Citation
Adjusted measures of district and school performance

Material Information

Title:
Adjusted measures of district and school performance a social justice study of Colorado's Latino students
Creator:
Broer, Ashley J. Raduege
Place of Publication:
Denver, Colo.
Publisher:
University of Colorado Denver
Publication Date:
Language:
English
Physical Description:
xxiv, 223 leaves : ; 28 cm.

Thesis/Dissertation Information

Degree:
Doctorate ( Doctor of Philosophy)
Degree Grantor:
University of Colorado Denver
Degree Divisions:
School of Education and Human Development, CU Denver
Degree Disciplines:
Education and Human Development
Committee Chair:
Muth, Rodney
Committee Members:
Davis, Alan
Moskowitz, Karla Haas
Palaich, Robert

Subjects

Subjects / Keywords:
Hispanic American students -- Colorado ( lcsh )
Social justice -- Colorado ( lcsh )
Educational evaluation -- Colorado ( lcsh )
Educational evaluation ( fast )
Hispanic American students ( fast )
Social justice ( fast )
Colorado ( fast )
Genre:
bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

Notes

Thesis:
Thesis (Ph. D.)--University of Colorado at Denver and Health Sciences Center, 2007.
Bibliography:
Includes bibliographical references (leaves 212-223).
Statement of Responsibility:
by Ashley J. Raduege Broer.

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:
166881796 ( OCLC )
ocn166881796

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Full Text
ADJUSTED MEASURES OF DISTRICT AND SCHOOL PERFORMANCE:
A SOCIAL JUSTICE STUDY OF COLORADOS LATINO STUDENTS
by
Ashley J. Raduege Broer
B*S., Eastern Illinois University, 1999
M.A., University of Colorado at Colorado Springs2001
A thesis submitted to the
University of Colorado at Denver and Health Sciences Center
in partial fiilfiltment
of the requirements for the degree of
Doctor of Philosophy
School of Education and Human Development
2007
.,r


2007 by Ashley J. Raduege Broer
All rights reserved.


This thesis for the Doctor of Philosophy
degree by
Ashley J, Raduege Broer
has been approved
Rodney Muth
. ijU , ! b, 2{' U
December 15, 2006


Raduege Broer, Ashley J+ (Doctor of Philosophy, Educational Leadership and Innovation)
Adjusted Measures of District and School Performance: A Social Justice Study of
Colorados Latino Students
Thesis directed by Dn Rodney Muth
ABSTRACT
The reauthorization of the No Child Left Behind Act of 2001 has increased
attention to student achievement. Specifically, the challenging demographics in
Colorado make attention to Colorado's Latino American students a critical issue.
Colorado's population of Latino American students is now the largest and fastest
growing ethnic minority group in the state* Although it is necessary to hold
educators accountable for students who are not achieving, it is inappropriate to
make judgments simply from raw test scores. Given that educators can only
control the school system, it makes sense to concentrate energies here.
This quantitative study was designed using Adjusted Performance Measures
(APM) to determine whether Colorado school districts and secondary schools were
performing at predicted levels. APM allow researchers to control for factors
beyond districts* power, while holding districts accountable for factors within their
power. The first part is a district-level analysis, comparing the 178 school districts
in Colorado* Secondary schools within two metro-area school districts arc
compared in the second part of the study.
Once the APM were determined, the Educational Quality inputs were
compared between the highest and lowest performing districts and schools.
Conclusions were drawn for all Colorado students with additional emphasis on
Latino Students,
This abstract accurately represents the content of the candidate^ thesis, I
recommend its publication.
Signed
Rodney Muth


DEDICATION PAGE
My completed dissertation is dedicated to my husband, Chad. His love gave me
the courage to persevere while he provided me with the time needed to complete
this degree. Over the past three years, many moments have been postponed so I
may achieve this goal. Now, at the conclusion of this process, I look forward to
focusing on new ambitions. Thank you for believing in me.
Additionally, this dissertation is dedicated to my parents, Hany and Julee Raduege.
My parents have always believed in the power and importance of education. They
chose to raise an open-minded and determined daughter even though it often
proved to be more challenging. Thank you for the foundation from which I have
built my life.


ACKNOWLEDGMENT
Many people have contributed to the completion of this dissertation. First and
foremost, I would like to acknowledge my committee members who encouraged
and stretched me through this program* My Chair, Rod Muth has provided endless
hours of discussion, guidance, and encouragement His experience and vision were
instrumental throughout my journey. Bob Palaich allowed me a glipse of the
educational policy world and helped me to design a valuable study. Alan Davis
contributed his understanding of Latino American students and research expertise.
Karla Haas Moskowitz has been a mentor who has an unrivaied> innovative passion
for education* Thank you, to my entire committee, for all of your time and energy
spent on helping me succeed*
I would also like to thank Mountain View Public Schools for believing in the value
of my research. Having access to the data elements contributed greatly to the depth
of my study.
Finally* I would like to acknowledge the many people who played a role in my
getting to this point. Specifically, I would like to express my gratitude to Marcia
Muth for offering writing workshops and providing structure through the
dissertation process. Also, having a group of colleagues to share the doctoral
experience has been invaluable* I would like to thank Paula Gallegos and Kristen
Kaiser Atwood^ in particular, for their encouragement.


TABLE OF CONTENTS
Figures ..................................................... xvi
Tables ......................................................xvii
CHAPTER
1.INTRODUCTION................................................... 1
Critical Attention Needed................................. 2
Study Rationale......................................... 2
An Achievement Gap...................................... 6
Shifting Policies.........................................8
The Model Fit...............................................8
Study Introduction.........................................10
Theoretical Framework......................................11
Looking Through the Social Justice Lens..................11
Appreciating the Complexity............................ 12
Involving the Privileged.................................13
Empowering the Marginalized..............................14
Study Implications.........................................15
Study Overview........................................... 16
Guiding Questions........................................17
Clarifying the Variables.................................17
viii


District-Level Analysis................................18
School-Level Analysis...........................*......20
Study Methodology.........................................21
Study Limitations.........................................22
Concluding Introductory Remarks......................... 23
2. LITERATURE REVIEW...............................................25
An Achievement Gap..........................................26
A Snapshot of Denver5 s Latino American Population..........31
Complexity of the Issue.....................................31
Differences Among Generations of Latino Americans...........32
Colorados Residents........................................33
Donning a Cap and Gown.................................... 34
Colorados Graduation Data................................35
Parent Involvement.................................... 37
School Culture.........-...................................38
Generational Immigration Patterns.........................39
A Leader with Laser-Like Focus............................41
Teacher Quality.................*..........................42
Years of Experience..................................... 42
Absences..................................................43
Salary....................................................44
ix


Degree in Area...........................................45
Revenue Expenditures..................................... 45
Instructional Dollars....................................46
Non-Instractional Dollars................................47
Revenue Sources............................................47
Per Pupil Revenue........................................48
Calculating Funding Allowances...........................49
Pupil Count............................................49
Total Per-Pupil Funding................................50
At-Risk Funding........................................51
On-Line Funding........................................51
Colorados Funding System..................................52
Local Share..............................................52
Property Taxes.........................................53
Specific Ownership.....................................53
State Share..............................................53
Other Funding............................................54
Concluding Remarks.........................................55
3. METHODOLOGY....................................................56
Data Collection............................................57
x


District-Level Analysts.......................................58
School Environment.........................................60
District Revenue Sources...................................60
Revenue Expenditures .....................................61
Teacher Quality .........................................61
Ratio or Professionals to Students.........................62
Student Characteristics....................................63
CSAP Scores......................................... 63
School-Level Analysis.................................... 04
Teacher Quality............................................65
Ratio of Professionals to Students.........................65
Leadership Experience.................................. 65
Student Characteristics....................................66
CSAP Scores...................*...........................66
District Membership Differences *..........................oJ
Data Sources..................................................o 7
District-Level Data Sources..................................o7
School Environment....................................... 68
District Revenue Sources...................................69
Revenue Expenditures.......................................69
Teacher Quality............................................70
xi


Ratio of Students to Professionals.....................71
Student Characteristics................................71
CSAP Scores............................................72
School-Level Data Sources.................................73
Teacher Quality........................................74
Ratio of Students to Professionals.....................74
Leadership Experience..................................75
Student Characteristics................................75
CSAP Scores..................*........................77
Data Analysis...............................................77
Units of Analysis.........................................78
Principal Components Analysis.............................78
Multiple Regression.......................................79
4. DISTRICT-LEVEL FINDINGS.........................................81
Adjusted Performance Measures...............................81
Principal Components Analysis...............................84
Uncontrollable District Factors...........................84
School Environment........................................87
Teacher Quality......................................... 89
Ratio of Professionals to Students........................90
xii


Regression Equation..........................................92
District Reading APM, All Students1 Performance............94
District Reading APM, Latino American Students ^
Performance.............................................97
District Math APMAll Students Performance...............103
District Math APMLatino American Students
Performance............................................108
Interpreting the Residuals..................................Ill
Analyzing District Differences..............................114
District Setting and APM Categories.......................115
Interpreting the APM Residual Categories..................115
Factors Within District Control........................121
Factors Beyond District Control........................123
District-Level Conclusions................................124
5, SCHOOL-LEVEL FINDINGS..........................................126
Principal Components Analysis...............................127
Uncontrollable School Factors.............................128
Teacher Quality...........................................130
Ratio of Students to Professionals........................132
Regression Equation.........................................134
School Reading APM, All Students' Performance.............136
xiii


School Reading APM, Latino American Students1
Performance.............................................140
School Math APM, All Students Performance.............. 145
School Math APMLatino American Students
Performance.............................................147
Interpreting the Residuals.................................15]
Analyzing School Differences.............................. 154
School Location and APM Categories........................155
Interpreting the APM Residual Categories..................155
Factors Beyond School Control...........................155
Factors Within School Control..........................157
School-Level Conclusions....................................165
6. IMPLICATIONS AND CONCLUSIONS....................................167
Conclusions of Findings.....................................168
District-Level Conclusions................................169
School-Level Conclusions..................................173
Study Limitations...........................................180
Future Studies..............................................181
The Need to Improve Education...............................184
Tackling Secondary School Reform..........................185
Social Justice Suggestions for Colorados Schools...........186
Professional Teachers.....................................186
xiv


Essential Leadership
18S
Smaller Schools.........................................189
Include the Family......................................190
Student Accountability..................................191
Education Expectations..................................192
P-16.................................................193
Curriculum Standards.................................194
Literacy, Literacy, Literacy.........................195
Acknowledge the Changing Society........................195
Final Thoughts............................................196
APPENDIX
A................................................................198
B................................................................199
C................................................................200
D................................................................201
E...............................................................202
F................................................................203
G................................................................204
H................................................................205
I................................................................206
xv


J.....................................................207
K.....................................................208
L.....................................................209
M.....................................................210
N.....................................................211
REFERENCES ................................................212
XVI


LIST OF FIGURES
Figure
LI District-Level Educational Input Variables.........................19
L2 School-Level Educational Input Variables...........................21
3.1 District-Level Educational Input Variables.........................59
3.2 School-Level Educational Input Variables...........................64
4*1 Factors Aifecting School Districts.................................82
4.2 District-Level Adjusted Performance Measure Equation...............83
4.3 District Regression Equation, Part One.............................93
4.4 District Regression Equation, Part Two.............................94
5.1 School-Level Educational Input Variables..........................127
5.2 School Regression Equation, Part One..............................134
5.3 School Regression Equation, Part Two..............................135


Table
LIST OF TABLES
LI Colorado pupil coxintsby race/ethnicity.................................3
1.2 Percent of Colorado pupils by race/ethnicity............................4
1.3 Education attainment by people 25 years and older.......................5
\A Median household income by race.........................................6
2.1 2002 9th grade DPS students7 reading proficiency levels over
3 years..............................................................27
2.2 2002 10th grade DPS students' reading proficiency levels over
3 years..............................................................27
2.3 2002 9th grade DPS students? writing proficiency levels over
3 years..............................................................28
2.4 2002 10th grade DPS students5 writing proficiency levels over
3 years..............................................................28
2.5 2002 9th grade DPS students' math proficiency levels over
3 years .............................................................29
2.6 2002 10th grade DPS students, math proficiency levels over
3 years..............................................................29
4.1 Uncontrollable factors total variance explained........................86
4.2 Uncontrollable factors rotated component matrix........................86
4.3 School environment total variance explained............................88
4.4 School environment rotated component matrix............................88
4.5 Ratio of professionals correlation matrix..............................91
4*6 Ratio of professionals total variance explained........................91
xviii


4.7 Ratio of professionals rotated component matrix...........................92
4.8 Means, standard deviations, and intercorrelations for all students
CSAP reading scores and predictor variables, part 1..............*......96
4.9 Simultaneous multiple regression analysis summary for all students
CSAP reading scores and predictor variables, part 1.....................96
4.10 Means, standard deviations, and intercorrelations for all students
CSAP reading scores and predictor variables, part 2.....................98
4.11 Simultaneous multiple regression analysis summary for all students
CSAP reading scores and predictor variables, part 2.....................99
4.12 Means, standard deviations, and intercorrelations for Latino American
students CSAP reading scores and predictor variables, part 1............100
4.13 Simultaneous multiple regression analysis summary for Latino American
students CSAP reading scores and predictor variables, part 1............100
4.14 Means, standard deviations, and intercorrelations for Latino American
students CSAP reading scores and predictor variables, part 2............102
4.15 Simultaneous multiple regression analysis summary for Latino
American students CSAP reading scores and predictor variables,
part 2..................................................................104
4.16 Means, standard deviations, and intercorrelations for all students
CSAP math scores and predictor variables, part 1........................105
4.17 Simultaneous multiple regression analysis summary for all students
CSAP math scores and predictor variables, part 1........................105
4.18 Means, standard deviations, and intercorrelations for all students
CSAP math scores and predictor variables, part 2........................107
4.19 Simultaneous multiple regression analysis summary for all students
CSAP math scores and predictor variables* part 2........................108
xvijj


