AN ASSESSMENT OF THE FACTORS THAT DRIVE PARENTAL CHOICE
REGARDING OPEN ENROLLMENT AND INTRADISTRICT TRANSFERS
Christopher Alan Morris
B.S., California State University, Sacramento, 1995
M.A., National University, Sacramento, 2002
DISSERTATION
Submitted in partial fulfillment of
the requirements for the degree of
DOCTOR OF EDUCATION
in
EDUCATIONAL LEADERSHIP
at
CALIFORNIA STATE UNIVERSITY, SACRAMENTO
SPRING
2013
Copyright © 2013
Christopher Alan Morris
All rights reserved
ii
AN ASSESSMENT OF THE FACTORS THAT DRIVE PARENTAL CHOICE
REGARDING OPEN ENROLLMENT AND INTRADISTRICT TRANSFERS
A Dissertation
by
Christopher Alan Morris
Approved by Dissertation Committee:
________________________________________
Robert W. Wassmer, Ph.D.
________________________________________
Su Jin Jez, Ph.D.
________________________________________
Edward (Ted) Lascher, Jr., Ph.D.
SPRING 2013
iii
AN ASSESSMENT OF THE FACTORS THAT DRIVE PARENTAL CHOICE
REGARDING OPEN ENROLLMENT AND INTRADISTRICT TRANSFERS
Student: Christopher A. Morris
I certify that this student has met the requirements for format contained in the University
format manual, and that this dissertation is suitable for shelving in the library and credit is
to be awarded for the dissertation.
__________________________, Program Director
Carlos Nevarez, Ph.D.
iv
______________
Date
DEDICATION
This dissertation is dedicated to my wife, Lori, and daughters Olivia and Camille, and to
the countless students that have inspired me with their dreams and aspirations. Without
their support this would not have been possible.
v
ACKNOWLEDGEMENTS
The unwavering support of Dr. Robert Wassmer was key in providing me the
stamina to continue on this journey. Dr. Wassmer not only provided academic guidance,
but also lifted my spirits when the path to completion was not always visible.
From day one, Dr. Su Jin Jez forced me to produce only scholarship that I knew I
could be proud of and to never doubt in my own ability to succeed. Dr. Jez was never
reluctant to provide the coaching and feedback she knew I needed.
Dr. Ted Lasher’s promise to make this a team effort is evident in the cohesiveness
of the committee. His expertise in public policy and research helped me to turn an idea
into policy recommendations with the potential to impact the lives of students and
families across the state.
Dr. JoLynn Britt has been an enthusiastic supporter of my work. Dr. Britt helped
turn the daunting task of multiple types of analysis into an endeavor that allowed me to
grow professionally and academically.
As this journey comes to an end, I would like to express my sincere thanks and
appreciation to my extended family in cohort four. This amazing group of educators and
leaders will have an effect on public education for years to come.
vi
CURRICULUM VITAE
Education
M.A. Educational Administration, National University, Sacramento
B.S. Criminal Justice, California State University, Sacramento
Professional Employment
Vice Principal/Director, Vallejo City Unified School District, Vallejo, California
Principal, San Juan Unified School District, Carmichael, California
Principal, Plumas Lake Elementary School District, Plumas Lake, California
Vice Principal, Elk Grove Unified School District, Elk Grove, California
Fields of Study
Open enrollment
Education policy
Adolescent psychological, social, and emotional development
vii
Abstract
of
AN ASSESSMENT OF THE FACTORS THAT DRIVE PARENTAL CHOICE
REGARDING OPEN ENROLLMENT AND INTRADISTRICT TRANSFERS
by
Christopher A. Morris
With increased school choice options for parents, open enrollment in public
schools has seen significant growth. As parents seek greater access to educational
options for their children, urban schools and schools in high poverty areas have seen
enrollments plummet. This has led to a decrease in the educational opportunities for
disadvantaged students that remain at their home schools. Research on school choice has
focused primarily on charter schools and private schools, with minimal attention given to
the factors that lead parents to choose a regular public school other than their home
school within the same school district. With nearly 20% of all California students in
grades K-12 exercising some form of school choice, this study will more closely examine
the phenomenon of families choosing to enroll their children in regular public schools
other than their home school.
For this study, quantitative methods are used. Within the frameworks of rational
choice theory and social cognitive theory, this study answers the following questions: 1)
to what extent do schools have the capacity to affect the changes necessary to influence
enrollment patterns of their schools, and 2) to what degree do current school policies
influence open-enrollment and school choice decisions of parents?
viii
The participating school district for this study is a large comprehensive pre K–12
school district in northern California. The data for this study included demographic and
enrollment data for the entire study body. The second source of data was derived from
parent surveys of participants and non-participants in open enrollment.
The results of this study suggest that the greatest indicator of participation in open
enrollment is if the neighborhood school has a lower API than the district’s average.
Additionally, students that identify as “other Asian” and not specifically with one of the
groups identified, are White and speak a language other than English, or are female, also
have an increased likelihood of participation in open enrollment. Parents also indicated
that the availability of desirable programs was a significant factor in open enrolment
participation.
Keywords: open enrollment, school choice, transfer students, charter schools,
intradistrict, interdistrict, student achievement, secondary education, urban education
ix
TABLE OF CONTENTS
Page
Dedication ............................................................................................................................v
Acknowledgements ............................................................................................................ vi
Curriculum Vitae .............................................................................................................. vii
List of Tables ................................................................................................................... xiii
List of Figures ....................................................................................................................xv
Chapter
1. SCHOOL CHOICE AND STUDENT OUTCOMES .....................................................1
Introduction ..............................................................................................................1
Open Enrollment ......................................................................................................5
Impact on the Poor, People of Color, and Urban Communities ................10
Nature of Study & Research Questions .................................................................13
Theoretical Frameworks ........................................................................................15
Rational Choice Theory .............................................................................15
Social Cognitive Theory ............................................................................17
Significance of the Study .......................................................................................20
Remainder of the Study .........................................................................................21
2. REVIEW OF RELATED LITERATURE ....................................................................23
Social and Cultural Aspects of School Choice ......................................................24
Charter Schools ......................................................................................................38
Effects of Choice on Student Learning ..................................................................41
x
Impact of Choice on Non-Choice Schools.............................................................56
Continued Debate on School Choice .....................................................................57
Conclusion .............................................................................................................61
3. METHODOLOGY .......................................................................................................64
Introduction ............................................................................................................64
Research Questions ................................................................................................64
Population and Setting ...........................................................................................65
Data ........................................................................................................................67
Quantitative Methods Used in this Study ..............................................................71
Logistic Regression Method ......................................................................72
Survey-Based Method ................................................................................74
Sampling ....................................................................................................77
Role of the Researcher ...........................................................................................79
Protection of Participants .......................................................................................79
4. DATA ANALYSIS AND FINDINGS .........................................................................81
Introduction ............................................................................................................81
School District Data ...............................................................................................82
Descriptive Statistics ..................................................................................82
Logistic Regression ....................................................................................87
Analysis of Survey Results ....................................................................................91
Descriptive Statistics ..................................................................................91
Test For Equality of Means........................................................................96
xi
Summary ..............................................................................................................101
5. CONCLUSIONS AND RECOMMENDATIONS .....................................................102
Introduction ..........................................................................................................102
Overview ..............................................................................................................103
Research Questions ..............................................................................................103
Summary of Findings ...........................................................................................104
Discussion ............................................................................................................114
Policy Implications ..............................................................................................117
Recommendations ................................................................................................118
Future Research ...................................................................................................125
Appendix A. Probability in Finding a School Attribute Important ................................127
Appendix B. Survey to Parents Participating in Open Enrollment .................................128
Appendix C. Survey to Parents Not Participating in Open Enrollment ..........................129
Appendix D. GUSD Open Enrollment Application .......................................................130
References ........................................................................................................................131
xii
LIST OF TABLES
Page
2.1. School Attribute Rankings of 1,582 Parents in New York City Suburbs ..................38
2.2. Black Over-Representation in Charter Schools; Top 15 MSAs 2007-2008 ..............39
2.3. The Race and Gender of New York City Charter School Applicants and Students
in Traditional Public Schools from 2000 to 2006 .....................................................40
3.1. Primary Languages of Students Within GUSD ..........................................................68
3.2. Ethnic and Racial Categories of Students Within GUSD ...........................................69
3.3. English Proficiency Designations of Students Within GUSD ....................................69
3.4. Descriptions of Variables in Survey ..........................................................................75
4.1. Comparisons of Means of Students Characteristics Between Participants and
Non-Participants ........................................................................................................84
4.2. Logistic Regression Results .......................................................................................88
4.3. Statistically Significant Effects on Participation in Open Enrollment.......................90
4.4. Fit of the Logistic Regression Prediction...................................................................91
4.5. Descriptive Statistics of Survey Responses (Questions 1-5) .....................................93
4.6. Descriptive Statistics of Survey Responses (Questions 6-14) ...................................94
4.7. Descriptive Statistics of Survey Responses (Questions 15-18) .................................95
4.8. Comparisons of Means of Survey Responses (Questions 1-14) ................................99
4.9. Comparisons of Means of Survey Responses (Questions 15-18) ............................100
5.1. Programs that Influence Parents’ Decision to Stay at Their Neighborhood
School .....................................................................................................................111
xiii
5.2. Programs that Influence Parents’ Decision to not Enroll Their Child at the
Neighborhood School .............................................................................................112
xiv
LIST OF FIGURES
Page
1.1. K-12 Enrollment Over Time in California...................................................................6
1.2. Percentages of Students in School Type by Race / Ethnicity ......................................7
1.3. Numbers of Charter Schools in California from 1999 to 2008 ....................................9
1.4. Percentage of Students Enrolled by School Type from 1993 to 2007 .......................10
1.5. Math Scores Among 4th Grade Students in the U.S. from 2003 to 2011 ...................12
1.6. Math and Reading Performance of U.S. Class of 2011 by Race/Ethnicity ...............13
1.7. Factors Central to Social Cognitive Theory...............................................................19
2.1. Quality and Impact Ratings for Studies of Achievement in Magnet or Interdistrict
Choice Schools..........................................................................................................45
2.2. Percentage of Schools that Meet Half or More of Their Final Goals ........................50
2.3. Comparisons of the 4th Grade Students Performing at or Above Connecticut
Goal on CMT Writing Test .......................................................................................54
2.4. Comparisons of the 6th Grade Students Performing at or Above Connecticut
Goal on CMT Writing Test .......................................................................................54
2.5. Comparisons of the 8th Grade Students Performing at or Above Connecticut
Goal on CMT Writing Test .......................................................................................54
3.1. District Racial and Ethnic Distribution for 2010 – 2011 School Year ......................65
3.2. District Students Percent at or Above Proficient – Math 2008 – 2012 ......................66
3.3. District Students Percent at or Above Proficient – English Language Arts 2008 –
2012...........................................................................................................................66
xv
3.4. Enrollment Patterns at Study High Schools ...............................................................77
4.1. Comparisons of API Score of O.E. Participants and Non-Participants .....................85
4.2. Comparisons of Home Language of O.E. Participants and Non-Participants ...........85
4.3. Comparisons of Socioeconomic Status of O.E. Participants and Non-Participants ..85
4.4. Comparisons of Female of O.E. Participants and Non-Participants ..........................85
4.5. Comparisons of White, Non-English Home Language O.E. Participants and
Non-Participants .......................................................................................................86
4.6. Comparisons of Hispanic or Latino O.E. Participants and Non-Participants ...........86
4.7. Comparisons of South-East Asian O.E. Participants and Non-Participants ..............86
4.8. Comparisons of Other Asian O.E. Participants and Non-Participants.......................86
5.1. Characteristics Likely to Increase or Decrease Participation in Open Enrollment ..106
5.2. Graphical Representation of Numerically Significant Factors that Influence Open
Enrollment Decisions – From Logistic Regression ................................................107
5.3. Mean Scores of Statistically Significant Parent Perceptions Regarding Academic
Programs .................................................................................................................109
5.4. Conceptual Framework of Educational Goal Attainment ........................................124
xvi
1
Chapter 1
School Choice and Student Outcomes
Introduction
Open enrollment in public K-12 schools has gained significant momentum in the
United States over the past ten years. According to the National Household Education
Surveys Program (NHES, 2010), 80% of students were attending their school of
residence in 1993, whereas that number had declined to 69% in 2007. The study
indicates that while the number of students enrolling in private schools and home-schools
has increased, the largest percentage of families seeking alternatives did so by using some
form of school choice (NHES, 2010). It is important to note that interdistrict open
enrollment serves more students than any other type of school choice program (Center for
Education Reform, 2009).
