall, 2 as placement
David Bowman, previous director of
graduate studies; transferred to another
institution in Fall, 2008 (11 yrs)
Elsa, Graduate Program Assistant (20 yrs)
Student interviews. Before I contacted a student, the chairs sent these eligible
students an approved email that served as an introductory cover letter (Appendix
B). Included in this two-paragraph cover letter was a brief description of the study as
well as an invitation to participate. If a student was interested, the student emailed me
at the address included in the cover letter. Upon hearing from a student, I responded
immediately and established a mutually agreeable meeting time and place for the
After emailing approximately 18 students in geography and 20 in political
science in January 2008,1 confirmed participation of 15 students in political science
and 9 in geography for a total of 24 participants. When a student expressed a