4.20 Means, standard deviations, and intercorrelations for Latino
American students CSAP math scores and predictor variables
part 1....................................................................109
4.21 Simultaneous multiple regression analysis summary for Latino
American students CSAP math scores and predictor variables,
part 1....................................................................110
4.22 Means, standard deviations, and intercorrelations for Latino
American students CSAP math scores and predictor variables,
part 2....................................................................112
4.23 Simultaneous multiple regression analysis summary for Latino
American students CSAP math scores and predictor variables,
part 2....................................................................113
4.24 District-level residual values............................................114
4.25 Reading all APM divided into five categories..............................116
4.26 Reading Latino American APM divided into five categories..................117
4.27 Math all APM divided into five categories.................................118
4.28 Math Latino American APM divided into five categories....................119
4.29 APM residual category means...............................................120
4.30 Factors within school districts' control..................................122
4.31 Math all professionals to student ratios..................................122
4.32 District spending on other expenses.......................................123
4.33 Factors beyond district control...........................................125
5.1 Student characteristics total variance explained..........................129
5.2 Student characteristics component matrix..................................129
5-3 Teacher quality total variance explained..................................131
xix


5.4 Teacher quality rotated component matrix.................................131
5.5 Ratio of professionals to students total variance explained..............133
5.6 Ratio of professionals component matrix..................................133
5.7 Means, standard deviations, and intercorrelations for all students1
CSAP reading scores and predictor variables, part 1...................137
5.8 Simultaneous multiple regression analysis summary for all students4
CSAP reading scores and predictor variables, part 1...................137
5.9 Meansstandard deviationsand intercorrelations for all students
CSAP reading scores and predictor variables, part 2...................139
5.10 Simultaneous multiple regression analysis summary for all students*
CSAP reading scores and predictor variables, part 2...................140
5.11 MeanSj standard deviations, and intercorrelations for Latino
American students1 CSAP reading scores and predictor variables,
part 1.......................................................141
5.12 Simultaneous multiple regression analysis summary for Latino
American students* CSAP reading scores and predictor variables,
part 1................................................................142
5.13 Means, standard deviations, and intercorrelations for Latino
American students' CSAP reading scores and predictor variables,
part 2.......................................................143
5*14 Simultaneous multiple regression analysis summary for Latino
American students' CSAP reading scores and predictor variables,
part 2.......................................................144
5*15 Means, standard deviations, and intercorrelations for all students5
CSAP math scores and predictor variables, part 1...................145
5.16 Simultaneous multiple regression analysis summary for all students'
CSAP math scores and predictor variables, part 1...................146
xx


5.17 Means, standard deviations, and intercorrelations for all students'
CSAP math scores and predictor variablespart 2....................148
5.18 Simultaneous multiple regression analysis summary for all students1
CSAP math scores and predictor variables, part 2...................149
5.19 Means, standard deviations, and intercorrelations for Latino
American studentsCSAP math scores and predictor variables,
part 1.............................................................150
5.20 Simultaneous multiple regression analysis summary for Latino
American students, GSA^P math scores and predictor variables
part 1.............................................................150
5.21 Means, standard deviations, and intercorrelations for Latino
American students' CSAP math scores and predictor variables,
part 2.............................................................152
5.22 Simultaneous multiple regression analysis summary for Latino
American students' CSAP math scores and predictor variables,
part 2.............................................................153
5.23 School-level residua] values.........................................153
5.24 Reading APM categorized by district membership.......................156
5-25 Math APM divided by district membership..............................157
5.26 Factors beyond schools controlreading..............................158
521 Factors beyond schools controlmath.................................159
5.28 Student ethnicityreading............................................160
5.29 Student ethnicitymath...............................................161
5.30 Student enrollment numbers...........................................162
5.31 Teacher quality findings
163


532 Ratio of professionals to student findings.................................164
5- 33 Leadership experience findings.............................................166
6A Factors within school districts control...................................170
62 Math all professionals to student ratios...................................171
6- 3 District spending on other expenses........................................172
6.4 School-level total student enrollment numbers..............................174
6.5 Teacher quality findings...................................................177
6.6 Ratio of professional to student findings..................................178
6.7 District-level conclusions.................................................182
6.8 School-level conclusions...................................................183
A Means, standard deviations, and intercorrelations for
uncontrollable factors..................................................198
B Means, standard deviations, and intercorrelations for
school environment......................................................199
C Means, standard deviations, and intercorrelations for
ratio or professionals..................................................200
D Means, standard deviations, and intercorrelations for
student characteristics..................................................201
E Means, standard deviations, and intercorrelations for
teacher quality.........................................................202
F Means, standard deviations, and intercorrelations for
ratio of professinals...................................................203
G District-level intercorrelations, Reading all..............................204
xxiii


H District-level intercorrelations, Reading Latino...............................205
I District-level intercorrelations, Math all.....................................206
J District'level intercorrelatioos, Math Latino..................................207
K School-level intercorrelations, Reading all....................................208
L School-level intercorrelations, Reading Latino.................................209
M School-level intercorrelations, Math all.......................................210
N School-level intercorrelations, Math Latino....................................211
XXIV


CHAPTER 1
INTRODUCTION
In June 2003, the United States Census Bureau reported that Latino
Americans had become the nation's largest minority group with 38.8 million
people, surpassing Black Americans by half a million people (Cavanagh & Lopez,
2004; Chapa & Rosa, 2004). Additionally, the United States Latino American
population is a very young population. More than 33% of Latino Americans are
under the age of 18, compared with only about 25% of the non-Latino American
population (Chapa & Rosa, p.136). Currently, 14.4% of White Americans are 65
years old and older, while only 5.1% of Latino Americans are in the same age
range (U.S. Census Bureau, 2003). These statistics indicate that the Latino
American population will continue increasing over time while the White American
population decreases. As this population shift transpires and Latino Americans1
financial base becomes more secure, the contribution to the American economy and
society in general will grow.
1


Critical Attention Needed
Attention to Colorado^ Latino American students is critical, Colorado's
population of Latino American students is now the largest and fastest growing
ethnic minority group in the state (Besnette & Schoales, 2004; Hernandez &
Nesman, 2004; Suro, 1999; Tatum, 2003; Weiner et al., 2000), Since 1990, the
Latino American population has increased by more than 57%, increasing almost
10% alone between 2000 and 2002 (Chapa & Rosa, 2004). According to the
October 2004 count in Colorado (see Table \A \ 201,016 Latino American
students, 45,127 Black American students, and 487,056 White American students
were enrolled in Colorado schools (Colorado Department of Education, 2004).
In relation to the other ethnic groups (see Table 1.2), Latino American
students increased by 8.6% since the ] 994 count and the Black American
population increased by 0.5%, whereas White American students decreased by 10%
(Colorado Department of Education), By 2020, Latino Americans are expected to
make up 20% of all United States children (Weiner et al,). If current trends
continue, Black and Latino American students will become the majority in
Colorado schools.
Study Rationale
First, studying this population is critical because today they may be an
underserved minority, but soon they will become an undersferved majority of our
2


Table 1,1
Colorado Pupil Counts by Race/Ethnicity
Racial/Ethnic Group Pupil Count October 2004 Pupil Count October 1994 Count Change 199410 2004 Percent Change 1994 to 2004 Pupil Count October 1984 Count Change 1984 [o 2004 Percent Change 198410 2004
American Indian 9, 048 6,467 2,581 39.91% 3,816 5,232 137.U%
Asian American 24,410 15,956 8,454 52,98% 10,505 13,905 132,37%
Black American 45,127 34,425 10*702 31,09% 25,384 19,743 77,78%
Latino American 201,016 112,890 88126 78.06% 81,371 119,645 147.04%
White American 487,056 470,783 16,273 3,46% 424,351 62,705 14,78%
Total 766,657 640,521 126,136 19.69% 545,427 221230 40.56%
Note^ From Colorado Student Assessment Program (Etenver Public Schools, 2004).
population. By increasing the achievement levels for Latino American youth,
educators will increase the achievement of America's schools and may even
produce more adequate educational experiences for other traditionally marginalized
populations as well.
Second, improving Latino American students* success in school is
important for their personal economic well-being. It should be no surprise that
individuals who achieve higher levels of education will make more money in their
lifetimes. Of White Americans, 82.8% have at least a high school diploma
compared to only 53,1% of Latino Americans (see Table 1.3). According to the
3


Table L2

Percent of Colorado Pupils by Race/Ethnicity
Racial/Ethnlc Group 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 % Change 1994 2004
American Indian 1.0% 1.1% 1.1% 1.1% 1.2% 1.2% 1.2% 1.2% 1.2% 1.2% 1.2% +.2%
Asian American 2.5% 2.6% 2.6/ 2.7% 2.7% 2.8% 2.9% 3.0% 3.0% 3.1% 3.2% +.7%
Black American 5.4% 5.4% 5.5% 5.6% 5.6% 5.7% 5.7% 5.7% 5.7% 5.8% 5.9% +.5%
Latino American 17.6% 18.4% 18.8% 19.3% 19.9% 20.8% 22.0% 23.3% 24.3% 25.3% 26.2% +8.6%
White American 73.5% 72.5% 72.0% 71.3% 70.6% 69.5% 68.2% 66.8% 65.7% 64.5% 63.5% -10%
Total 00% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%
Note. From Colorado Student Assessment Program (Denver Public Schools, 2004).


Table 13
Education Attainment by People 25 Years and Older
Racial/Ethnic Group High School Graduate Some College, No Degree Bachelors Degree Or Beyond Total Graduates High School Or Beyond
Black American 35,1% 25.5% 13.6% 74.3%
Latino American 26% 17.9% 9.3% 53,1%
White American 33.9% 24.6% 24.3% 82.8%
Note. From Population Profile of the United States: 1997 (U,S, Bureau of the
Census1998).
U+S. Bureau of the Census (1998), in 1997 Latino American households had a
median income of $22,860 compared to White American households with a median
income of $35,766 (see Table L4). In fact, Latino Americans are more than twice
as likely as non-Latino Americans to live in poverty (Chapa & Rosa, 2004).
Third, because Latino Americans represent such a large and growing
percentage of the United States' population, their overall economic welfare affects
our entire society. At this point, children from immigrant families are more likely
than others to live in poverty, lag behind academically, and live in overcrowded
housing (Sadowski, 2004). If these numbers do not shift as the population
5


Table 1.4
Median Household Income by Race
Racial/Ethnic Group 1988 1989 1994 1995
Black American $21136 $22,225 $21623 $22,393
Latino American $26,227 $26,942 $24,085 $22,860
White American $37,077 $37,370 $34,992 $35,766
Note. From Population Profile of the United States: !997(V.S. Bureau of the
Census, 1998),
increases, the entire country will bear the consequences of these circumstances.
Finally and most importantly, focusing attention on a marginalized and currently
underserved population with the end result of increasing their educational
opportunities and successes is the right and moral thing to do* I fully realize that
some individuals do not agree with my value set and have arguments supporting
their own values. Although I respect their right to believe differently, I will not
acknowledge these arguments in my study.
An Achievement Gap
In the United States, an achievement gap exists between students of color
and their White American peers* Graduating Latino American twelfth grade
6


students1 reading skills are basically the same as White American 8lh graders'
reading skills (Olson, 2005a). On the 2002 Colorado Student Assessment Program
(CSAP), 73% of White American students but only 37% of Latino American
students scored either proficient or advanced (Colorado Children's Campaign,
2005)* Similar to the vast differences in CSAP scores, a disparity is apparent in the
types of courses completed by Latino American students and White American
students. For example, of the Latino American students graduating from Denver
high schools in 2003, only 29% had completed the coursework necessary to attend
college (Hayes & Polls, 2005),
Because an achievement gap has been identified through course selections
and test scores, policies need to be adjusted to address these issues* On a very
basic level, two approaches of reform exist: change the student or transform the
system. Traaitionally, when discussing problems such as the achievement gap, the
focus has been on fixing the student, rather than changing the school system*
Furthermore, researchers have often measured whether inputs are equal among
schools and school districts (Archer, 2005; Bainbridge, 2003; Darling-Hammond,
2003; Santos, 2004). By inputs, I am referring to system-controllable factors such
as revenue allocations, personnel allotment and assignment, and so forth. Currently
it is more likely to find studies measuring outputs, often by measuring student
performaTice.
7