In a recent Gallop Poll of Americans’ confidence in public schools, 29%
responded they had a great deal or quite a lot of confidence. That is a new low since that
question has been asked since 1973. This represents a disparity, however, in how
Americans perceive their neighborhood schools. Further, 37% of the Gallup Poll
respondents gave their child’s school a grade of A, whereas only 14% gave public
schools as a whole a grade of A (Gallup, 2011). This shows that the public’s confidence
in the once highly regarded public school system has eroded. Much of the erosion of
support for the neighborhood school model is a result of government policies intended to
help the increasingly diverse population of students that are potentially harmed by open
enrollment policies.
2
Although school choice is growing across the nation, California and the United
States’ mediocre performance worldwide in mathematics and reading has most people
agreeing that more public education reforms are needed. The Organization for Economic
Cooperation and Development administers the Program for International Student
Assessment (PISA) to representative samples of 15-year-old students from 65 school
systems around the world. Based on the most recent data from the class of 2011, U.S.
students ranked 32nd in math among those countries that participated. U.S. students fared
better in reading, with only 10 other countries outperforming the United States by a
numerically significant amount (Peterson, Woessmann, Hanushek, & Lastra-Anadon,
2011). The same study showed that students in California ranked 40th out of all the states
and District of Columbia.
Viewpoints about reform include greater accountability, increased educational
requirements for teachers, increased local control, and school choice options. The larger
question is to what end are these reforms intended to produce? There are the benefits for
each individual student and then there are the public benefits and improved social
outcomes. What is known through the research is that students who receive better
schooling are able to transfer their skills into higher income and better occupations, they
benefit from greater self-understanding, have more positive personal contacts, and enjoy
a healthier lifestyle (Levin, 2012; Culter & Lleras-Muney, 2008). The societal benefits,
on the other hand, are the health, legal, political, social, and economic benefits that come
from an educated society. What is also known is that higher achieving schools provide
3
greater access to a more rigorous curriculum, guidance in course-taking patterns, and
access to extracurricular activities (Lauen, 2007).
Culter & Lleras-Muney (2008) further explore the link between health, education
and wealth. With the knowledge that increased education leads to greater wealth, their
study of adults over the age of 25 found that as wealth and education increased, there was
a decrease in the use or abuse of alcohol, tobacco, and illegal drugs. Additionally, with
increased education, adults over 25 had reported increased exercise, household safety,
and access to preventive health care including flu shots, mammograms, and colon cancer
screening. Further, individuals with high social hierarchy (education, wealth,
employment) enjoy better health than those below and have lower rates of mortality and
morbidity (Adler, et al., 1994). When examining the positive benefits of the investment
one makes in education, researchers have agreed that the effect of an educated
community can be seen in better public health, lower population growth rates, greater
volunteering and financial giving, political stability, lower homicide rates, lower property
crime rates, and greater participation in democracy.
The effects are not always positive however. As wealth increases as a direct
result of increased education, individual spending and economic choices change. Prior to
open-enrollment policies, parents have been exercising choice through housing. With
earnings rising by approximately 10% for each additional year of post secondary
education, (Krueger & Lindahl, 2000), urban sprawl and an exodus to the suburbs have
been a result of families looking to escape urban schools. Negative externalities as a
result of this include increased air pollution and driving times, traffic congestion, need for
4
more roads and infrastructure, a depletion of open spaces, an increase in the
concentration of the poor in the cities, and a further decline in the quality of the public
schools in these centralized communities (Wassmer 2006 and McMahon 2004).
With nearly 20% of all California students in grades K-12 exercising some form
of school choice, this study will more closely examine the phenomenon of families
choosing to enroll their children in regular public schools other than their neighborhood
school. It will not examine the factors related to parents choosing to enroll their children
in private schools or home school programs. Although research exists on why parents
choose private schools over public schools, far less is known as to why parents choose to
enroll their child in a regular public school other than their own within their school
district (Dillon 2008; Grady 2010; Tenbusch 1993). This dissertation study identifies the
factors that influence a parent’s decision to enroll their child in a public school, within the
same school district, other than their neighborhood school. Additionally, this study
provides valuable information to education policy-makers to inform open enrollment and
school improvement policies. Lastly, school leaders can use the results of this study to
determine the extent to which their schools have the capacity to affect the changes
necessary to influence enrollment patterns of their schools.
This first chapter offers the necessary background for this dissertation. It does
this through the following. It first provides historical background on open enrollment in
California by examining current laws and analyzing enrollment trends of the nearly seven
million California K-12 students. Second, I will provide a detailed description of the
problem and rationale justifying further study. Next, there is a thorough discussion of the
5
theoretical frameworks used to analyze the phenomenon of intradistrict transfers in
California. Through the lenses of rational choice theory and social cognitive theory, I
examine the complexities of choice and human decision-making. Chapter one concludes
with a description of each of the remaining chapters.
Open Enrollment
In recent decades, more and more of California’s families have exercised some
form of school choice for their children. It is important to note that in school districts
with open enrollment policies, it could be argued that even those families that stay at their
neighborhood schools are in essence exercising the choice to stay. For the purposes of
this study, choice schools, or families exercising choice refers only to those students and
families that have chosen to leave their neighborhood school.
The are nearly seven million K-12 students in California enrolled in various
school types. Figure 1.1 shows the distribution of California K-12 students in private,
charter, and regular public schools. What is noteworthy about this chart is the rising bar
representing charter school enrollment. Though charter school enrollment is not what is
specifically studied here, it does offer an indicator of Californians’ dissatisfaction with
their neighborhood public schools. In 1998 – 1999 charter schools represented 1% of
California K-12 enrollment. By 2008 – 2009, this had grown to 4.2%. In actual numbers
there was an increase of 217,000 students enrolled in public charter schools.
6
Figure 1.1. K-12 Enrollment Over Time in California
Increasing numbers of school districts are providing families with the option to
exercise a form of school choice through their open-enrollment policy. More
specifically, many school districts allow for voluntary transfers to any age appropriate
elementary, middle, or high school within their district. The term used to describe these
transfers is intradistrict, meaning within. Conversely, interdistrict transfers describe
students attending schools in districts outside of their home school district. According to
the Policy Analysis for California Education PACE (1999), nearly one fifth of all
children nationwide, about seven million, no longer attend their neighborhood public
school, with nearly ten percent attending private schools (Fuller, Burr, Huerta, Puryear, &
Wexler, 1999). While open enrollment advocates sometimes argue that these policies
will most benefit students from lower socioeconomic backgrounds, it is white, affluent
and working-class families that exercise choice options with the greatest frequency. For
7
example, 22% of the students enrolled in a public school of choice were poor, 21% were
near-poor, and 57% percent were non-poor. Figure 1.2 goes on to show that while the
percentage of Black and Hispanic students enrolled in schools of choice is greater than
their proportion enrolled in neighborhood schools, it is still White students by a ratio of
more than 2:1 that make up students enrolled in schools other that their neighborhood
schools (National Household Education Surveys Program, 2010).
Figure 1.2. Percentages of Students in School Type by Race/Ethnicity
California’s policies related to open enrollment center around providing choice to
families with children in failing schools. In 2010, California passed the Open Enrollment
Act (SBX54), more commonly referred to as the Romero Bill. The intent of the act is to
provide an option for students enrolled in one of the 1,000 “low-achieving” schools in the
state to enroll in a different school with a higher Academic Performance Index (API) than
the pupil’s school of residence (California Department of Education, 2011). The purpose
of the Open Enrollment Act is to “improve student achievement and enhance parental
choice in education by providing additional options to pupils to enroll in public schools
throughout the state without regard to the residence of their parents”
8
(http://www.cde.ca.gov/sp/eo/op/faq.asp). The list of 1,000 schools consists of 687
elementary schools, 165 middle schools, and 148 high schools. Excluded from the list
are court schools, community day schools, schools with fewer than 100 valid scores, and
charter schools. Additionally, no LEA may have more than 10% of their total schools on
the list. California’s open enrollment law goes a step further than the mandates of the No
Child Left Behind Act of 2001. NCLB states that only students attending Title I schools
that have been identified as in need of improvement are eligible for transfer. California
does not have the Title I requirement (U.S. Department of Education, 2007).
Parental choices are private schools, charter schools, vouchers, magnet schools,
homeschooling, dual/concurrent enrollment, and more commonly, intradistrict and
interdistrict transfers. Presently, open-enrollment policies exist in 46 states with many
dating back to the 1960s following the Brown v. Board of Education decision outlawing
de jure, or lawful, segregation. In practice, however, a segregated system is often left in
place when white students use these policies to leave desegregated schools in favor of allwhite schools (Dillon, 2008). While charter schools represent the smallest number in
terms of public school options, their growth over the past decades illustrates the growing
demand for more school choice options. In 1992 California was the second state in the
nation to authorize charter schools. Figure 1.3 illustrates the growth in charter schools
over the past decade. States throughout the nation have experienced similar growth in the
number of charter schools and charter school enrollment. A reference back to Figure 1.1
shows that the growth in charter schools has occurred at a similar pace as the increase in
9
total charter school enrollment. As a result, charter schools are educating a growing
percentage of students in California schools.
Figure 1.3. Numbers of Charter Schools in California from 1999 to 2008
It is widely understood that charter schools and regular public schools have
different characteristics. Therefore, when examining choice, the two do not compare well
with each other. California Education Code section 35160.5(b) specifies that intradistrict
open enrollment is locally determined, and that each local educational agency (LEA)
must adopt rules and regulations establishing their open enrollment policy. Commonly,
schools allow for transfers-in providing there is space available. The California School
Boards Association, however, recommends each district maintain a 5% reserve of the
school’s capacity to accommodate students of residence. Figure 1.4 further illustrates the
growth in school choice from 1993 – 2007.