Shifting Policies
Policy sets the context for districts, schools, administrators, and teachers to
educate students. By studying policy, it is easier to understand the current reality
of education. This study is a vehicle to establish whether the current reality in
Colorado's schools is conducive to Latino American students1 academic success.
Academic success, for the purpose of this study, is measured by students who
demonstrate their learning by earning scores of either advanced or proficient on the
CSAP lest* The findings may provide powerful tools from which to design future,
more far-reaching studies*
Given that educators can only control the school system, it makes sense to
concentrate energies here* Programs and reforms focusing on student-centered
issues have a tendency to fail because educators have limited influence on these
factors (Flannery & Jehlen, 2005; Haycock, 2001; Lopez, 2001; Montecel, Cortez,
& Cortez, 2004; Shreffler, 1998; West, 1993). To be accountable and responsible
for all students, educators need to identify interventions and develop effective
strategies to address what needs to be done differently in classrooms and schools
(Montecel et al*; Reid, 2004).
The Model Fit
Determining and selecting the most appropriate model for any study is
criticaL For this study, adopting the Adjusted Performance Measure (APM) model
8


made sense. Measuring district and school performance is a fairly simple approach
using the APM model.
The basic premise of the model is to use residuals, from multiple regression
equations, as quantifiable measurements in district and school performance. For
the regression equations, the dependent variables were CSAP test scores and the
independent variables included a variety of factors both within and beyond the
influence of the districts and schools. The beyond^influence factors were adjusted
for through the regression equation to focus the findings on the areas within the
scope of impact of districts and schools*
The APM model calculates t4the difference between the actual [district or]
school output and the output predicted from the regression equation, or the
estimated residual from the regression" (Stiefel, Schwartz, Rubenstein, & Zabel,
2005, p,18), This quantified performance data provides valuable information in
identifying differences between high performing districts and schools and those not
performing as well.
The information gathered from using the APM model is tied to student
achievement and provides valuable data for the social justice movement* Once
accurate determinations of how educators can best support achievement for all
students is made* these recommendations can be a mandatory minimum for all
districts and schools, rather than only applying to the institutions with the resources
to demand it.
9


Study Introduction
Determining whether districts serving Latino American students are
performing at predicted levels* based upon educational quality inputs, is the focus
of my dissertation. Currently, Latino American students perform at lower levels
than their White American peers (Colorado Children's Campaign, 2005; Hayes &
Polis, 2005; Olson, 2005a), Equity issues focus on like inputs available to all
students (Ladd & Hansen, 1999; Stiefel et al., 2005). On the other hand, adequacy
issues focus on like outputs (Ladd & Hansen). Adequacy could be illustrated as the
potential to bestow unequal inputs lo achieve equa! outcomes (Ladd & Hansen).
Examining APM at the district and school levels provides additional
infomiaUon in the quesl to increase educational opportunities for all students. No
Child Left Behind (NCLB) has increased attention to and scrutiny of the
performance of all students. Recently, reported dropout rates have been questioned
across the nation. In contrast, the school accountability data and dropout statistics
showing Latino American students and schools serving Latino American students,
performing at far lower levels, is not being disputed* In Chapter 2, these issues are
addressed in greater depth.
Another intention of the study is to eliminate variables that some
individuals consider key differences in education, while unearthing injustices in
areas of authentic inadequacy> The design of this study was grown from a social
justice lens. Social justice is a topic often explored through qualitative methods* I
10


have chosen the less typical path of delving into social justice through a
quantitative study of Colorado's districts and schools.
Theoretical Framework
As stated earlier, seeking to determine if Latino American students are
performing at predicted levels based upon districts1 inputs is the focus of my
dissertation. Three logical perspectives to frame this study include (a) the legal
basis for adequate education* (b) a financial focus which analyzes capacity or
adequacyor (c) socia justice. The chosen Jens affects my analysis, interpretation,
and final comments. While the first two perspectives are interesting and useful, the
intent of this study is to target social justice. Because I found districts and schools
serving larger populations of Latino American youth are performing below
adequate levels when using Adjusted Performance Measures, the issue of social
justice, as outlined in the following section, frames my recommendations for policy
makers and future studies.
Looking Through the Social Justice Lens
Social justice is a process, a goal, and for many a vision of the way the
world is meant to be (Bell,1997), Achieving social justice means creating and
maintaining a society that equally includes all groups in a system that continually
meets the needs of all participants (Bell; Neal & Moore, 2004). A socially just
system has an adequate distribution of resources and power* Maximizing society^
11


capacity to meet the needs of the whole society, while providing opportunities for
all individuals to realize and achieve their fullest potential, are basic principles of a
socially just system (Goodman, 2001; Parsons & Smelser, 1956). Further, social
justice allows all individuals to live with dignity in a safe and secure environment
(Bell; Denver Commission on Secondary School Reform, 2005; Goodman;
Walters, 1998),
Social justice means that all individuals have prospects for like
opportunities (Tatum, 2000). It constitutes the ability to send all children to a
school where they may be educated in a way that allows them choices for their
future (Dodson, 1993a). It is the expectation that each child may have a life full of
opportunities, free of marginalization (Dodson, 1993b).
Appreciating the Complexity
The positions of privilege for some and marginalization for others is
intricately woven into society (Bell, 1997). Human nature perpetuates this cycle by
allowing individuals and groups to uphold systems that support their best interests,
even if others are disadvantaged (Bell; Blanchett, Brantlinger, & Shealey> 2005;
Goodlad, 2003). Further, individuals tend to place higher standards and
expectations on others than they are willing to place upon themselves (Blanchett e
al-). Because human nature allows individuals to view others needs as ess
important than their own, a rational argument is created to serve first personal
12


interests and interests that mil benefit groups to which one belongs before the
interests of others (Blanchett et al.; Jost, Pelham, Sheldon, & Sullivan, 2003),
People often accept a hierarchal class structure that sorts others based upon
their ethnicity, religion, or economic situation (Blanchett et aL, 2005). Conversely
many people believe that all people should be treated equally (Blanchett et al.).
Clearly, these two statements produce conflicts between how one may truthfully
view the world and how one believes one should view the world.
Believing in social justice requires recognizing issues of adequacy, power,
and oppression exist (Goodman, 2001)* For many pnvileged individuals, simply
admitting that positions of advantage exist in society is difficult because, by this
admission, the implication is clear that positions of disadvantage, non-privilege,
and marginalization also exist (Goodman; Tatum, 2000),
Involving the Privileged
Unquestionably, marginalized individuals must struggle for their own
interests and not leave the fight to someone else (Concern America, 2005; Freire,
1989). Whereas many privileged individuals may choose to continue the cycle of
marginalization, other members of the dominant culture want to stop it (Goodman,
2001)-The inclusion of privileged individuals is of great value because they may
have access to resources, information, and most importantly the voice and the
power to help others listen (Goodman).
13


In order for social justice to prevail, enough people must recognize the
inadequacy and commit to making it known to others (Blanchett et aL, 2005). In
fact, people generally must become uncomfortable with the current system in order
to be willing to go through the effort required to make changes (Heifetz, 2000).
Often to create enough energy to make change happen, a pressure-cooker
environment must occur to force people to recognize the ineffectiveness of the
current situation (Heifetz). By allowing a situation to escalate to the point of an
uncomfortable simmer, all players become engaged in the process by
acknowledging the need for changes to take place (Heifetz). The increased
attention to the achievement gap between students of color and their White
American peers, racial segregation in schools, and the large number of students not
being well served by public education is fueling the pressure-cooker environment
needed for social justice change to transpire (Blanchett et ah; Colorado Children's
Campaign, 2005; Heifetz; Kozol, 2000; Tatum, 2003),
Empowering the Marginalized
Nevertheless, a truly powerful society is only possible through the
development of its most marginalized people (Social Justice Education, 2005)* As
long as pockets of individuals are perpetually given less, expected to do without, or
believed to be less important than other groups of people, society is constricted in
ways that keep civilization from transcending its current conditions (Social Justice
14


Education). In this regard, social justice means not acting self-centered]y, but
teaching people to help themselves (Concern America, 2005),
Education is the key to empowering individuals to lift themselves out of
their current situation and take control of their own lives (Concern America, 2005;
Freiret 1989)* By empowering individuals to change their current reality,
individuals are able to take control of their own lives rather than having a dominant
group of individuals make changes for them, generally in ways that most likely are
of benefit to the dominant group (Concern America; Freire).
In current society, education is arguably the best answer to affecting a more
socially just society (Banks et aI,T 2001). If denied the opportunity to receive an
education, people are unlikely to be successful in life (National Center for Public
Policy Research, 2005). Education is a basic right for all children, and adequate
resources, opportunities, and conditions should be available to all students,
regardless of ethnicity, zip code, or economic status (National Center for Public
Policy Research, 2005). This study seeks to determine if districts and schools are
performing at adequate levels when controlling factors beyond the district and
school control.
Study Implications
Because differences existed between expected outputs for districts and
schools serving White American students and those serving Latino American
15


students, the findings were framed from a social justice perspective. Education
has long been viewed as the major route to a good society and to improving the life
chances of individual citizensLadd & Hansen, 1999, p. 67). This study was
originated to determine if districts and schools serving Latino American students
are performing at levels below other districts and schools* The findings
demonstrated that additional inputs may improve Latino American student
achievement, potentially enabling outputs competitive with their peers,
Additionally, the findings from this study illustrate that some districts and schools
serving Latino American students are performing at expected levels from the
current inputs. For that reason, the case is made that additional inputs are required
to produce an adequate level of education for Latino American students.
Study Overview
The study is divided into two main parts* The first part is a district-level
analysis, comparing the 178 school districts in Colorado, The district*level analysis
compares school districts based upon the district setting. District settings are
defined by Colorado Department of Education (CDE) and include 15 metro area
school districts,15 urban-suburban school districts,13 outlying city school
districts, 49 outlying town school districts, and 86 rural school districts. The
second part of the study compares secondary schools within two metro-area school
districts.
16


Guiding Questions
This study was designed to answer two questions. The first question is the
following: Using an adjusted performance measure, are school districts Latino
American students1 CSAP scores at predicted levels, based upon the districts1
inputs? The seven categories of district inputs include (a) School Environment, (b)
District Revenue Sources, (c) District Expenditures, (d) Teacher Quality, (e) Ratio
of Students to Professionals, (f) Student Characteristics, and (g) Previous Year^
Test Results* The second research question is the following: Using an adjusted
performance measure, are schooPs Latino American students' CSAP scores at
predicted levels, based upon the schools' inputs? The categories of school inputs
include (a) Teacher Quality, (b) Ratio of Students to Professionals, (c) Leadership
Experience, (d) Student Characteristics, and (e) Previous Year^ CSAP Scores.
Clarifying the Variables
Because the study is rather large and includes many variables, Figure LI
and Figure 12 are included to depict visually the variables in the study and show
their relationship with other variables. Figure 1.1 describes the district-level
portion of the study, while Figure 1.2 represents the school-level portion of the
study. Both figures are also included iTi Chapter 3, the methodology chapter, where
they are referenced again H
17


District-Level Analysis
The district-level analysis included seven categorical indicators; all
involving multiple variables (see Figure l A). The first indicator, School
Environment, was measured through the retention of administrators, principals,
classroom instructors, and instructional supporters. Teacher Quality, the second
indicator, examined the average Years of Teaching Experience, percentage
instructing in degree area, percentage of days absent, and Teacher Salary which
correlates with educational degree level. The Ratio of Students to Professionals
indicator was calculated to include ratios of students to teachers, administrators,
and other professionals. The fourth indicator, Revenue Sources, was measured by
comparing the percentage of total revenue from local revenue, state share, state
Special Education funding, state English Language Learner funding, State Gifted
and Talented funding, and federal revenue. The comparison of Per Pupil Revenues
is also included in the fourth indicator. For the fifth indicator. Revenue
Expenditures, the percentage of dollars spent for instructional purposes, support
services purposes, andnon-instructional purposes were compared. Student
Characteristics, the sixth indicator, provides a measure of student need by
determining the free and reduced lunch percentages, percentage of the population
qualifying for special education services, and the percentage of students who are
English Language Learners. The seventh indicator was the Previous
18


School Environment Teacher Quality
Retention of Years experience
o Administralors Assignment in degree area
o Principals Q Days absent
o Classroom instructors Q Salary
o Instructional supporters
District
Educational Inputs
Student Characteristics
Ethnic breakdowns
Free and reduced lunch
Special education
English Language Learners
Ratio of Professionals
Ratio of students to:
o Teachers
o Administrators
O Other professionals
4
District Revenue Sources
Total revenue from
0 Local
o Federal
o State Share
o State Special Education
0 State English Language
Learners
o Per pupil
District Expenditures
Instructional
Support Services
Non-instructional
Last year's CSAP scores
Figure LL District-level educational input variables.
19


Yearns CSAP Scores. This indicator was included as a baseline marker from which
to measure the current CSAP scores, the outcome variable for my study.
School-Level Analysis
The second portion of the study was the school-level analysis (see Figure
1.2). Teacher Quality, the first indicator, was measured through average Years of
Teaching Experience, percentage of instructors teaching in their degree area,
percentage of days absent, percentage of teachers retained, and Teacher Salary.
The second indicator, Ratio of Students to Professionals, was calculated by
comparing the ratio of students to teachers, administrators, and counselors. The
third indicator, Leadership Experience, was determined by comparing the number
of years each building principal had been a principal and how long each had served
at the current location. Similar to the district-level analysis, the fourth indicator,
Student Characteristics, was included to provide a measure of student need by
determining the free and reduced lunch percentages, percentage of the population
qualifying for special education services, and the percentage of students who are
English Language Learners, The fifth indicator was the school's previous CSAP
scores. Previous CSAP scores were included to provide a baseline marker from
which to measure the current CSAP scores, the outcome variable also for the
school-level analysis.
20