10
Figure 1.4. Percentages of Students Enrolled by School Type from 1993 to 2007
The minimal research available examining the perceptions of parents utilizing
their districts’ choice options combined with the 5% growth in enrollment for public
schools of choice, creates the opportunity for the results of this study to greatly inform
school policies and have a positive impact on the educational outcomes of students from
culturally and economically diverse backgrounds that choose to remain in their
neighborhood schools.
Impact on the poor, people of color, and urban communities.
The number of factors and challenges often experienced by low income and
minority families in attaining a quality education for the children, and California’s
increasing diversity, underscore the urgency in preparing our young people for future
success. With Black and Latino students comprising 57% of the student population,
Asian and Filipino students an additional 12.5%, and the increasing urbanization in
California, the effort to address the educational achievement of students in our most
needy schools takes on greater urgency. Given this performance, and the growth of open-
11
enrollment policies, policy makers must continue to examine ways to improve student
performance and educational outcomes for poor and minority students.
Increased open-enrollment options in California, and the exercise of this school
choice has led to declining enrollment in many public neighborhood schools. This
declining enrollment has especially occurred in the state’s urban public schools that
disproportionately serve low income and people of color. As a result, the potential exists
for a greater loss of programs in these types of schools leading to a further decrease in the
educational opportunities for the disadvantaged students that remain at their
neighborhood schools.
With increased deregulation of school assignment policies, home address is no
longer the sole determining factor in school assignment. Families with greater financial
means are able to access choice options more readily than families in poverty (Lauen,
2007). The challenge of concentrated poverty and shrinking resources for public schools
further compels policy makers and educators to examine current policies in order to
better meet the needs of students in these communities. When low-income students are
concentrated and separated from their middle-income and middle-class peers, there tends
to be less academic support. Moreover, middle-class schools are twenty-two times more
likely to be high performing than schools in high-poverty areas (Kahlenberg, 2006).
Scores from the 2011 National Assessment of Educational Progress shows that while
students from all economic groups showed academic gains, there still exists a gap
between students of poverty and middle-class students. The chart in Figure 1.5 illustrates
this gap in math achievement. Further, the chart also shows that with the growth of
12
school choice options, the achievement gap between those students in and out of poverty
remains consistent. It suggests that poverty is the greatest predictor of low academic
achievement regardless of school choice.
Figure 1.5. Math Scores Among 4th Grade Students in the U.S. from 2003 to 2011
As recent as 2011, 42% of white students were identified as proficient in math
while only 11% of African American students, 15% of Hispanic students, and 16% of
Native American students were identified and proficient. Figure 1.6 shows the math and
reading performance of the United States’ class of 2011 (Peterson, Woessmann,
Hanushek, & Lastra-Anadon, 2011). This data further illustrates the gap that exists
between white students and students of color. As parents of minority students see their
children fall further behind their peers, it creates an even greater sense of urgency in
seeking educational options that they believe give their children increased access to
quality education.
13
Figure 1.6. Math and Reading Performance of U.S. Class of 2011 by Race/Ethnicity
Nature of Study & Research Questions
This study involves both qualitative and quantitative strategies. The quantitative
analysis involved using logistic regression and means comparison. The qualitative
strategy analyzed the survey responses from participants and non-participants in open
enrollment. I used these strategies to explore the demographic characteristics of those
who choose to participate, and not participate in open enrollment, and to study the first
hand perceptions of parents at the center of the phenomenon of enrolling their children in
public schools other than their neighborhood schools. The research questions are
answered using both research methods. In order to understand the perceptions of parents
choosing to enroll their child in a school other than their home school, this study
specifically perform these research tasks:
1. Using logistic regression analysis of a dependent variable measuring whether a
student left his or her neighborhood school for another school in the same district,
14
I uncover what variables (available in standard data files) exert a significant
impact on this choice. This analysis allows me to predict which variables are
related to parent decision-making regarding school choice.
2. I also analyze results from a survey or parents. This information allows me to
probe more deeply into the motivations for school choices, thereby helping me to
make policy recommendations.
The purpose of this study is to uncover the factors leading to the phenomenon of
parents moving their children from neighborhood schools and use that information to
inform open enrollment and school improvement policies. Additionally, this study seeks
to uncover the extent to which schools have the capacity to change or influence
enrollment patterns of their schools. I am to answer the question: To what degree do
current school policies influence open enrollment and school choice decisions of parents?
The groups of parents to be analyzed in this study are those parents who have chosen to
enroll their child in a regular public school other than their assigned school of attendance.
Researchers have underscored the need for policy makers and school officials to
thoroughly understand the dynamics of school choice by making the argument that
successful policies cannot be implemented without a thorough theoretical understanding
of the traditional school system and the implications to families that choose to go outside
that system (Koedel, Betts, Rice, & Zau, 2009).
15
Theoretical Frameworks
The complexities of human choice and the ways in which individuals express
their preferences in schools for their children may only be partially quantifiable.
However, through the application of theories used in the fields of economics, and
psychology, I posit how parents’ perceptions influence those choices. These theoretical
approaches are described next.
Rational Choice Theory.
Rational Choice Theory (RCT), originally developed by economists, is useful in
understanding human decision-making based upon their maximizing self-interest. In a
broad definition of rationality, it implies a degree of sensibleness and logic. Rational
Choice Theory, however, uses a more narrow definition of "rationality" to mean that an
individual acts to maximize their personal advantage (Abell, 1990). It takes into account
motivation, goal attainment, and personal advantage. The theory of Rational Choice will
help to explain and understand this specific human behavior and the phenomenon of
parents choosing to enroll their children in schools other than their neighborhood school.
Further, Rational Choice Theory attempts to examine how those individual private
choices produce outcomes that may have social consequences. Those consequences will
be described as the negative externalities occurring as a result of their choice. Under
Rational Choice Theory, it is expected that parents do not take into account these
negative externalities when making a choice to pull a child out of a neighborhood school
and move them to another school. Only when parents use this in deciding to leave or stay
16
at their neighborhood school cold they then assess the benefits and costs of making this
choice.
While Rational Choice Theory is the basis of economics, in recent decades
researchers have expanded its use to sociology, political science, and anthropology
(Green S., 2002). At its most basic elements, Rational Choice Theory attempts to analyze
individual or group behavior and examine how those individual choices produce
outcomes. The simplest model examines the relationship between buyers and sellers.
This study, however, will supplant the buyers with parents of school-age children, and
sellers with schools and school districts. Additionally, the readers must acknowledge the
role of parents as consumers (Frankenberg, Siegel-Hawley, & Wang, 2010).
Denzin (1990) cites the early work of many authors when he argues that the
following assumptions are at the center of Rational Choice Theory. First, humans are
egotistical, hedonistic, asocial, rational, and purposive in their actions. Secondly, when
choosing the most rewarding course of action, emotions and sentiments are factors.
Third, choices are made based on principle, information, history, an assessment of the
consequences, and weighing the chances of achieving the desired effect. This means that
in order for a rational choice to be made, one must know the desirable and undesirable
consequences of a choice, and must know how the choice may affect other plans. Most
importantly, this choice cannot violate any of their held principles. The choice is also
made within the context of the individual or family, with little to no consideration of a
broader social impact.
17
The fundamental question is how do parents of school age children as consumers
of the public education services offered to their children reach decisions on where to
attend? While some decisions are based on custom or habit, rational choice premises that
choices are made that best help both buyers achieve their personal objectives. Due to a
lack of full information on the benefits and costs involved in different choices, and the
expense to the family of gathering this information, decisions made about schooling may
revert to relying on custom or habit. For example, a parent may say, “the school is where
all my other children went, so why not send my youngest there,” Or “this is the school
that my children’s friends are attending, I will also send her there.” Much of the purpose
of this study is to help uncover the factors parents consider when selecting a school for
their child. There will also be consideration of the limitations of rational choice as a
guide to public policy.
Social Cognitive Theory.
Social Cognitive Theory is an additional framework that will be applied to this
study. In contrast to RCT, which fails to consider human group life, emotions, or human
experience (Denzin, 1990), Social Cognitive Theory suggests that people model their
behavior after others they identify with, and deals with the cognitive and emotional
aspects of behavior. It is often used to explain behavior patterns and evaluate behavioral
change based on environment, people, and behaviors.
As Social Cognitive Theory relates to this study, it is hypothesized that parents’
perceived social status changes by enrolling their child in another school. It follows that
18
this perceived change in social status and self-identification with a social group will
transfer into a positive effect on student learning outcomes and increased child’s selfefficacy. Although this study does not present the empirical evidence in support of this
claim, it is widely held that exposure to economic resources, social prestige, and social
power have a positive influence on learning experiences (Thompson & Dahling, 2012).
The core assumption regarding social cognitive theory is that environment,
people, and behavior are three factors that are constantly influencing each other. Further,
according to Bandura (1997), a person’s actions are not only reinforced by the actions of
others, but also by their environment. Additionally, of the concepts of SCT identified by
Baranowski et al. (1997), the following are most use useful as they relate to this study:

Environment – provides opportunities for social support

Self-control – provides opportunities for self-monitoring, goal setting, problem
solving, and self-reward

Observational learning – behavioral acquisition that occurs by watching the
actions and outcomes of others

Reinforcements – promotes self-initiated rewards and incentives (Glanz et al,
2002, p.169).
The conceptual model in Figure 1.7 further illustrates the interchange between the factors
central to SCT (Pajares, 2002).
19
Figure 1.7. Factors Central to Social Cognitive Theory
Similarly, there is a degree of self-identification and self-stereotyping that occurs
when children are made aware of social grouping (Johnson & Shapiro, 2003). Bennett
and Sani (2008) hypothesize that when individuals categorize themselves as members of
a social category, a process of depersonalization takes place. More specifically,
depersonalization causes members of the same group to begin to develop a sense of
similarity and will accentuate those traits that distinguish themselves from other groups.
Moreover, new members to the group will begin to adopt those group-specific traits.
While there will be little discussion of the interplay between competition and market
forces in education, it is important to note that a key assumption of proponents of school
choice is that competition will improve the level of schooling for all. Further research
may explore the hypothesis that cooperation among schools and school districts can have
an even greater positive effect on the educational outcomes of students.
20
Significance of the Study
This study is significant because there are a growing number of
socioeconomically disadvantaged students unable to access current school choice options.
This leaves them stuck in schools where the threat of exit is improbable. Where school
choice is exercised, there are also a large number of impoverished parents who remain at
a neighborhood school because they do not have the resources to exercise choice (de
Souza Briggs, 1997; Dee, 1998; Public Policy Forum, 2002). Two imperatives for
California school leaders have emerged. First, for school leaders in urban schools and
schools whose geographic isolation does not allow for parents to exercise school choice,
They must have adequate information in order to improve the educational outcomes for
all of their students. The second imperative is for school leaders understand this
phenomenon better so they can improve the characteristics of the schools that drive
parents away. Since interdistrict transfers account for the majority of school choice
options, less data is available on the impacts of choice when students stay within their
districts (intradistrict transfer). In these cases, the imperative is not to help people to
exercise choice; rather it is to create school environments that will make people want to
stay.
During this time when the need for high-skilled workers has grown and high rates
of unemployment have persisted, educators and policy makers must use every tool to
ensure that America’s young people have the skills and abilities necessary to succeed in
the global economy of the 21st century.
21
Remainder of the Study
This dissertation contains five remaining chapters. This chapter introduced the
study, contained a description of the problem, described the nature of the study,
summarized the theoretical frameworks, provided operational definitions, outlined
assumptions and limitations, and the significance of the study. Briefly restated, the
problem is that as open enrollment and school choice continue to grow, students from
economically and culturally diverse backgrounds face even greater challenges when they
remain in “hollowed out” public schools. While students in the United States and
California continue to show gains on standardized tests, the gap between poor and nonpoor students, and between white students and students of color remains wide. Through
the theoretical lenses of Rational Choice Theory and Social Cognitive Theory, I will
examine the perceptions of parents that choose open-enrollment options for their child.
The study will consist of both qualitative and quantitative research questions.
Chapter 2 provides a review of relevant literature on open enrollment, social and
cultural aspects of school choice, and achievement effect of school choice. The
psychological and social influences of school choice are also examined with an emphasis
on the effect of choice on those that remain at their neighborhood schools. Chapter 2 also
includes a brief discussion of the Cultural Ecology Theory and the characteristics that
have accompanied minority schooling in America.
Chapter 3 details the methodology used in this study. In Chapter 3, sampling
procedures, data collection and analysis, and issues related to validity and reliability are
presented.
22
Chapter 4 presents, explains, and interprets the data. I begin by presenting the
analysis of the logistic regression from the data provided by the district. The logistic
regression identifies those variables that exert a statistically significant impact on the
choice to participate in open enrollment to not participate. Next is the correlation and
mean comparison showing which factors (available through a self-administered survey of
parents in this school district) are significant in relation to why families choose to
participate in open enrollment and leave their neighborhood school, or choose to remain
at their neighborhood school and not participate in open enrollment. Lastly, through the
analysis of written responses, I look for any patterns that may indicate to what degree do
current school policies influence open enrollment and school choice decisions.
Chapter 5 summarizes the major findings and outlines areas for further research. I
provide further explanation of those variables I found statistically significant in relation
to school choice decisions. In Chapter 5 I revisit each of the research questions and
specifically describe how each question was addressed. Chapter 5 concludes by
providing recommendations for policy makers and K through 12th grade school leaders.
23
Chapter 2
Review of Related Literature
The vast majority of research on school choice examines enrollment patterns,
student achievement, specific demographics of families opting for choice, or seeks to
evaluate charter or voucher programs. There is little research on the psychosocial
influences on parents when making decisions about schools for their child. This study
closely examines the attitudes, perceptions, and influencers of parents who choose to
enroll their child in a school other than their home school. The questions central to this
study are (1) what variables, if any, significantly influence parents’ choice and selection
of school for their child during open enrollment, (2) to what extent do schools have the
capacity to affect the necessary changes to influence enrollment patterns, (3) and to what
degree do current school policies influence open enrollment and school choice decisions?
The following subsections categorize the literature reviewed in this chapter: (a) social
and cultural aspects of school choice, and (b) achievement effects of school choice.
Much of the data presented comes from California schools, however, the issues raised
and the questions posed are representative of large urban school districts across the entire
country.
I specifically chose to examine the following themes and subjects for this
literature review: (a) open-enrollment, (b) school choice, (c) school competition, (d)
school reform, (e) the economic impact of school choice and open enrollment, (f) urban
schooling, and (g) charter schools. The vast majority of the literature uncovered statistics
24
and data resulting from quantitative research. There is a significant body of knowledge
related to student outcomes and achievement in public, charter, and private schools.
Additionally, many studies have been conducted to evaluate the effectiveness of school
choice models in the areas of racial integration, student achievement, access to programs,
and efficiency. This study extends the literature by examining the psychological and
social perceptions that influence parent choice decisions. Additionally, this study will
explore the relationship between rationality and social influences when making school
choice decisions.
Articles and studies published in peer-reviewed journals account for the majority
of the literature reviewed in this chapter. However, additional data was gathered from
state departments of education, the U.S. Department of Education, university studies, and
from papers published by seminal researchers on school choice and economic theory.
Social and Cultural Aspects of School Choice
Prompting many to advocate for school choice is the disproportionate number of
non-white children at risk of dropping out of high school, unemployment, imprisonment,
and poverty. This resulted in greater efforts to try to improve the educational outcomes
of this group. One such method, though controversial, is through increased school choice
options. In general, choice refers to decision-making when faced with two or more
possibilities. As it relates to this study, choice is used to describe the right of parents to
be able to choose where to send their children to school. Parents exercise school choice
through enrollment in charter schools and private schools, through participation in school
25
voucher programs, and through school district open-enrollment programs. In accordance
with a 1993 state law, California public school districts have created intra- and
interdistrict public school choice policies, whereby a student may choose to attend a
participating school outside the student's neighborhood if space permits. Under the
federal No Child Left Behind Act (NCLB), school districts must allow students to
transfer out of consistently low-performing or persistently dangerous schools, as defined
by the state (EdSource, 2012).
The controversy on the use of school choice is primarily fought on two fronts.
First, it is argued without adequate social and financial resources, families in
disadvantaged neighborhoods are less likely to seek, apply for, and travel to schools of
choice (Lauen, 2007). Secondly, school choice has the potential to cream the best
students from schools and leave those hollowed-out and filled with the weakest students
and fewer economic resources.
Segregation in metropolitan areas concentrates poverty, intensifies segregation in
schools, and isolates the most disadvantaged children limiting their access to educational
and economic opportunity (Orfield & Wallace, 2007). Often, de facto segregation occurs
as a result of residential patterns of Black and Latino families and a lack of affordable
housing within the boundaries of the most effective schools. A rarely discussed
consequence of public school integration efforts is the toll it takes on communities and
families. With students often traveling more than an hour to school, it not only creates
physical distance, but social distance to the community. The disconnect that occurs when
children do not go to school with their neighbors, or are not able to participate in the
26
kinds of extracurricular activities that happen after school, has a disproportionately
negative effect on disadvantaged African American students and families. White
students and students of higher socio-economic status that live within the boundaries of
the choice schools do not experience this community disconnect (Smrekar & Goldring,
1999). An ideal model of integration would include integrated neighborhoods where
Blacks and whites live next to each other and there is a real opportunity for discourse,
communication, and understanding. Sending kids off to integrated schools has many
convinced that any gains are temporary and insufficient to bring about any lasting
change. From the point of view of teachers, by eliminating the schools of already
disadvantaged Black children and bussing them to other communities, they risk loss of
their culture, their history, and their heritage (Morris, 1997). When asking parents,
however, to consider the personal costs of bussing, they cited the benefits of diversity,
tolerance, and integration as being worth it (Smrekar & Goldring, 1999).
Notably, what parents described as good schools tended to be in predominately
white suburbs (Johnson & Shapiro, 2003). For many, schools, housing, and race are
intertwined in such a way that a discussion of one leads to a discussion of the others.
When considering school choice, parents with financial means continue to exercise
school choice by residence to a degree that families in poverty could ever hope to do.
When Johnson & Shapiro (2003) asked white parents to explain how they chose their
neighborhood, most parents explained right away that it was because of the school or
school district. Their interviews revealed that when asked to explain what “good
neighborhoods” and “good schools” meant to them, parents’ explanations usually
27
included a discussion of race. When asked if race played a role in any of the decisions
she had made, a white parent replied, “I have to be honest and…I’m probably wrong for
saying it, but truthfully, it’s in the back of my mind, yes.” She goes on to say, “if there
was a nice Black family…and they bought the house next door to us and had the same
values and the same desires and goals that we had…I wouldn’t be afraid to have my
children carpool or sit by them. I guess I am a racist deep down inside, and I feel guilty
for admitting that” (p.175). This statement reflects an internal conflict, however, an
examination may reveal that her sentiment is more that of classism rather than racism.
Johnson (2006) goes on to explain how parents with higher degrees of wealth are
able to “buy-in” to good public schools in good neighborhoods, or opt out of the public
school system all together and send their child to a private school. She explores the
paradox that exist between the belief in the American Dream where people will be
rewarded for their efforts and that anything is possible no matter your background, and
the understanding that wealth provides advantages especially in education. Further, those
families without wealth had severely limited options (Johnson, 2006). Families she
interviewed reported openly that were aware of the advantages they had by having
wealth. Her description of the power of the American Dream Ideology may help to
further explain the eagerness of many low-income families and parents of traditionally
underserved students clinging to the hope that sending their children to the perceived
good schools will overcome the disparities created by wealth or the lack thereof.
Johnson and Shapiro’s interviews also revealed that many of the white families in
the St. Louis suburb they studied feared that as more Blacks moved in there would be
28
increased violence, drug use, lower property values, and an overall deterioration of the
neighborhood. Relating this sentiment back to the question of why Black families
believe it is worth it to bus their children to other communities leads to another question
to consider and the challenging of widely held beliefs. If the sentiment reported by
Johnson & Shapiro is pervasive and well known in Black communities, it is then
conceivable that financial means is not the only impediment for Black families to move
into predominately white neighborhoods. In other words, do Black families know that
they are not welcome, and therefore remain in the communities that offer social
cohesiveness? This question may never be answered or reconciled. What exists is a
paradox. If we accept that all parents, regardless of race and class, want the best for their
children, then why would certain families be unwelcome? Further study on race and
cultural acceptance may help to answer this. This again highlights the conflict between
the social goal of integration and the private goals of acceptance. More specifically, it
appears that in the hopes of breaking enduring patterns of racism and social isolation,
parents of disadvantaged students are willing to sacrifice and send their children to
neighboring schools in the hopes that they realize the educational benefits promised to
them (Johnson & Shapiro, 2003; Morris, 1997; Smrekar & Goldring, 1999). Mreover,
because Blacks are overrepresented in poor communities and are often characterized as
not having the same aspirations as Whites, it is clear to some Blacks that they must work
harder and achieve greater in order to overcome these enduring stereotypes. This
recognition supports data presented in the later discussion of charter schools showing that
charters attract a higher percentage of Black students than traditional public schools, in
29
part because they tend to be located in urban areas. This fact may lead to the following
conclusion: When opting for school of choice, in contrast to schools in predominately
white suburbs, Black parents will prefer to send their children to schools that are
perceived higher quality if those schools are located in urban areas as opposed to schools
in the suburbs in order to remain in areas that are culturally familiar.
As a result, many of the efforts at trying to improve the K-12 educational
outcomes of the underclass in the United States have focused on providing increased
school options to Black, Latino, and historically underserved students. Some see school
choice as one such mechanism for change. The intent of such choice is to empower
parents to gather information and shop around for schools that best satisfy his or her
given preferences. Exercising this choice is expected to benefit those that leave an
underperforming school and even possibly those that stay behind in that administrators
will be forced to reform their education delivery practices or even lose more students and
experience drastic declines in enrollment.