Teacher Quality
Years experience
Assignment in degree area
Days absent
Retention rate
Salary
Ratio of Professionals
Teachers
Administrators
Counselors
School
Educational Inputs
Student Characteristics Leadership Experience
Free and reduced lunch Years as principal
Special education Years at cunrent location
English Language Learners
Previous year's CSAP scores
Figure L2. School-level educational input variables.
Study Methodology
As stated earlier, the study is made up of two distinct parts. The first
portion analyzes school districts within Colorado, while the second portion
analyzes individual schools within two metro-area school districts. The study was
intentionally arranged using a tiered approach to allow for focus on two different
social justice angles. First, in the district-level component, an examination of
adequate federal, state, and local inputs for districts was included. On the other
21


hand, in the school-level section, adequate division of resources within the control
of the school district was the concentrated focus.
Two types of analyses were used for both district-level and school-level
investigations. The first was an exploratory factor analysis (EFA) and the second
was a multiple regression. Using EFA allowed for the identification of variables
that were, in essence, overlapping. By reducing overlapping variables, the
opportunity for multicollinearity to interfere with the findings was diminished, and
the number of variables in the regression equation was lessened. Using regression
analysis allowed for the creation of a model to determine the APM for each school
district and for schools within two school districts-
Study Limitations
While much thought was put into designing a tiered inquiry into adequate
educational inputs in Colorado school districts and schools, limitations to the study
exist. For one, all secondary data was used for the district^level portion of the
study. Although the data were compiled from reputable sources, I was not involved
in the collection. This limitation could also be viewed as a strength because there
was less opportunity to influence, either consciously or unconsciously, the
information.
A second limitation is that the analysis is strictly quantitative. As an
educator, I fully realize the vital pieces of information that can not be captured
22


through test scores. Great insights are often revealed when using qualitative
measures. But for this study, a larger-scale quantitative analysis using secondary
data was designed. This study does open the door to future researchers to build
upon the foundation created from these findings.
A third limitation of the study is that the school-level analysis only includes
secondary schools in two school districts. The study would have been strengthened
by including schools from districts throughout Colorado, Because the school-level
analysis required some information gathered from the school districts themselves, I
needed to submit an application to conduct external research to each district for
approval. The complexity of each district's approval process kept me from
branching out to include additional school districts in the school-level analysis.
Again, future follow-up studies could be completed with additional school districts
to widen the reliability scope of the study.
Concluding Introductory Remarks
Through this study, I intended to determine if significant differences exist in
APM between districts serving more Latino American students and those serving
fewer Latino American students. Findings from this study demonstrate that schools
in Colorado do provide different opportunities for student achievement*
Because differences in fundamental areas such as School Environment,
Teacher Quality, Leadership Experience, and Revenue are identified, lower scores
23


and overall performance ratings contribute to school-controllable and district-
controllable factors. These findings should initiate conversations on creating
adequate educational environments and opportunities for all students. In addition
to sparking conversation, these significant findings should set in motion the
drafting of education legislation to allow for a more adequate allocation of
education quality indicators and opportunities for all schools.
24


CHAPTER 2
ITERATURE REVIEW
4The America that I love is one that values freedom and the differences of
its people. Education is the key to understandingAsfahani. 1996. p* 18), and the
more educated people are, the better society is (Swail, Cabrera, & Lee, 2004)*
This viewpoint is particularly acute given that the face of American society is
changing substamially* National projections estimate that the percentage of Latino
American children enrolled in K-12 schools will increase from 14% in 2000 to 25%
by 2050 (Viadero, 2005). To maintain the overall strength of the United States,
schools must meet the needs of all of its students, specifically the fast-growing
population of Latino Americans. With a population of more than 25 million,
Latino Americans are the second largest and fastest growing population in the
United States (Besnette & Schoales, 2004; Hernandez & Nesman, 2004; Suro,
1999; Tatum, 2003; Weiner, Leighton, & Funkhouser, 2000).
Students in the United States generally do not have equal access to quality
education (Kozol, 2000; McWhirter, McWhirter, McWhirter, & McWhirter, 1998;
Tatum, 2003). America^ schools fail to educate large numbers of students, and the
25


cause of this failure lies with schools, not with the students (Amster, 1994). Latino
American students do not receive the quality of education they deserve to attain an
independent, self-sufficient life in the United States, perpetuating the downward
spiral of life opportunities (Denver Commission on Secondary School Reform,
2005).
In Colorado, like the rest of the states in the United States, Latino American
students' high school dropout rates are particularly dismal (Blake, 2005; Colorado
Children^ Campaign, 2004; Hayes & Polis, 2005; Hernandez & Nesman, 2004;
Tellez, 2004; Walters, 1998; Weiner et al., 2000), This becomes a national issue
because ltas Latinos become a majority population in many states, failure to address
the dropout/graduation issue will have disastrous implications^ (Montecel et aL,
2004, p,171), To stop the slide, schools must develop strategies for engaging all
students and provide opportunities for academic success for Latino American
students (NASSP, 2005),
An Achievement Gap
Three decades ago, the achievement gap was declining, but the progress
ceased around 1988, and for the last 18 years the gap has actually expanded
(Haycock, 2001)-Recent studies in Denver's schools (see Tables 2.1,22, 23, 2.4,
2,5 and 2.6) reveal that the gap not only exists but that it is continuing to widen
(Horrell & Guzman, 2005). It appears that the longer a Latino American student is
26


Table 2 A
2002 9lh Grade DPS Students1 Reading Proficiency Levels Over 3 Years
Racial/Ethnic Group 2002 9* Grade Total At or Above Number Proficiency 2003 9th Grade Total At or Above Number Proficiency 2004 9th Grade Total At or Above Number Proficiency
Black American 1016 37% 1181 35% 1134 40%
Latino American 2255 25% 2874 25% 2816 25%
White American 1069 75% 1167 67% 1062 71%
Total 4544 40% 5480 37% 5269 38%
Note. From Colorado Student Assessment Program (Denver Public Schools, 2004)*
Table 2.2 2002 10lh Grade DPS Students' Reading Proficiency Levels Over 3 Years
Racial/Ethnic Group 2002 lO1*' Grade Total At or Above Number Proficiency 2003 10* Grade Total At or Above Number Proficiency 2004 10th Grade Total At or Above Number Proficiency
Black American 917 34% 890 40% 891 33%
Latino American 1881 25% 1759 29% 2022 25%
White American 1031 68% 953 73% 932 70%
Total 4028 39% 3791 43% 4051 39%
Note. From Colorado Student Assessment Program (Denver Public Schools, 2004).
27


Table 23
2002 9lh Grade DPS Students' Writing Proficiency Levels Over 3 Years
Racial/Ethnic Group 2002 9th Grade Total At or Above Number Proficiency 2003 Total Number 9th Grade At or Above Proficiency 2004 9th Grade Total At or Above Number Proficiency
Black American 1016 21% 1181 23% 1134 28%
Latino American 2254 13% 2877 15% 2815 15%
White American 1069 60% 1167 55% 1062 60%
Total 4543 27% 5483 26% 5268 28%
Note. From Colorado Student Assessment Program (Denver Public Schools, 2004).
Table 2.4 2002 10th Grade DPS Students5 Writing Proficiency Levels Over 3 Years
Racial/Ethnic Group 2002 10* Grade Total At or Above Number Proficiency 2003 10th Grade Total At or Above Number Proficiency 2004 10th Grade Total At or Above Number Proficiency
Black American 918 22% 890 23% 891 23%
Latino American 1882 16% 1761 15% 2022 15%
White American 1032 58% 953 63% 932 60%
Total 4031 29% 3793 30% 4051 28%
Note, From Colorado Student Assessment Program (Denver Public Schools, 2004)*
28


Table 2.5
2002 9lh Grade DPS Students' Math Proficiency Levels Over 3 Years
Racial/Hthnic Group 2002 9th Grade Total At or Above Number Proficiency 2003 9th Grade Total At or Above Number Proficiency 2004 9th Grade Total At or Above Number Proficiency
Black American 999 4% 1179 3% 1141 5%
Latino American 2245 3% 2870 3% 2843 4%
White American 1063 34% 1170 29% 1063 37%
Total 4508 11% 5476 9% 5306 11%
Note, From Colorado Student Assessment Program (Denver Public Schools, 2004).
Table 2.6
2002 10th Grade DPS Students' Math Proficiency Levels Over 3 Years
Racial/Ethnic Group 2002 lO* Grade Total At or Above Number Proficiency 2003 lO111 Grade Total At or Above Number Proficiency 2004 10th Grade Total At or Above Number Proficiency
Black American 908 3% 900 4% 892 2%
Latino American 1876 3% 1768 3% 2046 2%
White American 1024 26% 964 31% 939 30%
Total 4004 10% 3820 11% 4085 10%
Note, From Colorado Student Assessment Program (Denver Public Schools, 2004).
29


in school, the greater the gap for that child becomes (Colorado Children's
Campaign2004)As long as an achievement gap exists, a great part of our
population is being underserved and inadequately educated.
Interestingly, Reid (2004) questioned teachers about the achievement gap
and found that teachers were likely to attribute the cause of the gap to family or
student-centered factors. Student interviews from the same study identified school-
related causes to explain the achievement gap. In an earlier study, Camevale
(1999) found in the middle and high school years that low aspirations are not the
problem, but rather mismatches among the student's future vision and the academic
courses they take in middle school and high school. It appears that many Latino
American students have a desire to attend post-secondary schools but are unaware
of the classes they should take. In the findings of one study, Latino American
students completing Algebra 2 cut the gap between White Americans and Latino
Americans completing college in half (Honawar, 2005). Simply dispersing this
information to parents, students, educators, and policy makers should encourage
districts to require students complete at least Algebra 2 in high school. By adopting
this policy, any student who chooses to attend college has a much better chance of
completing their degree.
30


A Snapshot of Denver's Latino American Population
An estimated 62% of the Latino Americans who have recently moved to
Denver were bom outside of the United States (Colorado Childrens Campaign,
2004). Because such a large percentage of Latino Americans moving to Denver
have recently immigrated to the United States, many of Denver^s new students
were bom in a different country with different cultural norms and are likely to have
limited English proficiency (Colorado Childrens Campaign). Family, religionand
discipline are examples of cultural norms that are central to Latino culture
(Cavanagh & Lopez, 2004). For example in the United States more than 25% of
Latino Americans, compared tojusi 11% of White Americans, live with five or
more people (Cavanagh & Lopez). Furthermore, Latino women are often expected
to begin families at an early age* In Denver, Latino Americans account for 8% of
the teenage births with White Americans accounting for only 6% (Colorado
Childrens Campaign). Regardless of the parents citizenship statusbabies bom in
the United States are citizens of the United States*
Complexity of the Issue
Attempting to create educational environments that provide better
opportunities for Latino American students to be successful is difficult at best,
although understanding the complexity of the issue is a necessary starting point.
To begin with, it is complicated to identify the target uLatino American student^
31


population with much variance in socioeconomic status, country of origin, length of
time in the United States, English proficiency, and so forth (Hernandez & Nesman,
2004) Second, when narrowing lo "Latino American students, literature suggests
that if their ancestors were voluntary minorities (i.e., Cuban Amencans, Filipino
Americans, and so forth) instead of involuntary minorities Mexican
Americans, Puerto Ricans, Native Americans, and so forth), difference are evident
in their long-term emotional feelings affecting their comfort level within the United
States (Conchas, 2001; Rong & Brown, 2001). Third, the numbers of second-
generation Latino American students are expected to double by 2020 (Freeman,
2004). This increase adds complexity because it is expected that the majority of
these students will require English-language support even though they will have
been bom in the United States.
Differences Among Generations of Latino Americans
In 2000, about 40% of all United States Latino Americans were forcign-
bom immigrants to the United States (Chapa & Rosa, 2004). Currently, children of
immigrants account for 1 in 5 students (Conchas, 2001; Orellana, 2001; Qin-
Hilliard, Feinauer, & Quiroz, 2001; Sadowski, 2004; Suarez-Orozco, 2001;
Suarez-Orozco, M., 2001) enrolled in United States schools, with the number
expecting to increase to 1 in 3 by 2020 (Suarez-Orozco, CO-
32


In Denver high schools, hostility has been noted between different
generations of Latino American students (Aguilera, 2004), The hostility has
surrounded issues of Spanish fluency, '"acting White/1 and being l4Whitewashed,1
(Aguilera, p. A 14), Some students are accused of trying to forget their past and to
adapt fully to American culture in order to fit with the majority population, while
others are offended by these actions and lash out (Asfahani, 1996).
Colorado 7s Residents
As stated earlier, the students enrolled in Colorado schools, as of 2003,
include 44,085 Black American students,191,976 Latino American students, and
489,053 White American students (Colorado Department of Education, 2003),
From the 2000 count through 2003, the Black American population increased by
244%, the Latino American student population increased by 5%, and the White
American population decreased by 1*05% (Colorado Department of Education),
Currently immigrants account for 34% of Colorado's Latino American population
(Aguilera, 2004). These statistics convey that Colorado's White American student
population is diminishing as both Black and Latino Americans are growing.
Denverfs total population is 2,581,506 and the Latino American population
is 476,627, which is 18.5% of the total state population (Chapa & Rosa, 2004)*
Denver's population grew over 21% from 1990*2003 with Latino Americans
accounting for 79% of the city's growth (Colorado Children's Campaign, 2004),
33