In contrast to the theory of how school choice will improve all schools,
superintendents reported making significant programmatic cuts due to the strain of
decreased enrollment and the loss of revenue rather than making dramatic improvements
to instruction or the delivery model. Those cuts included cutting art, music, and physical
education, eliminating foreign language and science in elementary school, increasing
class size, eliminating field trips, a reduction in counseling, and eliminating programs in
high school. This is exacerbated when families choose to go outside of the their home
district because the money follows the child. Therefore, it stands to reason that urban
30
high-poverty districts will be affected most by declining enrollment due to choice. Those
districts, however, that experienced gains in enrollment had the opposite result (Jimerson,
2002). The pattern that emerges is central to those advocating for a market-driven
education system. The programs and activities that parents find most appealing and
attractive are the ones that are cut when districts face declining enrollment (Fowler,
2002). This exacerbates and speeds up the school’s decline. Any hopes that the school
will improve are significantly impaired and those that suffer are the students who are
unable to access any of the school choice options presented to them. The time it takes for
reform efforts to take hold and to see a corresponding increase in school and faculty
efficacy is not always congruent with the high-anxiety and pressure schools face to
improve now (Muhammad, 2009). Further longitudinal studies may explore student
achievement in both the schools that receive and lose their disproportionate numbers of
students through choice programs.
Many see school choice as a means for White families to bypass integration
efforts and remain suspicious that choice will improve the quality of schools attended by
mostly Black and Latino students. Critics point to post Brown v. Board of Education
policies of the South. These “freedom of choice” plans were a way for white families to
avoid forced integration and continue to deny Blacks, Hispanics, and Native Americans
equality of educational opportunity (Farrell, Jr. & Mathews, 1990; George & Farrell, Jr.,
1990; Jones-Wilson, Arnez, & Asbury, 1992). It follows then that if the poor cannot
move out of their neighborhoods to escape their ineffective schools, as the more affluent
have already done (Johnson, 2006), then the school or school district essentially has a
31
monopoly over them. In theory, providing choice can break this monopoly. However,
lack of transportation and cultural barriers may result in low income, historically
disadvantages, and students of color remaining in their failing schools.
Exposure alone to high-performing students, however, may be sufficient to
increase the outcomes for below-average students. Bennett and Sani (2008) go on to
explore the link between group identification and the depersonalization that takes place
when members of the same group begin to use terms like “we” and “us” instead of “I”
and “me.” Further, this depersonalization, they argue, causes group members to begin
possessing the stereotypical characteristics that are normally assigned to that group. In
the case of academics, traits like hard working, involved, motivated, opportunistic, and
problem solver may be gradually picked up as new students are assimilated into the new
group.
Although this study does not attempt to explore the psychological, social, and
emotional conditions experienced by students who transfer schools, the belief that
students’ achievement will increase through the exposure to high-achieving students is
best supported by the theory of cultural ecology. Broadly, it refers to how humans adapt
to their physical and social environments in order to survive. For several decades John
Ogbu studied the performance of minority children in school and has identified the two
sets of factors influencing minority schooling; 1) the educational system, and 2)
community forces. In his work with Herbert Simons (Ogbu & Simons, 1998), they use
the term minority schools to describe the characteristics under which minorities have
been historically educated in the United States. Not only the urban locations of many
32
schools, but the perceptions and cultural characteristics of those doing the educating.
Broadly, the educational system is comprised of policies, practices, and reward systems
in place that reinforce and define academic achievement. The system is also
characterized by how minorities or any subordinate group are treated in schools. Ogbu
and Simons found that the denial of opportunity and rewards to minorities characterized
school systems (1998). Community forces are the perceptions of minorities and how they
respond to the mistreatment they have experienced by whites. Discrimination,
denigration of language and culture, policing practices, and unwarranted barriers all
influence how minorities respond to education (Ogbu & Simons, 1998).
They
concluded that even if some African American students possessed the academic ability to
succeed, many would not because high achievement was considered “acting white.” As
his theory relates to school choice, it is important to consider whether moving minority to
students to perceived “good schools” in the suburbs will have a positive effect on their
academic achievement.
The relationship between school choice and race has yet to be disentangled to a
degree that will allow policy makers to implement effective strategies to eliminate the
achievement gap between Black and white students. In 2003, Ogbu & Davis studied an
affluent suburb in Ohio where white and Black social classes were similar. In their
results, they find that although Blacks express high goals, they do not always exhibit or
engage in the behaviors that promote academic success. Their findings contradict, to
some degree, the self-categorization theory espoused by Bennett and Sani, (2008). In my
33
earlier discussion of enrollment patterns, we found that when exercising choice, Black
families are more likely to enroll in schools located in urban areas.
Since many school and district leaders base school choice efforts on
desegregation and improved outcomes for minority students and the poor, the discussion
would not be complete with consideration of how minorities respond to schooling.
Changes to the school structure alone do not address the notion that a students’ academic
success is impacted by community forces, and how those community forces can
contribute to the failure of minority students (Foster, 2004). The discussion of school
choice policies related solely on the “system” would be inadequate. If the ultimate goal
is the academic success of those groups that have been historically marginalized by
society, then the school reform efforts need to take on a broader scope and address the
community forces in tandem with “the system.” Ogbu implies that academic
achievement of minority students cannot be achieved without both the systemic changes
combined with strategies to address the poorly adapted cultural norms that exist in many
communities. closure. Further, proponents of open enrollment have only attempted to
address the policy and practical factors within the “system” without addressing
“community forces” which will have a greater or equal impact on the overall educational
outcomes of minority students (Ogbu & Simons, 1998).
While race, poverty, and mobility remain powerful contextual explanations in
school choice patterns, additional push and pull factors are relevant in school choice
decision-making. Parent education, experience, and income may also factor in to
decision-making. Further research in this area specifically related to school choice and
34
observed patterns may attempt to answer the question of whether low-income or less
educated parents are equipped to make good decisions. Lareau (2002) does however
provide insight into how observed class differences impact childrearing. As her work
relates to school choice, she notes that reliable transportation and flexible work schedules
are necessary for parents to cultivate and transmit the advantages of social class.
Furthermore, parents’ ability to gather and process information is essential if they are to
avoid making poor decisions (Schneider, Marschall, Teske, & Roch, 1998). Ball and
Gewirtz (1998) and Ridenour et al. (2001), divide parents into three categories of
choosers: the skilled/privileged, the semi-skilled, and the disconnected:
1.
The privileged/skilled chooser is more likely to know how to choose more
selective schools because of their substantial personal experiences with schools
and social capital.
2.
To a lesser extent, the semi-skilled chooser, who has some knowledge but who is
less able to determine fiction from fact, may experience subtle personal benefits.
3.
The disconnected chooser is unable to critically examine and compare a wide
range of schools. It is not due to a lack of interest, it is more often a lack of
knowledge (Ridenour, Lasley, II, & Bainbridge, 2001, p. 75).
Ridenour, et al.’s theory that there exists less able choosers reinforces the position
of those opposed to widespread choice policies because it relies on parents being able to
make well-informed choices, but not all parents are the highly informed and engaged
consumers that are necessary for them to compete in an education marketplace.
Schneider, Marschall, Teske, & Roch (1998) go on to describe four stages that parents
35
go through when deciding what and how to choose: 1) parents must decide on a set of
preferences that they want to realize, 2) parents engage in information gathering, 3) make
trade-offs between neighborhood school and choice school, and 4) monitor the school’s
and their child’s performance to make sure that their choice was a good one. They go on
to assert the “disparities in different types of parents’ resources, involvement, and
cognitive abilities are particular concerns when considering how parents will play an
expanded role in choosing schools” (p. 490).
There is little disagreement that more advantaged parents generally have better
knowledge about relevant factors in choosing a school (Archbald 2000; Teske and
Schneider 2001). What also emerges from this debate is the cultural divide that exists
between poor and middle-class families. During the 1990s, a time when school-choice as
a public policy grew, many researchers explored the cultural conflicts that exists and
compared how families from different backgrounds often seek different outcomes for
their children (Cookson 1994; Delpit 1995; Elmore 1991; Fuller, Elmore, and Orfield
1996; Henig 1994; and Hirsch 1996). Several themes emerged from their work.
Notably, poor people are as committed to the education of the children as the more
economically advantaged. Secondly, in many urban centers, school choice movements
have the capacity to tear communities apart and breed a culture of racial resentment and
bitterness between those who have exercised choice and those who have not. Next, for a
complete understanding of school choice, one must accept that conflict will arise from the
practical applications of such polices and the moral imperative to provide all students
with access to the best educational options. Lastly, policy changes alone are inadequate
36
in any school reform effort and that without changes, those most at risk and the
marginalized are the ones most likely to suffer from a system that collapses.
“Educational reform requires a more profound, more lasting, and more structural
commitment to families, teachers, and children (Cookson, 1994, p. 11).
Delpit (1995) argues that this cultural conflict is most noticeable when contrasting
the ideas of white liberal reformers with Black reformers. Whites, who may already be
fully participating in the culture of power, advocate for a system that does not arbitrarily
force standards upon their children. While Blacks, who have experienced
marginalization, “want to ensure that the school provides their children with discourse
patterns, interactional styles, and spoken and written language codes that will allow them
success in the larger society” (p.29). Similarly, Schneider, et al. (1997) points out that
several disparities among parents exist which may impede their ability to become actively
involved in their newly expanded role in the school marketplace. These disparities are
namely parent resources, involvement, cognitive abilities, and educational experiences.
This collection of work is best summarized by Schneider, Marschall, Teske, &
Roch (1998) in asserting that “whites and racial minority groups may want different
things from the schools, and given choice, greater segregation will result as parents of
different class and racial groups choose schools structured on different organizing
principles” (p.493). In their research they examinied how families of different social
classes and racial groups differ in their evaluation of four school characteristics:
1. the academic quality of the school,
2. the racial composition of its student body,
37
3. the values espoused by the school, and
4. the school disciplinary code.
Schneider et al., (1998) sought to discover the degree to which each of these
dimensions of school was a function of race and class. They hired a research laboratory
to interview 400 families representing the four school districts in the New York
metropolitan area. Families must have had a child attending school in any grade K-8
from either private or public school.
With regards to academic quality, Schneider et al., found that Black parents and
parents who graduated high school, but not college, ranked high test scores as important.
Next, parents that had reported attending college were eight percentage points less likely
to say that high test scores are important. It follows then that Blacks and parents with no
more than a high school diploma equate high academic quality with test scores more so
than middle and upper class parents with more education. As more minority and
historically marginalized groups have increased awareness around the requirements for
academic success, they will be demanding more of their schools or seeking other schools
through choice programs (Delpit, 1995).
The second finding was that white parents and parents with education levels of
some college or above were more likely to rank the school’s values as important than
families of racial minorities and lower education levels. On the third dimension,
discipline was valued much less by white parents and parents with higher education than
minority parents and parents with less education (Schneider, Marschall, Teske, & Roch,
1998). Table 2.1 shows how each group ranked the four different school attributes.
38
Table 2.1. School Attribute Rankings of 1,582 Parents in New York City and Suburbs
Black
Asian
Hispanic
H.S. Graduate
College
High Scores
1
2
2
1
4
Values
3
3
4
4
1
Discipline
2
1
1
2
3
Diversity
4
4
3
3
2
(Schneider, Marschall, Teske, & Roch, 1998)
Note: See Appendix A for complete table of the change in probability.
Charter Schools
As previously described, race, culture, and economics are strong factors to
consider when examining school choice. With regard to the use of charter schools as a
specific form of school choice, the data suggest a different trend. According to the
University of California Civil Rights Project, in their report Choice without Equity:
Charter School Segregation and the Need for Civil Rights Standards, several important
facts regarding race and charter schools are noted:

Latinos are disproportionately less likely to enroll in charter schools in five of the
six states with the largest shares of Latino students.

Nationally, white students are enrolled in charter schools at a rate lower than their
representation, but in the U.S. West, where traditional public schools are the most
racially diverse whites are over-enrolled in charter schools.

Charters attract a higher percentage of Black students than traditional public
schools, in part because they tend to be located in urban areas where more Black
students may tend to live (See Table 2.2).
39

In the industrial Midwest, more students enroll in charter schools compared to
other regions, and Midwestern charter programs display high concentrations of
Black students (The Civil Rights Project, 2010).
Table 2.2. Black Over-Representation in Charter Schools, top 15 MSAs, 2007-2008
Metropolitan Statistical Area (MSA)
Charter School
Black %
Public School
Black %
Black Charter
OverRepresentation
Cincinnati-Middletown, OH-KY-IN
78%
15%
520.0%
Kansas City, MO-KS
79%
17%
464.7%
Dayton, OH
74%
17%
435.3%
Boston-Cambridge, Quincy, MA-NH
32%
8%
400.0%
New York-Northern New Jersey-Long
Island, NY-NJ-PA
66%
20%
330.0%
Indianapolis-Carmel, IN
62%
19%
326.3%
Minneapolis-St. Paul-Bloomington, MNWI
37%
12%
308.3%
Chicago-Naperville-Joliet, IL-IN-WI
64%
22%
290.90%
Washington-Arlington-Alexandria, DCVA-MD-WV
88%
31%
283.9%
Detroit-Warren-Livonia, MI
72%
26%
276.9%
Cleveland-Elyria-Mentor, OH
70%
27%
259.3%
San Antonio, TX
17%
7%
242.9%
Los Angeles-Long Beach-Santa Ana,
CA
17%
7%
242.9%
Milwaukee-Waukesha-West Allis, WI
50%
23%
217.4%
Columbus, OH
42%
20%
210.0%
Source: Frankenberg, Siegel-Hawley, & Wang, 2010
An examination of charter school applicants to New York City charter schools
reveals a similar trend. Table 2.3 shows that charter school applicants were largely Black
and Hispanic, 63% and 29% respectively. Only a few percent were white, Asian, or
40
another race. Hoxby (2009) notes that all of the charter schools in New York City are
oversubscribed and use a lottery system for admission. There will be further discussion
of the results of this study in the next section covering Effects on Student Learning.
Table 2.3. The Race, and Gender of New York City Charter School Applicants and
Students in Traditional Public Schools from 2000 to 2006
Students' Race / Ethnicity
Black non-Hispanic
White non-Hispanic
Hispanic
Asian
Other race
All
Applicants to
charter
schools
Applicants
who were
lotteried-in
Applicants
who enrolled
in charter
schools
New York
City's
traditional
public schools
63%
4%
29%
3%
<1%
64%
4%
28%
3%
<1%
61%
4%
29%
4%
<1%
34%
15%
38%
12%
<1%
(Hoxby, The promise and performance of charter schools: Drivers of educational
improvement in the U.S.?, 2009)
Table 2.3 also shows that charter school students in New York were
disproportionately Black and Hispanic with only a few percent white, Asian, or of other
race. The table also shows that compared to all applicants, those students that were
lotteried-in are nearly identical to those lotteried-out, indicating that the selection of
enrollees was truly random. As a result, New York’s traditional public schools are far
less Black, and more white and Asian than charter schools in New York.
Mathematically, there are nearly four times more Asian and white students in New
York’s traditional public schools than in charter schools. From this data, it appears that
Black students and their families use choice options much more than others do. What the
data does not answer is why. This study addresses this question.
41
Years of research on social and economic isolation has linked segregation to
higher crime rates, unemployment, lower academic achievement, more aggressive
policing policies, and teenage childbearing (Bursik 1998; Lauen 2007; and Harding
2003). Additionally, inner-city and geographically isolated residents have decreased
access to information regarding jobs, education, and opportunities for mobility. Without
adequate social and financial resources, families in disadvantaged neighborhoods are less
likely to seek, apply for, and travel to schools of choice.
As a result, many of the reform efforts have focused on providing increased
school options to Black, Latino, and historically underserved students. School transfers
and choice are seen by some as one such mechanism for change. This proposed shift in
power is intended to empower parents to gather information and shop around for schools
that best satisfy their given preferences. Many, however, see school choice as a means of
bypassing integration efforts and are suspicious that choice will in fact improve the
quality of schools attended by mostly Black and Latino students. Critics point to postBrown v. Board of Education policies of the South. These “freedom of choice” plans
were a way for white families to avoid forced integration and continue to deny Blacks,
Hispanics, and Native Americans equality of educational opportunity (Farrell, Jr. &
Mathews, 1990; George & Farrell, Jr., 1990; Jones-Wilson, Arnez, & Asbury, 1992).
Effects of Choice on Student Learning
Research in the area of school choice has sought to examine the effects choice has
on the educational outcomes of students. More specifically, the research has sought to
42
answer the question: does school choice increase student achievement at both the
receiving schools and the schools that students are leaving? Low-income, minority
students in urban areas tend to be the focus of open enrollment and school choice efforts.
Advocates claim that these students, and others from racially and economically isolated
schools, are the ones that will see the biggest benefit from attending higher performing,
more integrated schools (Dillon, 2008).
Extending the market effects analogy to K-12 education, Ledwith (2010) points
specifically to research conducted by Dee (1998) and Hoxby (2000) where graduation
rates and student achievement increased subsequent to enacting open enrollment policies.
The following are the main findings of Hoxby’s analysis of New York City charter
schools:

On average, a student who attended a charter school for all of grades K-8 would close
about 86 percent of the achievement gap in math and 66 percent of the achievement
gap in English. A student who attended fewer grades would improve by a
commensurately smaller amount.

On average, his lotteried-out counterpart who stayed in the traditional public schools
for all of grades K-8 would stay on grade level but would not close the achievement
gap by much. However, the lotteried-out students' performance does improve and is
better than the norm in the U.S. where, as a rule, disadvantaged students fall further
behind as they age.
43

Compared to his lotteried-out counterparts, a student who attends a charter high
school has Regents examination scores that are about three points higher for each
year he spends in the charter school before taking the test.

A student who attends a charter high school is about seven percent more likely to earn
a Regents diploma by age twenty for each year he spends in that school. For instance,
a student who spent grades ten through twelve in charter high school would have
about a twenty-one percent higher probability of getting a Regents diploma (Hoxby &
Murarka, 2009, pp. IV-I).
An important fact of this study and similar studies that compared lotteried-in and
lotteried-out is that both cohorts of parents participated in the lottery and therefore it can
be concluded that they both have similar levels of parent involvement. This directly
refutes the claim that uses parent involvement as the deciding factor in student
achievement.
Effective evaluation of school choice programs suffers from many limitations.
Often times controlling for demographic differences and selection biases are hurdles.
However, changes in testing formats, other school improvement strategies, residential
decisions by parents, application procedures, prior student achievement, and availability
of transportation are additional factors that make measuring the effectiveness of
particular programs difficult and often inconclusive. The criteria used in the selection of
students for school choice programs provide a way of separating the effect of the program
from the effect of other characteristics. Furthermore, since most choice programs are
44
oversubscribed, those students that gain admission and those students that do not, make
natural treatment and control groups (Ballou, Goldring, & Liu, 2006, ).
Miron, Evergreen, & Urschel (2008), in a policy brief to examine and summarize
the evidence regarding school choice and its impact on student achievement, examine 87
school choice studies to measure the effect on student achievement. The authors based
their selection of these studies on the following seven criteria.
1. Presence of the technical report with a clear explanation of the procedures used
2. Presence of analysis and conclusions
3. Use of standardized test scores to measure student achievement
4. Use of comparison groups
5. Exclusion of duplicated studies
6. Exclusion of case studies or single school studies
7. Exclusion of studies on school choice outside the United States
Of the 87 studies examined, nine were related to inter-, intra-district, or magnet
school programs. For the purposes of this dissertation, I will only look at these nine
studies. The authors analyzed each study and gave ratings on the quality of the study,
and impact on student achievement. Positive values for impact indicate that the choice
program showed an increase in student achievement. A scale value of 2 indicated a
positive overall effect, 1, a slightly positive effect, 0 mixed impact, -1 slightly negative
overall impact, and -2 negative overall impact. Secondly, the studies were given a quality
of study score from 0 to 32 based on six different dimensions including research design,
duration of study, controls, measures of student performance, scope of study, and
completeness of technical report.
45
The results illustrated in Figure 2.1 show that only four had a “slightly positive”
effect on student achievement with none demonstrating a “very positive” effect.
Moreover, two of the nine programs showed a “slightly negative” or “very negative”
effect on student achievement (Miron, Evergreen, & Urschel, 2008).
Figure 2.1. Quality and Impact Ratings for Studies of Student Achievement in Magnet or
Interdistrict Choice Schools
(Miron, Evergreen, & Urschel, 2008)
Leading with the highest quality studies first, Study H, Does School Choice
Work? Effects on Student Integration and Achievement, (Betts, Rice, Zau, Tang, &
Koedel, 2006) compares lottery winners and losers in an urban intra-district choice
program. The San Diego Voluntary Ethnic Enrollment Program (VEEP), which started
after the court-order desegregation of schools in the 1970s, is another example of a
program that sought to increase the racial diversity at San Diego schools and increase
student achievement. Despite achieving the type of integration that open-enrollment
advocates argue for, there was little evidence to indicate students where achieving higher
degrees of academic success. Betts et al., examine the achievement of students after San
46
Diego implemented their VEEP program. The two groups were labeled lottery-winners
and lottery-losers. This is similar to what Hoxby describes as lotteried-in and lotteriedout. Betts and colleagues’ findings indicate that there was no significant difference in
math and reading achievement one, two, or three years after the lottery took place.
Surprisingly, they found that after the first year of transfer, there were temporary loses
among the lottery winners. (Betts, Rice, Zau, Tang, & Koedel, 2006).
This last discovery opens the door to exploring the disadvantages of non-routine
change of schools. When students transfer schools at times other than from elementary to
middle school, and middle school to high school, they are at risk of mitigating any
advantages they would otherwise enjoy by attending schools that follow a sequenced
course-taking pattern (Schneider, Swanson, & Riegle-Crumb, 1998). Increased
residential mobility and frequent school transfers is often associated with negative social
outcomes, higher drop-out rates, more serious discipline problems, and lower level of
educational attainment. Moreover, students who make non-routine school changes are
often misplaced in their new school’s curricular structure. Schneider, et al. describe this
as curriculum dislocation, which places them at a disadvantage to those students who
have not had non-routine school changes (Schneider, Swanson, & Riegle-Crumb, 1998).
Further research on this topic may explore how other factors of adolescence, family
influences, and residential moves affect student achievement during non-routine changes
of schools.
Study B, Magnet Schools and Student Achievement, (Ballou, Goldring, & Liu,
2006) compared lottery winners and losers and makes up for deficiencies in other studies
47
that do not control for individual student differences and changes in the demographic
composition of the schools. The seven variables controlled for were race, gender,
English proficiency, disability, poverty, and previous grade’s reading and math scores.