Currently, 32% of Denver's residents are Latino American, but almost 50% of the
students enrolled in Denver schools are Latino American (Colorado Children's
Campaign; Denver Commission on Secondary School Reform, 2005). Latino
Americans comprise approximately about 33% of Denver^ total population,
account for 50% of the total population under the age of 18, and encompass almost
67% of the children living in poverty (Colorado Children's Campaign).
Donning a Cap and Gown
Nationwide, Latino American students are more likely to drop out of school
than any other group of student (Paige^ 2003). Furthermore, approximately 30% of
students drop out of school each year in the United States, and the number
increases sharply to approximately 50% in urban locations (Olson, 2005a). While
the rest of the nation's high school graduation rates have increased, Latino
American students' dropout rates remain more than double that of Black Americans
and over triple that of their White American peers (Walters, 1998). Only
approximately half of Mexican Americans over the age of 25 have completed high
school (Conchas, 2001; Tatum, 2003)*
The average Latino American high school graduate finishes with having
taken lower levels of Math courses than any other group of students (Swail et aLT
2004), Nationally, only 4% of Latino American 12th graders test at a proficient
level in Math (Paige, 2003). Glimmers of success have been revealed in studies
34


showing that 60% of Latino American high schools students completing an
advanced Math course go to a four-year college or university compared to only
16% of students advancing oniy as far as intermediate leve] Math (Paige).
To further compound this issue, the number of Latino American students
graduating from high school and being prepared for post-secondary educational
opportunities is low (Paige, 2003). Of the Latino American students graduating
from high school, only 29% have completed the necessary coursework to attend
college (Hayes & Polist 2005).In another study of 1,000 Latino Americans high
school graduates, only 277 qualified for college based on the courses that they had
completed in high school (SwaiJ et al., 2004), These numbers demonstrate that
even though these students are graduating, they are clearly not in a position to
choose to attend post-secondary education. Clearly, greater effort needs to be
placed on enrolling students in appropriate and challenging courses.
Colorado's Graduation Data
More than 25% of Colorado students are Latino American, but less than
15% of Colorado high school graduates are Latino American students (Sanchez,
2004). Like the national rates, Latino American student graduation rates are
significantly lower than those of White American students, with Colorado falling
7% short of the national average (Blake, 2005; Rouse & Sherry, 2004). Colorado's
Latino American high school students have less than 50% likelihood of graduating
from high school (Besnette & Schoales, 2004). Denver's dropout rate is the third
35


worst in the country (Hayes & Polls, 2005) as evidenced by only 42% of Latino
American students graduating, in comparison to 68% of their White American
peers in 2003 (Colorado Children s Campaign, 2005; Hayes & Polis),
Despite the high dropout rates, most Latino American students want to be
successful in school (Sadowski, 2005). According to a 40,000-student survey
conducted by Ronald Ferguson of Harvard University's John F* Kennedy School of
Government, Latino American students were more likely than their White
American peers to believe it is 'Very important^ to i4study hard and get good
grades^ (Sadowski, p. 4). Latino American students believe in the importance of
education, yet they may harbor negative attitudes toward education because of their
actual school experiences (Schwartz, 1989; Smith, 2000).
According to Denver's Latino Students (Colorado Children's Campaign,
2004), fewer than half of Denver's Latino American adults have a high school
diploma ana less than one out of ten have a college degree. Not surpnsingly,
Latino American students struggle more in school than other students (Sanchez,
2004)* Some of the major obstacles in the lives of Latino American students
include working part-time or full-time jobs, not seeing a long-term reason for
attending school, and not understanding the benefit of college (Stem, 2004), In
additiTi, Latino American students might encounter teachers who offer little
support and counselors who are busy or otherwise unavailable (Stem),
36


Gender has been noticed as another obstacle in educational achievement.
Latino American females, for instance, often will defer to boys in mixed gender
settings when expected to perform an academic task (Delpit, 1995), Once in the
company of alt females, they will then be more likely to display their knowledge
(Delpit, 1995b), To complicate matters, quite often Latino American families
encourage their sons to attend college while discouraging their daughters because
of traditional family roles and dynamics (Walters, 1998).
Parent Involvement
Despite common misperceptions, most Latino American parents have high
expectations for their children to do well in school and to attend college (Stem,
2004; Walters, 1998). In spite of their high expectations, many parents lack the
knowledge, information, or both to help their children reach these academic goals
(Stem), Rong and Brown (2001) found that many immigrant parents recognize that
if their children are educated and socialized into mainstream society through
schools, their children's chance to be successful increases drastically.
Immigrant parents value education but may not be involved in schools as
educators traditionally expect parents to be involved (Su^irez-Orozco, C., 2001).
Many immigrant parents are uncomfortable with their English skills and choose not
to be involved to avoid discomfort or embarrassment (Wiltz, 2004). Second, many
other cultures greatly respect teachers and feel uncomfortable asking questions for
fear it could be interpreted as disrespectful (Suarez-Orozco, C,, 2001; Wiltz),
37


Third, many parents are confused about the school's expectations for their children
and do not understand how to support their child in American schools (Wiltz)
Finally, many students may not have the resources required to complete homework
assignments because they lack computers, Internet access, sufficient English skills,
and understanding of the concepts being taught (Suarez-Orozco, C,)*
School Culture
Schools must promote opportunities for student-adult relationships
(Cavanagh & L6pez2004; Sadowski2005; Su^rez-Orozco, C.. 21;Weir Jr
1996), As Sadowski observes, ^regardless of the level of encouragement students
receive at home, positive relationships with adults at schoolteachers, counselors,
administrators coachescan also make a crucial difference" (p, 2). When seeking
to increase student retention, a close relationship with a teacher is an essential
ingredient (Nieto, 1999). Literature repeatedly shows the important link between
supportive adult relationships and student academic success (Nieto, 1999;
Sadowski). Districts and schools that keep their student to teacher, administrator,
and other professional ratios low send a clear message about the value of building
stronger relationships between adults and students.
Students require a safe, respectful, and caring environment to perform up to
their potential (Denver Commission on Secondary School Reform, 2005),
Knowing an adult in the school cares about a student can be the difference needed
38


for that child to continue attending school (Gales, 2005; Montecel et aL> 2004;
Weiner et aL, 2000)* Teachers must seek a careful balance between creating these
friendly relationships while continuing to demand rigorous academic effort
(Gordon, 2004b; Makkonen, 2004; Olson, 2005b; Sadowski, 2005).
Generational Immigration Patterns
The needs and goals of students, teachers, and schools vary based on their
environment and how long their family has been inhe United Stales, Because
differences exist among generations of Latino Americans, it is not possible to group
all Latino Americans into one category. For instance, when looking at Latino
American youth, I could divide students living in Colorado into three broad
categories associated with their assimilation process: (a) native to Colorado, (b)
multi-generational in Colorado, and (c) recently immigrated to Colorado. Whereas
it is obvious that not all of Colorado's Latino American youth have identical
schooling experiences, students in similar environments are more likely to have
parallel goals. For example, students native to Colorado are more likely to choose
to stay in their community* If they choose to attend college, they will most likely
attend a school in their immediate community (Chang & Szelenyi, 2002; Cohen,
1990; Laden, 2001;Santos, M 2004)
Second, multi-generational Latino Americans might view education as a
lower priority if their family has made a living without attaining higher levels of
39


education. In fact, multi-generational Latino Americans tend to exhibit higher
dropout rates and lower achievement rates than other groups (Walters, 1998). John
Ogbu (1992) found that some minority students renounce education after
repeatedly noticing that it does not offer them the same rewards it does for the
majority population. For example, the United States 1990 census data shows that
the mean annual income for White American male high school graduates was
$22,521 while for Latino Americans it was only $14,644 (Walters)-
Third, families who have recently immigrated are most likely to aspire to
higher educational attainment but are also less likely to understand the required
elements for college acceptance. Completing college applications and financial aid
forms can be confusing for a highly education, proficient English speaker These
tasks can become downright intimidating for individuals lacking a strong grasp of
the English language and American culture (Greene & Greene, 2004). Often times,
the miscommunication of expectations and necessary requirements, not low
motivation levels, are the basic problems of recently immigrated students being
admitted to college (Camevale,1999)*
Past studies have shown that Latino American student achievement
decreases with each successive generation (Conchas, 2001). When immigrant
students first arrive, they generally spend more time on homework and tend to do
well in school (Suarez-Orozco, M. M.? 2001), Typically, newly immigrated
students perform at higher levels than United States bom Latino Americans* But
40


trends show that as these immigrated students become more Americanized, they are
likely to become less committed to school (Rong & Brown, 2001; Suarez-Orozco,
2001;Walters, 1998).
A Leader with Laser-Like Focus
Districts and buildings with high administrator retention are able to
maintain a laser-like focus on the organization^ vision, goals, and most
importantly, student achievement (Denver Commission on Secondary School
Reform, 2005; Northoase, 2004), The building principal is the most important
element in creating a high-achieving school (Horrell & Guzman, 2005). Concisely
stated, good schools have good principalsJesseDavis, & Pokomy, 2004t p. 25).
The school leader sets the culture, tone, and vision of the school (Horrell &
Guzman; National Association of Secondary School Principals, 2005). Productive
leaders are easily accessible, share their thinking and rationale for decisions with all
involved individuals, and build trust through tneir predictability (Gordon, 2004a).
In addition, effective leaders assume responsibility for the performance of
teachers and students and are willing to take action, when necessary, if teachers are
unproductive, uncaring, or both. Such teachers will be harmful to their students
and can poison the entire school atmosphere if no action is taken to terminate their
damage (Fullan, Bertani & Quimi,2004; Horrell & Guzman, 2005)* When leaders
allow teachers to remain in positions where they are unsuccessful or poorly
41


matched, it can actually decrease the motivation and accomplishments of the
successful teachers in the building (Collins, 2001).
Teacher Quality
Teachers in high-poverty, high-minority schools are often less experienced
and are more likely to be un- or under-qualified (Diamond & Tamman, 2004;
Flannery & Jehlen, 2005; Makkonen, 2003; Nieto, 1999; Reyes, 2003; Sadowski,
2004; Shields, Humphrey, Wechsler, Rie], Tiffany-Morales, Woodworth et aL,
2001). Although some dedicated, qualified, and impassioned teachers choose to
teach in high-poverty and high'minority schools, capable teachers are less likely to
teach in areas with poor conditions, where performance standards will be less likely
to be reached (Darling-Hammond; Suarez-Orozco, C*, 2001; Suarez-Orozco, M-,
2001).
Years of Experience
Most research studies show that teachers become increasingly effective
during their first five years of teaching (Bracey, 2004), Because teacher quality
strongly influences student achievement, Barth ¢1990) boldly claimed that,
"probably nothing within a school has more impact on students in terms of skill
development, self-confidence, or classroom behavior than the personal and
professional growth of the teacherp. 49).
42


Teachers, who know what they are leaching and how to teach best the
material, are critical to effective learning (Denver Commission on Secondary
School Reform, 2005; Spellings, 2005; Steinberg, 1998a). Teachers become more
effective at delivering curriculum in ways that will be relevant and meaningful to
their students when they have experience teaching the same content for a few years
(Diamond & Tamman, 2004). A research study in the Boston Public School
system examined the affect teachers can make on student achievement. After just
one academic school year, the students of highly effective teachers demonstrated
six times the learning growth as students of other teachers (Haycock, 2001).
Because nothing is more important in the learning process than a good
teacher^ low-achieving students most need the highest quality teachers (Denver
Commission on Secondary School Reform, 2005; Spellings, 2005). Many
contributing factors to the achievement gap are beyond a school*s grasp, but
teacher quality remains within the educational systems' control (Diamond &
Tamman, 2004; Spellings; Sternberg, 1998a).
Absences
Much attemion has been placed on the need for high quality teachers in
each and every classroom in the United Slates. ButT if those teachers are often
absent, the classrooms then become staffed with usually much less qualified
substitute teachers (Bowers, 2001; Patterson, Collins, & Abbott, 2004; Scott,
43


1998)+ High levels of teacher absences can hurt both student achievement and
student attendance (Sherry, 2006). Typically teachers are reported absent even
when they are participating in professional development activities, which is
different than the way most other professions calculate employee attendance rates
(Sherry). Interestingly, when compared to other professions, teachers have lower
absenteeism rates (Scott)* Nevertheless, schools with teachers who have lower
absenteeism rates may be providing higher quality instruction (Patterson, et al.)-
Salary
Working conditions, salaries, and support need to be fairly distributed
among all schools for all schools to have an equal chance in recruiting and
retaining good teachers (Archer, 2005; Bainbridge, 2003; Bhatt, 2005; Spellings,
2005). Bainbridge (2003) articulates thatT 4tif the education system ever is to be
better balanced for all children, we must first fix the issue of teacher recruitment by
providing all school systems with the tools and incentives necessary to attract the
best candidatesp. A 08),
In addition to the working conditions and daunting performance
expectations, teaching salary discrepancies add to the segregation of quality
teachers in more affluent areas. For example, Kozo] (2000) discovered that salaries
of beginning teachers in urban districts started at $27,000, whereas beginning
teachers in suburban districts started at $42,000. This trend continued with the
44


median salary in urban districts at $43,000 compared to $71,000 in suburban
districts (Kozol)*
Degree in Area
As earlier stated, students in high need areas have the greatest need for
qualified and dynamic teachers, yet typically these students are assigned teachers
with the weakest academic and educational foundations (Haycock, 2001;
Makkonen2003; Nieto, 1999). Some states reduce the certification requirements
for teachers in order to hire teachers who do not meet certification requirements
and place them in low-income urban schools that are often harder to staff (Reyes,
2003), This practice encourages and further promotes inequitable education in
schools serving students of color (Reyes)* One of the basic premises of No Child
Left Behind is (o have a highly qualified teacher in every classroom. Although this
policy has been in place for a number of years, many schools serving lower
socioeconomic communities continue to have problems attracting enough highly
qualified candidates. The policy has created a mandate for the problem without
creating a solution for the problem.
Revenue Expenditures
Education policy needs to be passed allowing for uniform funding of all
schools (Banks et alM 2001; Olson, 2005b), Current ^funding systems and tax
policies leave most urban districts with fewer resources than their suburban
45


neighbors, but schools with high concentrations of low-income and Minority'
students receive fewer resources than other schools within these districts" (Darling-
Hammond, 2004, p* 1056). One aspect of my study measures the funding practices
in Colorado to determine if inequitable practices exist in Colorado as well,
Instructional Dollars
Some believe that with all of the obstacles facing teachers in high-poverty
schools, the resources and salaries should be higher than those allotted to affluent
schools (Archer, 2005)- However, in reality, based upon common distribution of
resources, high-poverty and high-minority schools receive far less than wealthier
schools, even within the same district (Archer; Darling-HammondT 2004). High-
poverty, high-minority schools are more likely 10 employ less experienced teachers
(Archer; Darling-Hammond, 2003; Paterson et aL, 2004; Shields et alM 2001), and
less experienced teachers are generally paid less than veteran teachers.
While districts pay less to teachers in schools with less experienced
teachers, they do not level this inequality by allocating additional resources to these
less experienced teachers in often higher-need environments (Archer, 2005).
Recently, some districts have begun exploring the idea of calculating teacher salary
as part of the entire school budget. As a result, schools employing less expensive
teachers would have more money to increase resources in other areas (Archer;
Denver Commission on Secondary School Reform, 2005)*
46


Non-lnstructional Dollars
Revenue inequities contribute to great differences in learning environments
based upon the location of a school. Schools serving White Americans and affluent
students often receive more money and tend to have more conducive learning
environments (Bainbridge, 2003; Conchas, 2001; Darling-Hammond, 2004;
Makkonen, 2003). Working and learning conditions are often better in schools
where more money is available to spend on construction and building maintenance
(Bainbridge, 2003)* Further, ^research indicates that low-income minority students
often encounter aesthetically unpleasant and ill-equipped learning environmems,
inadequate instructional materials, [and] ineffective teachersConchas, p. 476).
Inadequate educational environments are likely to affect Black and Latino
American students more than any other group of students because United States
schools have become re-segregated (Darling-Hammond)- In fact
more than two-thirds of tminority, students attend predominantly minority
schools, and one third of Black and Latino students attend intensely
segregated schools . most of which are in central cities.... currently,
about two-thirds of all students in central city schools are Black or Hispanic
(Darhng-HammoTid, p,1055)
Revenue Sources
In addition to the achievement gap, a great funding gap exists within
schools serving White American students and schools serving Black and Latino
American students as well as those serving affluent students and those serving poor
47


students (Darling-Hammond, 2004; Makkonen, 2003). School funding and
resource allocation policies typically leave poor and minority students with more
students per classroom, outdated books and technology, less qualified teachers, and
limited access to high quality curriculum (Darling-Hammond),
Per Pupil Revenue
Makkonen (2003) found that in most states across the country, school
districts with a larger percentage of minority students received much less money
per student than districts serving the fewest Black and Latino American students.
To rectify such disparity, ediicational policy needs to provide uniform funding of
all schools (Banks et al.T 2001; Olson, 2005b). Currently, schools are typically
funded in ways that ensure more resources for schools located in suburban
neighborhoods than those located in urban neighborhoods (Archer, 2005; Darling-
Hammond, 2004; Makkonen). Similar patterns are often found within districts.
For example, even within the same schoo district, schools serving higher numbers
of minority and low-income students may receive fewer resources than schools
serving more affluent students (Archer; Darling-Hammond)*
Kozol determined that *sin 1997-1998, NYC [New York City] spent about
$8,200 per pupil, including special education, and an actual sum of $5,200 per
pupil in a mainstream elementary classroom. In the same year, Great Neck spent
about $18,000 and Manhasset nearly $20,000" per pupil(2000, p, 359). These
48


figures show that some schools receive more than three times the funding to
educate students, where schools in less affluent neighborhoods receive much
smaller amounts. Inequitable practices like these leave poor and minority students
with lower quality textbooks, fewer resources, limited technology, and generally
less materials in addition to larger classes being taught by less qualified and
inexperienced teachers (Archer, 2005; Darling-Hammond, 2004).
Calculating Funding Allowance
Colorado uses a formula to calculate Total Program, which is the funding
allowance per school district. The formula uses pupil count multiplied by total
per-pupil funding plus at-risk funding plus on-line funding to determine Tota]
Program. Next, I will explain what each of these terms means and how it affects
school district funding*
Pupil Count
Schoo] funding is based on a schools' student enrollment as of the first day
in October, the official student count day in Colorado (Chapman & Kispert, 2005).
For the 2005-2006 school year, the base funding amount is $4,717.62. Typically,
the allocated funding is determined on the student enrollment for the current year.
In the event of fluctuating enrollment numbers, funding is based on the average of
the ast three student count days and the student count from the current year
Student enrollment numbers in Colorado school districts range from 52 students in
49


Campo RE-6 to 86339 in Jefferson County (Colorado Department of Education,
2005).
Total Per-Pupil Funding
In addition to the base allocation determined by student enrollment,
additional money, called tstotal per-pupil funding," is distributed through a formula
calculating variation in district (a) cost of living averages, (b) personnel costs, and
(c) size (Chapman & Kispert, 2005). In the past, instead of cost of living, funding
was adjusted for inflation. Beginning in 2004-2005, cost of living is factored by
looking al the cost of living compared with the household income in the district.
This change allows for resource allocation to reflect local economic changes. The
cost of living factor is indexed, currently ranging from 1,009 to 1.641 based on
local economic trends (Chapman & Kispert).
The second factor of "total per-pupil funding^ personnel costs, represents
the largest expense in every school district. Obviously, personnel costs correlate
with student enrollment numbers. The funding for this factor is determined
through past information and also by using the cost of living factor. For 2005-
2006, the projection ranges from 79*96% to 90*50% (Chapman & Kispert, 2005),
The final factor of "total per-pupil funding1* incorporates district size.
Including district size is necessary because larger school districts often have greater
purchasing power when purchasing services. With this in mind, the size factor
gives more funding to smaller districts, fewer than 4,023 students, than to larger
50


districts, more than 4,023 students (Chapman & Kispert, 2005), The size-factor
projections are expected to range from i .0297 to 2.3725 in the 2005-2006 budget
year (Chapman & Kispert).
At-Risk Funding
The third part of the Total Program formula is i£at-risk funding/* "At-risk
funding" is determined by the federal free and reduced lunch program population.
For each student identified as at-risk, the district ieceives funding of between 12%
and 30% of its "Total Per-Pupil Funding" (Chapman & Kispert, 2005). Beginning
in the current fiscal year, the at-risk definition is being expanded to include
"'students whose CSAP scores are not included in calculating a school^
performance grade because the student's dominant language is not English and who
are also not eligible for free lunch" (Chapman & Kispert, p* 4),
On-Line Funding
The final element of the Total Program formula is "on-line funding This
aspect of the formula allocates funding for students enrolled in a school district's
on-line program at the mmtmum funding level of $5,689 (Chapman & Kispert,
2005), If the student was enrolled in the on-line program during the 2001-2002
fiscal year, then the student is funded at the same level as other students in the
district.
Together, these components comprise the Total Program funding process
for Colorado. In the 2005*2006 budget year, each school district is guaranteed
5i


Total Program funding of at least $5,689 per student (Chapman & Kispert, 2005),
Each year, school districts Total Program per pupil funding cannot exceed 125% of
the prior year's funding allocation (Chapman & Kispert).
Colorados Funding System
For the most part, districts are able to determine how to spend the money
allocated from the Total Program, as long as they comply with three state-required
stipulations. The first stipulation states that each district must set aside a minimum
of $167 per pupil for supplies and materials (Chapman & Kispert, 2005), Second,
districts need lo hold back between $271 and $800 per pupil for capita reserves.
Districts with more than $1,355 per pupil already in reserves can opt out of this
second condition (Chapman cS: Kispert). The final requirement is that at least 75%
of the at-risk funding be used for its at-risk students or to develop the staff working
with these students (Chapman & Kispert)*
Local Share
Colorado has determined that funding for school districts Total Program is
first provided through local means. District local share comes from two sources,
property taxes and specific ownership taxes* If the funding provided from the local
sources is insufficient, the state subsidizes the financial deficiency.
52


Property Taxes
Colorado school funding system requires each district to enforce a property
tax levy* The revenue collected from the taxes varies greatly among distncts
because of the wide range of property values throughout the state. At this point,
Colorado does not transfer any money collected from property taxes in one district
to other districts, but instead allows the money collected to stay in the district.
Statewide, property taxes are expected to provide an average of $2,084 per student,
which accounts for about 33,8% of the Total Program funding needed (Chapman &
Kispert2005).
Specific Ownership
Specific ownership taxes are collected through vehicle registration monies.
The county collects the money and then splits the proceeds with school districts.
The specific ownership amount is determined by the total monies collected m the
previous year. Specific ownership taxes are expected to give $235 per student,
accounting for approximately 3,8% of the Total Program funding needed
(Chapman & Kispert, 2005).
State Share
In Colorado, the state will subsidize each school district whose Local Share
is not able to fund fully its Total Program amount, The State Share monies are
provided mainly from state income, sales, and collected tax revenues. For the
53


2005-2006 budget year, the State Share to districts will range from $520 to $10,115
per student, with an average projection amount being $3,845 per student, or 62.4%
of Total Program funding (Chapman & Kispert, 2005)-
Other Funding
Districts may receive funding from sources other than their Local and State
Shar For example, districts may ask voters to raise override property taxes
through an additional mill levy. A mill tax means one-tenth of one percentage, or
.00L Chapman and Kispert (2005) offer the example that a home valued at
$100,000 would have an assessed value of $7,960 and each mill tax would raise an
additional $7,96 (p. 6). In addition, school districts with capital needs, building
needs, or both have five other avenues to receive funding for these needs. These
five ai'eas are (a) use tneir capital reserve fund, (b) hold an election to authorize
issuing bonds, (c) hold an election to authorize a three-year mill levy for building
construction and security, instructional, and information technology, (d) apply for
funding through a competitive grant process for capital construction and school
renovation, or (e) if identified as a "growth district,apply for a loan through the
State Treasurer In addition, Colorado State Board of Education is authorized to
provide emergency supplemental funds to school districts in great need.
54


Concluding Remarks
At this point, anyone would be hard-pressed to produce examples of
Colorado districts and schools with evidence of Latino American students'
sustained exemplary academic performance, Districts or schools with low
percentages of Latino American students have been able to mask the poor results
easier than those serving greater percentages of Latino American students.
Through this study, as detailed in Chapter 3, a measure has been developed that
allows educators to determine if student achievement results produced at both
district and school levels are expected, based upon district and school inputs.
55


CHAPTER 3
METHODOLOGY
For the study, my group of interest is school-aged Latino American
children. Schoo districts, and then individual schoolsare the units of analysis. In
examining the educational process, the study emphasizes outputs and adequacy,
using CSAP scores as the outcome measure* Although experts and practioners
differ on the CSAP measurement accuracy, this was selected as the outcome
variable because it is the current gauge of student, school, and district performance
in Colorado.
This study design creates a model to determine adjusted performance
measures (APM) for school districts and secondary schools within two large school
districts in Colorado (Stiefel et al 2005). Because I intend to share my findings
with policy makers and educational practioners, I have chosen to design a
quantitative and mainly secondary data analysis* Policy makers need reliable
information in a timely manner; for that reason, a secondary data analysis of
information collected from trusted and reputable archive sources is appropriate
(Young & Ryu, 2000).
56


Valuable lessons have been learned from previous studies using secondary
data. Because studies using secondary data are more economical in both time and
money than primary data analyses, secondary data analyses are popular in social
science research (Kiecolt & Nathan, 1985; Stiefel et aL, 2005), For example,
secondary analyses can allow for large-scale studies to be completed within a
reasonable time frame (King, Jritzhugh, Bassett, McLaughlin, StrathT Swartz, et alM
2001; Ramisetty-Mikler, Caetano, Goebert, & Nishimura, 2004), A secondary
analysis is a viable research method when the original data are available and the
data provide the information needed to answer a new research question (Church,
2002).
Data Collection
Before data was collected, the population of interest for the study needed to
be determined* It was decided that a logical starting point would be to measure
school districts throughout the state by comparing APM. Second, APM would be
compared within two school districts m Colorado: Exploration Public Schools
(EPS) and Mountain View Public Schools (MVPS). To maintain anonymity, the
names of districts and schools included in the school-level portion of the study have
been changed* These two districts are valid selections because they are large
districts and serve economically and ethnically diverse student populations.
Charter schools were excluded from the studyfs second aspect because they have
57


different financing regulations and management designs and tend to be fairly
autonomous from school districts (Bowman, 2000).
Before comparing the districts, they were organized by setting. The
settings, as determined by Colorado Department of Education (n*d.), were broken
into five categories; (a) Denver metroT (b) urban-suburban, (c) outlying city, (d)
outlying town, and (e) rural* Categorizing the school districts by setting is
important because a district's location often affects many of the variables included
in the study. For instance, districts in a rural setting require more money per pupil
in order to offer a range of courses that would be competitive with the courses
offered in urban and suburban schools* Furthermore, rural school districts are
given additional liberties for teachers instructing outside of their primary
certification areas- Because of the difficulties associated with having a small
teaching staff yet needing to offer a wide range of courses, rural educators
sometimes are required to teach courses beyond their primary certified discipline.
District-Level Analysis
As previewed in Chapter 1T school districts were measured through seven
educational input categories (see Figure 3*1), The inputs ranged from less direct,
such as revenue, to more direct, such as the School Environment and Professional
Assignment. These areas included (a) School Environment, (b) District Revenue
Sources, (c) Revenue Expenditures, (d) Teacher Quality, (e) Ratio of Students to
58