This study examined the effect of magnet schools in a mid-sized Southern city. The
district serves students in grades K-12 and is racially mixed with 40% White students and
48% Black. The focus of this study is on middle school students who had applied to one
or more of the district’s magnet programs through lottery.
The districts’ magnet program showed mixed results. There appeared to be a
positive impact on magnet students’ math scores, however, when prior levels of
achievement and demographics were controlled for, the results in math mirrored the
district as a whole. Additionally, Ballou et al., (2006) found that although there appeared
to be a positive magnet effect on math scores, the growth was not sustained over time as
would be expected with the additional benefit of attending a magnet school. In contrast,
Ballou et al., (2006) report that there is less evidence that the magnet school is having a
positive effect on reading scores. Similar to math, there was no evidence that students
would experience a cumulative academic gain by attending a magnet school for
consecutive years.
Another important factor uncovered by Ballou et al., (2006) is the role of attrition
when trying to compare lottery winners and losers. Their analysis of attrition showed an
interesting pattern. Lottery losers with lower test scores relative the lottery winners left
the district with greater frequency than lottery winners with similar levels of
achievement. It appeared that lottery winners, regardless of level of achievement were
48
confident that they found a satisfactory schooling option and were likely to stay in the
district. Following, if low test scores were the motivation for families to consider
different schooling options, they will continue looking if they fail to win a lottery. This
means that the control group of lottery losers will lose more of its weaker students that
the group of lottery winners, the treatment group. The implication is that measuring the
effectiveness of magnet schools becomes more difficult without controlling for attrition
and previous levels of achievement.
Study D, Student Achievement in Public Magnet, Public Comprehensive, and
Private City High Schools (Gamoran, 1996), and Study E, The Impact of Career Magnet
High Schools: Experimental and Qualitative (Heebner, 1995), both study magnet high
schools that have a career focus. Gamoran (1996) uses National Educational
Longitudinal Survey (NELS) test data from 1988 – 1990 to compare the gains in student
achievement from 8th to 10th grade for magnet schools, public comprehensive schools,
and private Catholic schools. In general, he found that magnet schools are more effective
than regular public schools at raising student achievement in science, reading, and social
studies, and when controlling for preexisting levels of student achievement non-secular
private schools did not offer any advantage. Consistent with social and economic
advantages, students at private Catholic schools scored higher in math, science, reading,
and social science.
The results of his study will favor more and support those who advocate for more
specialized programs in public schools. It also appeared that the magnet schools studied
served more disadvantaged students than did the regular comprehensive schools. This
49
trend may reflect the growing outcry for reform of inner-city schools and the resulting
efforts for school transformation. Additionally, as more districts expand their school
choice options, the growth in urban magnet schools may be an effort to attract students
from outside the boundaries, and retain those from within who may otherwise leave.
Heebner (1995) uses data from five career magnet schools in New York to
examine the outcomes for students who gained admission through lottery and those that
gained admission through a selection process. Because of the uniqueness of the program
and the means for selection of the participants, the results may not be generalizable to
other groups. However, lottery winners did experience higher math scores than those
attending regular public schools. In reading, students with average reading scores
demonstrated more growth than their counterparts in regular public schools (Heebner,
1995).
Study G, Evaluation of the Magnet Schools Assistance Program (Christensen,
Eaton, Garet, Miller, Hikawa, & DuBois, 2003), is a report that examines the progress
MSAP projects have made in meeting the goal of improving educational outcomes for
minority students and reducing minority student isolation. The report pointed out that
each school was required to establish goals in various domains that did not always
include language arts and math. Final goals were a set target level of proficiency at the
end of the grant period. While all of the schools had goals, only about half of the MSAP
schools had data that was analyzable. For example, schools had goals for educational
attainment, preparation for college, or alternative assessments. Nonetheless, Figure 2.2
shows the percentages of schools that met at least half of their final goals.
50
Figure 2.2. Percentage of Schools that Meet Half or More of Their Final Goals
(Christensen, Eaton, Garet, Miller, Hikawa, & DuBois, 2003)
Concerning the stated purposes of MSAP, 57% of the grant funded schools
succeeded in desegregation efforts when adjusting demographics to the current district
trends. Conversely, 43% of the schools were not successful in eliminating or reducing
minority group isolation (Christensen, Eaton, Garet, Miller, Hikawa, & DuBois, 2003).
Next, MSAP supported schools were most successful during their first year of
implementation in meeting their goals, but over longer periods of time the gains were not
fully sustained. When addressing the third and fourth purposes of innovation, improved
methods, and systemic reform, MSAP supported schools had adopted reform models at
greater frequencies than non-magnet schools. Additionally, survey data indicated tat
MSAP schools had a more positive school climate and teachers reported a greater
emphasis on higher level thinking skills. However, the case studies highlighted tensions
that sometimes existed when trying to implement systemic reforms and innovative
instructional practices (Christensen, Eaton, Garet, Miller, Hikawa, & DuBois, 2003).
51
Overall, the results showed that the most relevant school factor improving student
achievement was school climate. Christensen et al., report that schools with more
positive program features outperformed comparison schools. However, most MSAP
schools had adopted innovative themes and had somewhat more positive climates and
professional learning communities than did comparable schools.
In addition to a comprehensive examination of varied school choice programs, the
work of Miron et al., demonstrates that well conceived school choice initiatives that are
effectively evaluated and studies have a more positive impact on student achievement.
Four of the five studies that received a quality of study score of 19 or higher also showed
at least a slightly positive effect on student achievement. Conversely, those studies that
received a quality of study score of 17 or lower either had no effect or a negative effect on
student achievement.
Study C, The Effects of Academic Career magnet Education on High Schools and
Their Graduates, (Crain, et al., 1999), studied career magnet programs in large lowincome cities with high populations of African American or Hispanic students. Their
study consisted of two parts. First, a quantitative analysis of 9,176 student data files
compared test performance, attendance, graduation rates, and dropout rates of lottery
winners and losers to career magnet programs. What their analysis uncovered was that
many career magnet programs have lower graduation rates and higher dropout rates than
comprehensive high schools. Higher academic standards and a tendency to push weaker
students out seemed to be a cause. In addition, admission to these programs is not solely
by lottery; up to half of the students were handpicked. Subsequently, students would
52
have a greater chance of graduating had they lost the lottery. The analysis of student data
files revealed that students in career magnet programs did not have significantly different
math and reading scores, nor do they take advanced graduation tests at rates different
from their counterparts in comprehensive high schools.
Second, 110 high school graduate lottery winners and losers were surveyed and
interviewed. In addition, the researchers selected 30 participants from the survey
respondents for four-hour interviews. Their analysis showed that graduates from career
magnets were more likely to have chosen a major within the first two years of college
attendance and have earned more college credits. The additional positive effects related
more to the psychological and social benefits small learning communities. Career
magnet graduates reported they smoked less, had fewer fights, drank alcohol much less
often, and became pregnant or caused a pregnancy less often (Crain, et al., 1999). This
last observation supports the position of the open-enrollment proponents who subscribe
to Ogbu’s theory of cultural ecology. The magnet schools appear to better help students
through their identity development process and adolescence. School attachment,
perceived teacher support, parental control, and minimal exposure to community violence
are linked to greater student outcomes and lower levels of delinquency (Frey, Ruchkin,
Martin, & Schwab-Stone, 2009).
Study A, (Beaudin, 2003) was a report to the Connecticut Department of
Education on interdistrict magnet and magnet schools in the state. It compared the scores
of students in magnet schools with the statewide averages over a two-year period. The
results were mixed and showed both positive and negative effects on the two different
53
standardized tests. Additionally, the study’s lack of controls for demographics or other
reform efforts that individual schools were undertaking accounted for the low rating in
quality of study (Beaudin, 2003).
During the two years studied, 2000 and 2001, students enrolled in magnet schools
in grades 4, 6, and 8 in Connecticut scored below the state average and below students
from high socioeconomic backgrounds. The only group that magnet school students
performed better than are students from high-poverty schools. In reading the results are
similar. Magnet school students in grades 4, 6, and 8 scored below the state average and
were outperformed by students from schools that were predominately white and had low
numbers of students in poverty. On the CMT Writing Test, it appears that 8th grade
magnet school students are better prepared in writing and outperformed the state average
by 4 percentage points in 2001. However, those same students performed 20 percentage
points below students in low-poverty schools. Grade configurations for Connecticut
schools include K-8th grade and K-6th grade. In examining the data, 6th and 8th grade
students are included in both sets, but are not disaggregated any further. Figures 2.3, 2.4,
and 2.5 show the comparisons of each group on the CMT Mathematics, Reading, and
Writing Tests administered in 2000 and 2001.
54
Figure 2.3. Comparisons of the 4th Grade Students Performing at or Above Connecticut
Goal on CMT Writing Test
(Beaudin, 2003)
Figure 2.4. Comparisons of the 6th Grade Students Performing at or Above Connecticut
Goal on CMT Writing Test
(Beaudin, 2003)
Figure 2.5. Comparisons of the 8th Grade Students Performing at or Above Connecticut
Goal on CMT Writing Test
(Beaudin, 2003)
The overall conclusions from the Connecticut study of the impact of elementary
and middle magnet schools on academic performance is mixed. Without controlling for
55
demographics it is unclear if high poverty and students of color are overly enrolled in
Connecticut’s magnet schools. If they are in fact attending magnet schools at high rates,
then it can be concluded that magnet schools are increasing student achievement and
reducing the gap in performance for students who attend them.
To date, studies on school choice have primarily focused on the family as the
agent empowered with choice. A growing area of research is focusing on the school as
the choice agents. When certain market conditions exist, school leaders use various tools
to seek and retain students that will enhance their test scores and reputation (Jennings
2010; Lauen 2007). Further research may examine how school leaders use overt and
covert means to influence enrollment patterns. Marketing, interviews, test scores, family
and child demographics, and the social network that exists among principals are among
some of the ways schools may weed out those students that require higher levels of
service including those that are English learners, have special needs, or have behavior
problems (Jennings 2010; Lauen 2007).
Skimming refers to the practice of enrolling high ability students and leaving out
lower achievers and students with disabilities. Although lottery-based studies do not
support that charter schools in fact do intentionally “skim” the top students from regular
public schools, with regards to race and economic status, there is substantial evidence to
suggest that white parents and parents with higher socioeconomic status exercise other
school choice options at higher rates than do Black, Latino, and economically
disadvantage families (Fisk and Ladd 2000; Hsieh & Urquiola, 2006; Teske and
Schneider 2001). Zimmer et al., (2009b) studied locations Chicago, Denver, Milwaukee,
56
Ohio, Philadelphia San Diego, and Texas examining student level data for stratification.
Their findings did not show that charter schools systematically skim high achieving
students from regular public schools. This may lead to the conclusion that open
enrollment polices do nothing to close the achievement gap among white students and
students of color.