Figure 3J. District-level educational input variables.
59


professionals, ( Student Characteristics, and (g) Previous Year's Test Results.
School Environment
The school's environment and culture is difficult to measure without
designing a specific study centering on the school's culture. Because this is simply
one component of the study, the choice was made to explore this variable through
data reflecting the percentage of adults choosing to work in the building or district.
Many studies focus on the importance of retaining teachers and counselors
whom students know and trust (Denver Commission on Secondary School Reform,
2005; Ennis & McCauley, 2002; Kannapel, Clements, Taylor, Sl Hibpshman,
2005). The case can be logically made that districts and schools with high retention
rates of their employees are more positive school environments* The School
Environment is measured through the average percentage of administrators,
principals, classroom instructors, and instructional supporters retained from the last
two school years.
District Revenue Sources
Issues of money have surrounded school districts for years. Does money
make a difference in educating students? No clear answer to this question is
universally accepted as the response seems to change based on who is answering
the question. In this study, the choice was made to include variables for district
revenues and the allocation of monies. For District Revenues, the percentage of
total revenue from local sources, state share, state Special Education funding, state
60


English Language Learner funding, state Gifted and Talented funding, federal
revenue, and per pupil revenue were compared.
Revenue Expenditures
In addition to the District Revenue Sources, the percentage of total revenue
allocated to instructional, support services, and non-instructional costs were
compared. The instructional costs include salaries, employee benefits, purchased
services, supplies and materials, and capital outlay. Support services money pays
for pupil support, instructional staff support, general administration, school
administration, operations and maintenance, pupil transportation, food services, and
other support costs. The non insiructional costs include services to the community
such as recreation, child care programs, and other expenditures* In addition, the
change in Revenue Expenditures was calculated from the 2003-2004 and 2004-
2005 school years. When calculating the change, the higher the percent increase
shows an increase in money allocated for 2004-2005 from the previous school year*
Teacher Quality
Many researchers have demonstrated that high quality teachers can make a
great difference for the students they teach (Diamond & Tamman, 2004; Flannery
& Jehlen, 2005; Haycock, 2001; Ladson-BillingsT 1994). The more debatable issue
is how to determine a quality teacher using quantitative methods. For the purpose
of this study, four indicators were used to determine the Teacher Quality variable.
The four indicators include the average Years of Teaching Experience, Percentage
61


of Teachers Instructing in Their Degree Area, average Percentage of Days Teachers
are Absent, and the average Teacher Salary. Whereas the average Teacher Salary
is not necessarily tied to quality, it is tied to Years of Teaching Experience and also
to the level of education teachers have earned.
Ratio of Students to Professionals
One area where most educational experts and school reform models agree is
the importance of students developing relationships with adults in their school
(Cavanagh & L6pezT 2004; Denver Commission on Secondary School Reform,
2005; Sadowski, 2005; Suarez-Or2C> C.t 2001; Weir Jr, 1996). Because this is
one variable of many in my study, a way to measure the potential for relationships
by determining the ratio of professionals in the building to students was created
The rationale for this measure is that smaller ratios may lend themselves to
establishing stronger relationships between adults and students. For Ratio of
Students to Professionals, the number of teachers, administrators, and other
professionals (counselors, social workers, and librarians) were compared to the
number of students in the school district. School districts with smaller ratios of
students to professionals may be providing greater opportunity for professional-
student relationships to develop. In addition, the change in student to professional
ratios was calculated between the 2003-2004 and 2004-2CM35 school years. A
reduction in ratios can promote an environment for developing relationships
between the adults and students in the building.
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Student Characteristics
Student Characteristics are necessary in analyzing the study results through
a social justice lens. One of the main intentions of this study is to compare
educational adequacy for districts serving larger Latino American student
populations. For Student Characteristics, the percentages for student ethnicity,
students qualifying for free and reduced lunch, students qualifying for special
education, and English Language Learners were included,
CSAP Scores
As mentioned earlier, CSAP scores are one common way progress is
measured for students, schools, and districts. Although many people may question
whether the CSAP offers a completely accurate picture of learning, it is the current
gauge used to measure learning in Colorado.
The study includes two years of Reading and Math CSAP scores.
Furthermore, CSAP scores were included for all students and Latino American
students in Reading and Math. Reading and Math scores were selected because
both can predict onrem and future academic success. Reading skills should be
necessary to succeed in any academic setting. Advanced Math capability has been
linked to college enrollment (Bracey, 2004; Honawar, 2005; Makkonen, 2003;
Paige2003),
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School-Level Analysis
Next, information was collected on each school in EPS and MVPS-
Educational quality indicators were compared for the district schools through five
areas (see Figure 3.2), The areas include (a) Teacher Quality, (b) Ratio of Students
to Professionals, (cj Leadership Experience, (d) Student Characteristics, and (e)
Previous Year*s CSAP Scores.
Figure 3.2, School-level educational input variables.
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Teacher Quality
As mentioned above, creating a large-scale quantitative measure for
Teacher Quality is a difficult task. For the school-level analysis, comparisons were
made for the average number of years teaching, the Percentage of Teachers
Instructing in Their Degree Area, the average percentage of days absent, the
retention rate of teachers for the last two years, and average Teacher Salary.
Within a school district, Teacher Salary is determined by teaching experience and
education level. Because teaching experience is included separately, this measure
was included in an attempt to compare teacher degree levels within the school.
Ratio of Students to Professionals
As in the district-level analysis, comparing the number of professionals to
students is one way to explore the likelihood of developing strong relationships
between students and adults* Also, when ratios are very large, the case load
becomes too great for professionals to make much progress with any of their
students. For the ratio of students to professionals, the number of students in
relation to teachers, administrators, and counselors were compared.
Leadership Experience
Like most professions, leaders typically have their own vision for the
organization, a personal leadership style, and beliefs about best practices. Schools
65


are no different. Each time a school gains a new leader, progress is halted while the
new leader determines the direction the school needs to move for greatest success-
For the most part, the longer a leader has been at a school the more moirientum the
school has gained in moving towards the leader's vision (Collins, 2001), In
addition, when educators make the decision to move from their previous position
into a leadership role, time needs to be factored in for new leaders to leam the
basics of their new positions* For Leadership Experience, the number of years each
principal has been a principal and the number of years the principal has been at the
current location were compared.
Student Characteristics
Student Characteristics are used in the school-level analysis much as they
are used in the district'level analysis. The Student Characteristics are necessary to
determine the number of school-level inputs to produce adequate outcomes.
Student Characteristics at the school level also compared student the percentage of
students qualifying for free and reduced lunch, the percentage of students
qualifying for special education, and the percentage of English Language Learners.
CSAP Scores
CSAP scores were also used as the outcome variable for the school-level
analysis. As in the district-level analysis, two years of CSAP scores were included
and selected Reading and Math scores because both can predict current and future
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academic success. Reading skills should be necessary to be successful in any
academic setting whereas advanced Math capability has been linked to college
enrollment (Bracey, 2004; Honawar, 2005; Makkonen, 2003; Paige, 2003),
District Membership Differences
Finally, the decision was made to determine if differences existed in the
educational experience based on student enrollment in either EPS or MVPS, A
dummy variable for district location was used to determine if differences existed
simply because of district membership.
Data Sources
Secondary data was used for the portion of the study comparing school
districts* Because the data collected for the study were from mainly secondary
public sources and did not identify individual students or teachers, the University^
Human Subjects Review application was accepted with exemption status* The
process became much more difficult for the school district Human Subject Review
to collect data on individual schools. In the next two sections, the process used to
collect the data elements for the study is explained in detail.
District-Level Data Sources
All of the district-level data was available from reports through the
Colorado Department of Education^ (CDE) Web site. In the following sections,
67


the step-by-step processes are explained for gathering the data for this study, with
the intention of allowing future researchers the opportunity to replicate the study.
In addition, I may choose to repeat this study in a number of years to track changes
in Colorado schools*
School Environment
School Environmem was measured through adminislrator, principal,
classroom teacher, and instructional support turnover rates in each school district.
For this information, the report was titled ^Personnel Turnover Rate by District and
Position Categories" and was accessible from the CDE Web site. This report was
available from the CDE homepage by clicking on School/District Statistics, then
clicking on School/District Staff Statistics, next clicking on Fall 2005 Staff Data
and finally clicking on Fall 2004 Staff Data, Under each of these final pages was
the link to the report for the respective year* The administrator, principal, teacher,
and instructional support turnover percentages for 2003-2004 and 2004*2005
school years were used. Then, the 2003-2004 turnover percentages were subtracted
from the 2004-2005 turnover percentages to arrive at the 2003-2004 to 2004-2005
change percentages for the study. Based upon the rationale for this indicator
explained earlier, the lower the turnover rate means the more positive the school
environment. For the 2003-2004 to 2004-2005 turnover change, a negative number
shows turnover has decreased, meaning retention has increased.
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District Revenue Sources
Information was collected on each district^ revenue sources from reports
on the CDE Web site. For this informatioTi, the report titled ^Comparison of
Revenues and Other Sources'1 was used and was accessible from the CDE Web
site* This report can be located from the CDE homepage by clicking on School
Finance, next clicking on District Revenues and Expenditures, then clicking on
Fiscal Year 2004-2005 Revenues and Expenditures, and finally clicking on
Comparison of Revenues and Other Sources. This report identifies the district
revenue from a number of potential sources. For this study, the total local revenue,
the state share, the state Special Education funding, the state English Language
Learning funding, the state Gifted and Talented funding, and the total federal
revenue were used.
Revenue Expenditures
Information on each district's Revenue Expenditures was collected from a
report on the CDE Web site tilled "Comparison of All Program Expenditures (All
Funds)/1 To locate this report from the CDE homepage, click on School Finance,
next click on District Revenues and Expenditures, then click on Fiscal Year 2004-
2005 Revenues and Expenditures^ and finally click on Comparison of All Program
Expenditures (All Funds).
This report identifies each school district^ expenditures by categories,
including instruction! support services, community services, other, and total. The
69


instructional category includes salaries, employee benefits, purchased services,
supplies and materials, capital outlay, and other expenditures (Herrmann, Stroup, &
Moloney, 2006). The support services category includes pupil activities,
instructional staff activities, general administration, school administration,
operations and maintenance, transportation, food services, and other support
(Herrmann et al 2006), The Community Service category includes dollars paid
for providing services to the community. Finally, Other Expenditures includes
expenditures aside from those listed above.
For this study, expenditures were compared by the percentage spent for
instructi on asupport services, and non-instructiona purposes. The non-
instructional dollar category was created by combining community service and
other expenditures. Then, the instructional amount was divided by the total
expenditures to determine the percent spent on instructional activities. This process
was repeated to determine the percent spent on support services and non-
instructional activities.
Teacher Quality
Teacher Quality was measured in four ways: (a) years of experience, (b)
percent of teachers instructing in the area of their degree, (c) percent of days
teachers are absent, and (d) the average teacher's salary. Each of these four areas
was accessible from a School Accountability Report (SAR) and so a SAR was used
from one of the schools within each school district.
70


Ratio of Students to Professionals
For determining the ratio of students to professionals, information from a
SAR was used. For the ratio of students to teachers the number of teachers
employed by the district from the SAR under 14district full-time and part-time
teachers was collected. Full-time teachers were counted as one and part-time
teachers as one-half, meaning every two part-time teachers were recorded as one
full-time teacher. Then the school district student enrollment was divided by the
total number of district teachers* The same process was followed for determining
the student to administrator ratio and the student to professional ratio.
Student Characteristics
The Student Characteristic indicators consist of the percentage of students
qualifying for free and reduced lunch, the percentage of students qualifying for
Special Education, and the percentage of English Language Learners, All of the
information needed was available through reports accessible from the CDE Web
site.
These reports can be located from the CDE Web site by clicking on
School/District Statistics, then clicking on 2005 Pupil Membership, From here,
clicking on the report titled 4Tall 2005 Pupil Membership by County, District,
Ethnicity, Gender, and Grade Level," The groups were combined into the
following classifications: (a) White Americans, (b) Latino Americans, (c) Black
Americans, and (d) Other Americans, Finally, each group was divided by the total
71


enrollment to determine each ethnic groups percentage within the district's student
population.
For the free and reduced lunch portion, the report titled 4*K-12 Free and
Reduced Lunch Eligibility by County and District" was used. This report was
available from the CDE Web site by clicking on School/District Statistics, then
clicking on 2005 Pupil Membership, and finally clicking on the above report. For
this study, the information labeled t4% Free and Reduced" was used for each school
district.
Finally, for Special Education participants and English Language Learners,
the report titled 4tPupi] Membership by Instructional Program1' was used. This
report can be located from the CDE Web site. First click on School/District
Statistics, then click on 2005 Pupil Membership^ and then click on the report named
above* The numbers reported for both Special Education and English Language
Learner counts were used. Finally, each count was divided by the total district
population for the percentage of Special Education and English Language Learners
in the school district.
CSAP Scores
The district-level CSAP scores were used from the CDE Web site. This
report is available by first clicking on Assessment, then clicking on Visit the CDE
Unit of Student Assessment Web site link, next clicking on CSAP, and then under
the Data and Results category clicking on CSAP District and School
72


Disaggregated Data and clicking on CSAP Summary Data. From this point, the
reports titled "Reading Grades 3-10," stMath Grades 3-10^ "CSAP School and
District Summary Results, Reading Grades 3-10/' and "CSAP School and District
Summary Results, Math Grades 3-10'1 were used* Then the grading categories
were collapsed into three groups: (a) advanced and proficient, (b) partially
proficient and unsatisfactory, and (c) no score. Finally, the number from each
group was divided by the total number of students in the district to determine the
percent of students achieving in each testing group.
School-Level Data Sources
The data for the school-level analysis was mostly gathered through
published SARt with a few items gathered from school-level employees in EPS and
district-level employees in MVPS. Because it was not possible to locate all of the
information through publicly accessible means, the assistance of both school
districts was requested in collecting the remaining data points.
For both districts, the outside researcher protocol was followed. MVPS
accepted the research proposal and offered support by gathering reports with the
information requested for the study. EPS did not accept the research proposal on
the grounds that they did not have the budget to provide personnel to locate the
information requested. Because I was unable to use district-generated reports,
other avenues to locate the needed data were required. In the sections to follow, the
73


methods followed in gathering the data are outlined, including the alternative
avenues used to collect information.
Teacher Quality
The Teacher Quality indicator was made up of five variables including: (a)
years of experience, (b) percent of teachers instructing in the subject they received
their degree, (c) teacher absenteeism percent, (d) teacher retention rateT and (e)
Teacher Salary. The data for all five variables was found on the SAR. For the
variables years of experience, percent instructing in degree area, percent of days
absent, and salary, the data was simply recorded from the SAR, For retention rate,
the number of teachers who left the school last year was taken from the SAR and
subtracted this number from the total number of teachers at the school. Once again,
each part-time teacher was counted as one-half of a full-time teacher. Then, the
number of retained teachers was divided by the total teachers for the retention
percentage. This same process was followed using data from both the 2003-2004
and 2CM34-2005 school years and then averaged the two years for an average
retention rate.
Ratio of Students to Professionals
For determining the school-level ratio of students to professionals,
information from SAR was used. For the ratio of students to teachers the number
of teachers employed by the district was collected from the SAR under "your
74


school full-time and part-time teachers/1 As mentioned earlier, full-time teachers
were counted as one and part-time teachers were counted as one-half. Then, the
school student enrollment was divided by the total number of teachers. The same
process was followed for determining sludent to administrator ratios and counselor
to student ratios.
Leadership Experience
Because Leadership Experience is reported on each school's SAR, both
pieces of data were collected from the SAR* The information umber of years as
principal at any school and as principal at this school was used The nuTnbers
are reported in the same format used for the study.
Student Characteristics
The school-level Student Characteristic indicators consist of free and
reduced lunch percentages, Special Education participant percentages, and the
number of English Language Learners. The ethnicity of students and free and
reduced lunch percentages were available from reports accessible through the CDE
Web site. This report is available from the CDE Web site by click on
School/District Statistics, then clicking on 2005 Pupil Membership, From here,
clicking on the report titled *Tall 2005 Pupil Membership by School, Ethnicity,
Gender & Grade Level.11 Again like the district-level portion, groups were
combined into the following classifications: (a) White American, (b) Latino
75


American, (c) Black American, and (d) Other American. Finally, each group was
divided by the total enrollment to determine each ethnic groups percentage within
the school student population.
For the free and reduced lunch portion, the report titled **K-12 Free and
Reduced Lunch Eligibility by County, Districi, and School" was used. This report
can be located from the CDE Web site by clicking on School/District Statistics,
then clicking on 2005 Pupil Membership, and finally clicking on the above report.
For this study, the information labeled Free and ReducecT, was used for each
school district.
Although Special Education student population numbers are available at the
district level, they are not freely available for the school level. Because I had the
support of MVPS, the numbers reported from their district office were used. On
the other hand, the Special Education numbers for each school in EPS was
collected by a school-level employee. Although these numbers were gathered with
the best of intentions, they were not ^cleaned up" by the district-level employees.
Similar to Special Education enrollment numbers, English Language
Learner enrollment data is available at the district level but not broken out at the
school level. Again, like the data collection for the Special Education numbers, the
numbers provided from the district office were used for MVPS. For EPS, the
English Language Learner data was located from the district's Web site by
76


accessing each school profile where it listed ihe percentage of English Language
Learners enrolled in each schooL
CSAP Scores
The school-level CSAP scores were found from the CDE Web site. This
report can be located by clicking on Assessment, then clicking on Visit the CDE
Unit of Student Assessment Web site link, next clicking on CSAP, and then under
the Data and Results category click on both C5AP Summary Data and CSAP
District and School Disaggregated Data. From these points, the reports titled
Reading Grades 3-10, "Math Grades 3-10 CSAP School and District
Summary Results, Reading Grades 3-10, and CSAP School and District
Summary Results, Math Grades 3-10 were used. Like the district-level data, the
grading categories were collapsed into three groups: (a) advanced and proficient,
(b) partially proficient and unsatisfactory, and (c) no score. Finally, the number
from each group was divided by the total number of students in the district to
determine the percent of students achieving in each testing group.
Data Analysis
Once all of the data were collected, the data was entered into the Statistical
Package for the Social Sciences (SPSS) for analysis, SPSS (2005) is a computer
program that allows the user to collect, analyze, and manage data, SPSS is a
trusted research tool that has been used in the field of education for over 37 years*
77


Full Text

PAGE 1

_0.1_

PAGE 3

C

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Note. Colorado Student Assessment Program

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Note. Colorado Student Assessment Program

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Note. Population Profile of the United States:

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Note. Population Profile o/the United States: An Achievement Gap

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Shifting Policies

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all

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inputs outputs

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Looking Through the Social Justice Lens

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Appreciating the Complexity

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Involving the Privileged

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Empowering the Marginalized

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Guiding Questions Clarifying the Variables

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District-Level Analysis

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Figure

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School-Level Analysis

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Figure Study Methodology

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Study Limitations

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Concluding Introductory Remarks

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Note. Colorado Student Assessment Program Note. Colorado Student Assessment Program

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Note. Colorado Student Assessment Program Note. Colorado Student Assessment Program

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Note. Colorado Student Assessment Program Note. Colorado Student Assessment Program

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A Snapshot of Denver's Latino American Population Complexity of the Issue

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Differences Among Generations of Latino Americans

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Colorado's Residents

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Donning a Cap and Gown

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Colorado's Graduation Data

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more Denver's Latino Students

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Parent Involvement

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Generational Immigration Patterns

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A Leader with Laser-Like Focus

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Years of Experience

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Absences

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Salary

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Degree in Area

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Instructional Dollars

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Non-Instructional Dollars

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Per Pupil Revenue

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Calculating Funding Allowance Pupil Count

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Total Per-Pupil Funding

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At-Risk Funding On-Line Funding

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Local Share

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Property Taxes Specific Ownership State Share

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Other Funding

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District-Level Analysis

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Figure

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School Environment District Revenue Sources

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Revenue Expenditures Teacher Quality

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Ratio of Students to Professionals

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Student Characteristics CSAP Scores

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School-Level Analysis Figure

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Teacher Quality Ratio of Students to Professionals Leadership Experience

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Student Characteristics CSAP Scores

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District Membership Differences District-Level Data Sources

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School Environment School/District Statistics, School/District Staff Statistics, Fall 2005 Staff Data Fall 2004 Staff Data.

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District Revenue Sources School Finance, District Revenues and Expenditures, Fiscal Year 2004-2005 Revenues and Expenditures, Comparison of Revenues and Other Sources. Revenue Expenditures School Finance, District Revenues and Expenditures, Fiscal Year 20042005 Revenues and Expenditures, Comparison of All Program Expenditures (All Funds).

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Teacher Quality

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Ratio of Students to Professionals Student Characteristics School/District Statistics, 2005 Pupil Membership.

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School/District Statistics, 2005 Pupil Membership, School/District Statistics, 2005 Pupil Membership, CSAP Scores Assessment, Visit the CDE Unit of Student Assessment Web site CSAP, Data and Results CSAP District and School

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Disaggregated Data CSAP Summary Data. School-Level Data Sources

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Teacher Quality Ratio of Students to Professionals

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Leadership Experience Student Characteristics School/District Statistics, 2005 Pupil Membership.

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School/District Statistics, 2005 Pupil Membership,

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CSAP Scores Assessment, Visit the CDE Unit of Student Assessment Web site CSAP, Data and Results CSAP Summary Data CSAP District and School Disaggregated Data.

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Units of Analysis Principal Components Analysis

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Multiple Regression

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Figure

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Figure

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Uncontrollable District Factors

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School Environment

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Teacher Quality

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Ratio of Students to Professionals

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Figure

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Figure District Reading APM, All Students' Performance

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F 25.32,p

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Note. R2 F p p SEB

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District Reading APM, Latino American Students' Performance

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Note. P

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Note. R2 F(5, SEB R

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SD p p Note. R2 F p 0.05. B SEB

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SD *p
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R District Math APM, All Students' Performance F P R

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Note. R2 F p P

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M p B Note. R2 F P *p SEB

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F P R

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M P

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B SEB Note. R2 F(5, District Math APM, Latino American Students' Performance F P

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SD p R

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Note. R2 F B SEB

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F P R

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SD P p p

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B SEB Note. R2 F(4, 24.243,p P p

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District Setting and APM Categories Interpreting the APM Residual Categories

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Note.

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Factors Within District Control

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Note. Note.

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Note. Factors Beyond District Control

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Note.

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Figure

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Uncontrollable School Factors

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Teacher Quality

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Ratio of Students to Professionals

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Figure

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Figure

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School Reading APM, All Students' Performance F P R

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M SD B Note. R2 F P P SEB

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F P R

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SO 0.225 P p

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B SEB Note. R2 F(7, P P School Reading APM, Latino American Students' Performance F

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P SD R

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B Note. R2 F SEB F P

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M SD p p

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R R B SEB Note. R2 F(4, P P

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School Math APM, All Students' Perfonnance F P R SD P

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B Note. F SEB

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F p R School Math APM, Latino American Students' Performance

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M SD P p p

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B SEB Note. R2 F(6, P P p

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M SD P Note. R2 F P p SEB

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p R

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M SD *p p

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B SEB Note. R2 F(4,

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School Location and APM Categories Interpreting the APM Residual Categories Factors Beyond School Control

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Note. n n

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Note. n n:::: Factors Within School Control

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Note.

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Note,

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Note. Because

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Note.

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Note.

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Note.

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Note.

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Note.

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can

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District-LeveL Conclusions

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Note.

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Note. *p
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Note.

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School-Level Conclusions

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Note.

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Note. *p<0.10;

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Note.

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culture of expectations

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Tackling Secondary School Refonn

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Professional Teachers

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Essential Leadership

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Smaller Schools

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Include the Family

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Student Accountability for Social Justice

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Educational Expectations

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Curriculum Standards

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Literacy, Literacy, Literacy Acknowledge the Changing Society

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M SD

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SD

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SD

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SD

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SD

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SD

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Note. R1

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Note. R' P

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Note. P P

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Note. Rl p P

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Note. R2 p P

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Note. R2 P

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Note. R2

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No/e. R2 p

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Denver Post, Harvard Education Letter, 10(1). Education Week, 24(23), Newsweek, USA Today, Phi Delta Kappan, Improving schools from within: Teachers, parents, and principals can make the difference. Teaching for diversity and social justice: A sourcebook Headfirst Colorado, Schools struggle to reduce high teacher turnover. Latino student data called into question.

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Remedial and Special Education, 26(2), Cambridge Journal of Education, Education Week, 20(10), 1-3. Phi Delta Kappan, 85(10), Childhood Education, Education success: Empowering Hispanic youth and adults. Independent School, Community College Review, Education and Urban Society, Understanding Colorado school finance and categorical program funding. Learning and Motivation, American Journal of Education, Statistical power and analysis for the behavioral sciences

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Good to great: Why some companies make the leap .and others don't. Denver's Latino Students: A snapshot of education and opportunity. Raising the bar: Policy recommendations for high school reform. Pupil counts by racial/ethnic group. 2004 Colorado Education Facts. acts/2004 Colorado Department of Education 2005 District Rankings by Pupil Membership. Colorado school districts listed by setting. About concern America. Harvard Educational Review Special Issue: Immigration and Education, English Journal, Educational Leadership,

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Teachers College Record, Other people's children: Cultural conflict in the classroom Not a moment to lose: A call to actionfor transforming Denver's high schools. Colorado Student Assessment Program (CSAP). Minorities miss quality teachers. Annual report of the Aboriginal and Torres Strait islander. What is socialjustice? Journal of Curriculum Studies, NEA Today, Teaching immigrant and second-language students: Strategiesfor success Pedagogy of the oppressed. The path of least resistance: Principlesfor creating what you want to create. Phi Delta Kappan,

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Educational Leadership, Educational Leadership, Education and Urban Society, What's wrong with American high schools. Education Week, Education Week, Promoting diversity and social justice: Education people from privileged groups. School reform in Chicago: Lessons in policy and practice School reform in Chicago: Lessons in policy and practice University Business, School reform in Chicago: Lessons in policy and practice Facing reality in our high schools.

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Educational Leadership, Denver Post, Leadership without easy answers. Journal of Child and Family Studies, 3(4), Education Week, Denver Post, Journal of Education for Students Placed At Risk, European Journal of Social Psychology, Inside the black box of high-performing high-poverty schools. High schools should be harder, govs say. Harvard Education Letter, J Secondary analysis o/survey data.

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International Journal 0/ Obesity, Ordinary resurrections. Making money matter: Financing America's schools. Peabody Journalo/Education, Educational Leadership, 51(8),22-27. SPSS/or intermediate statistics: Use and interpretation Harvard Educational Review Special Issue: Immigration and Education, House OKs certification reward bill. Harvard Education Letter, Teaching immigrant and second-language students: Strategies/or success At risk youth: A comprehemive respome. Virginia Journal o/Social Policy and the Law,

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