Impact of Choice on Non-Choice Schools
Another undeniable aspect of the effects of school choice is the impact it has on
the schools that are the net-losers of such policies. What is more compelling is the
influence of culture on school choice decisions. While some will overemphasize the
extent to which low-income families will disengage from the process, “social norms and
ethnic identity constrain[s] the range of school choices that are credible in their eyes”
(Wells, 1996, p. 25). In addition, the lack of adults willing or capable of advocating for
those students will ultimately relegate them to the inferior school even when choice exists
(Ridenour, Lasley, II, & Bainbridge, 2001). Ledwith (2010) goes on to acknowledge the
points made by opponents of school choice. She points to the work of Fiske and Ladd
(2000), who argue that families without adequate financial means are not able to take
advantage of choice options. Further, she states that students and families “will not be in
a position to choose good schools and will become trapped in ‘hollowed-out’ public
schools” (p. 245). Moreover, she points to the “skimming” that can occur of white and
non-Hispanic students from traditional public schools. These “skimming” practices are
usually attributed to charter schools in which selection, enrollment, and retention
57
practices attempt to include only students with greater potential for academic
achievement.
Continued Debate on School Choice
Does school choice matter in the achievement of students and whose parents
chose to exercise it? This is the very important question that policy makers wish to
answer.
An argument used in support of school choice is that the competition it generates
will significantly raise the quality of public schools. The market analogy to consider is if
you could only get your auto serviced by one mechanic (your child can only go to one
school). Granting such a monopoly provision would cause most to expect that the quality
of service provided by this one mechanic at a given price would be far less than if the
consumer had many auto mechanics to chose from to service their auto.
Supporters go on to argue that school choice will motivate public schools to be
more responsive to parent and student demand and promote the pedagogical changes
necessary to improve student outcomes (Tooley 1993; Whitty & Edwards 1998).
Additionally, competition through open enrollment will create incentives for traditional
public schools to embrace reform. An Indiana study, Study of the Effectiveness and
Efficiency of Charter Schools in Indiana, conducted by the Center for Evaluation and
Education Policy, states, “it appears that charter schools have played some role, through
market competition, in motivating school[s] to make positive structural and
programmatic changes” (Akey, et al., 2008, p. 105). The study, however, did not note
58
any significant improvements in student achievement, but it illustrates that when schools
and districts are faced with potential declining enrollment because of choice options,
choice can be a catalyst for organizational change. The report quotes one principal as
saying:
“Some really great ideas are emerging. Ultimately, you have this
innovative culture. People are always thinking about how to differentiate
ourselves and meet the needs of our children. We’re seeing significant
changes from a climate where everything has to be the same. The others
run with it and say ‘we can do it too.’ There are different treatments for
different needs. That’s where I see different ways to approach this work”
(Akey, et al., 2008, pp. 105-106).
The data for the Indiana study came from three major sources. First, CEEP
obtained the qualitative data related to student achievement, attendance, and graduation
rates from the Indiana Department of Education and individual school accountability
reports. Qualitative data was obtained through interviews with 30 community
stakeholders. They included superintendents, IDOE staff, leaders from professional
organizations, local university staff, and staff from the city mayor’s office. The CEEP
collected additional data from documents related to charter school contracts and
procedural policies.
The transformation of local public schools to become market driven institutions
requires the acceptance of certain assumptions related to both schools and the teachers
59
within them. First, these schools must not already be market-driven. Second, school
systems would now offer educational options that matched the demands of parents and
students. Third, limited mobility for families in poverty and private schools being cost
prohibitive strengthens the monopoly of the local public school. Lastly teachers would
embrace the accompanying changes and make corresponding changes to their
instructional practices. This last point assumes that the teachers have not already adopted
the changes in instructional practices. In a system that has operated as a monopoly for
decades, the challenge becomes not only changing the system, but also changing the
people within it. Gaining market share in schooling equates to increased enrollment, it
offers prestige to those teaching there, and it provides power and influence in the system
(Smrekar & Goldring, 1999). The prestige that comes with the knowledge that your
school is preferred to others, offers greater empowerment to teachers and may further
increase teachers perceived efficacy. Furthermore, this empowerment has a tremendous
impact on satisfaction when it is within an organization that supports the individual by
providing the vision, training, and resources necessary (Bogler & Nir, 2012; Fullan
2008). Bogler & Nir (2012) go on to report that the intrinsic satisfaction that comes from
empowerment is the self-efficacy one experiences when their psychological and social
needs are met. Steffens and Cookson, 2002, however, make the claim that the market
metaphor does not apply to public education.
“Public education is a social commitment that transcends individual
interest and corporate gain…[A]s a human service, education is grounded
in a belief in human dignity that transcends the values and behaviors
60
associated with markets. It means public education cannot be squeezed to
fit the market model and still meet the needs of a just society” (p.5).
Similar to public education, health care is another commodity that is provided in market
systems.
Beyond improving academic achievement and the other previously described
outcomes, proponents of school choice contend that open enrollment will have a positive
effect on reducing racial and economic segregation in public schools (Dillon, 2008). The
UCLA Civil Rights Project reports that 40% of Black students in America attend a school
that is at least 90% Black. That number is up from 1988 figures that showed that onethird of Blacks attended similarly comprised schools. The report goes on to confirm that
Black and Latino children were more segregated in 2009 than at the time of Martin
Luther King Jr.’s death. This new trend of re-segregation was brought on by a disturbing
housing trend that drastically reduced the amount of affordable housing combined with
stagnation and slight decline in average wages for American workers has created new
concentrations of poverty in America’s cities and schools. With greater attention given to
equity issues related to choice, the need to study school enrollment practices has caused
The University of California, Civil Rights Project, The Journal of Negro Education, The
Journal of School Choice, The Brookings Institute and others to examine whether or not
charter schools provide choice without equity. Nearly two decades of study around
charter schools led to the following three outcomes:
1. Most states provide incentives for charter schools to serve low-income and
minority students,
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2. The people seeking to run charter schools were predominately dedicated to
improving school options for the most disadvantaged students,
3. An increasing number of foundations provide targeted financial assistance to
charter schools serving poor minority students in urban districts that have
been slow to adopt reforms (Hill & Lake 2010, Nathan 1996, Hoxby, 2009).
As previously described, the California Open Enrollment Act was intended to
improve student achievement and enhance parental choice in education by providing
additional options to pupils to enroll in public schools throughout the state without regard
to the residence of their parents. Dillon (2008) states that due to lack of resources,
political barriers, and underfunded policies, achievement gains have been inconsistent
and can actually exacerbate segregation and increase the achievement gap among Black
and Latino students, and white and Asian students. This happens when school choice
plans are poorly designed and implemented, and do not target those students that could
benefit most from increasing their access to higher performing schools (2008, p.3).
Conclusion
In attempting to understand the impact of school choice on student achievement,
we have yet to collectively define what student achievement means, what factors
contribute to it, and how it can be measured. The measures currently in place, IQ tests,
standardized test scores, graduation rates, retention and drop-out rates, and college
acceptance may be too simplistic to measure complex human behaviors (Cookson, 1994).
Additionally, some consider job skill preparation, civic engagement, an appreciation of
62
the arts, character development, physical development, and the appreciation of lifelong
learning as fundamental measures of student achievement (Goodman & Zimerman,
2000).
Cookson (1994) describes how statistical control remains a fundamental issue in
measuring and interpreting data. For example, although school governance has shown to
have positive effects on student achievement (Goodman & Zimerman, 2000), so has
student family backgrounds, socioeconomics, community forces, and the social,
psychological, or religious forces that influence parents to sacrifice for the sake of the
child’s education (Cookson, 1994; Delpit, 1995; Lauen, 2007). As described earlier,
among those studies that did have suitable controls, some found positive effects of school
choice, some found negative effects, and others found no significant effect at all. The
researched survey here provides no conclusive evidence that competition through school
choice provided any substantial benefit to those students choosing choice schools or those
that remained. It highlights the clear need for a deeper analysis and possibly case study
research within states or even school districts specifically following cohorts of students
that remain within their same school district. The absence of any definitive conclusion
on overall student achievement does not rule out the other possible benefits such as other
improved outcomes for active choosers, a better match between families and schools,
opportunities to participate in unique programs, and the benefits provided by social
cohesion (Levin, 1998; Levin, 2002).
The mixed results of choice on academic achievement indicate that the issue of
school choice is complex. An explanation may be found by further examining more
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demographic information including suburban vs. urban communities, the number of
schools families have to choose from, geographic features, availability of public transit,
and race and class tensions.
Only recently have school choice policies been implemented on a scale large
enough to allow for meaningful study. Although the base of knowledge is growing, the
results are inconclusive and can neither support nor refute claims that school choice plans
improve the educational outcomes of those students that leave or remain at their
neighborhood schools. The absence of any strong evidence confirming that choice
polices do improve schools, does not rule out any possible gains in equity, social
cohesion, or improved outcomes for those who actively choose (Arsen & Ni, 2008).
Researchers have underscored the need for policy makers and school officials to
thoroughly understand the dynamics of school choice by making the argument that
successful policies cannot be implemented without a thorough theoretical understanding
of the traditional school system and the implications to families that choose to go outside
that system (Koedel, Betts, Rice, & Zau, 2009).
64
Chapter 3
Methodology
Introduction
The following chapter reviews the research design for this study. It presents a
rationale for the use of a regression analysis to analyze the demographic data of both
participants and non-participants in open enrollment, and the use of Pearson correlation
coefficients to analyze the results of parent surveys. Both are integral components in
understanding the phenomenon of parents choosing to enroll their child in a school other
than their home school during open enrollment. This chapter reviews the data collection
procedures, describes the study setting, population, and research sample. Chapter 3 also
reexamines the research questions and explains how the quantitative data was collected
and analyzed. Finally, I discuss the roll of the researcher and the measures used to
protect the study participants.
Research Questions
1. What variables (available in standard data files) exert a significant impact on
the choice to participate in open enrollment, both in terms of them having a
non-zero influence and the magnitude of this influence?
2. Through correlation and mean comparison, what factors are significant in
relation to why families choose to participate in open enrollment and leave
their home/neighborhood school?
65
3. To what degree do current school policies influence open enrollment and
school choice decisions?
Population and Setting
The setting for this study is a large urban and suburban comprehensive pre-K-12
school district in northern California. For the purposes of this study, the district will be
known as Golden Unified School District, GUSD, to conceal and protect the identities of
the study participants. GUSD serves approximately 47,000 students in grades pre-K
through 12. Figures 3.1, 3.2, 3.3, and 3.4 show the demographic breakdown of the
student body and academic progress of GUSD over time.
Figure 3.1. District Racial and Ethnic Distribution 2010 -2011 School Year
Source: Ed-Data, 2012
66
Figure 3.2. District Students Percent at or Above Proficient – Math 2008 - 2012
Source: California Department of Education, 2012
Figure 3.3. District Students Percent at or Above Proficient - English-Language Arts
2008 - 2012
Source: California Department of Education, 2012
67
GUSD is presently in program improvement status. School districts identified as
in program improvement status have not met adequate yearly progress in ELA or Math
for all numerically significant subgroups for two consecutive years. Not until 2010 did
GUSD’s performance fall below the state’s targets. The low initial targets were
established with the intent that all students will be proficient by the year 2014. The
California Department of Education reports that there are 486 school districts or LEAs
Local Education agencies, in program improvement status. That number represents 49%
of the 994 districts in the state of California. Schools or school districts can exit PI status
when they make adequate yearly progress for two consecutive years.
Data
I collected quantitative descriptive data on 42,228 students from GUSD for the
2012 – 2013 academic school year. After receiving university and district approval to
conduct this research, I met with the GUSD’s research and evaluation department and
was provided with an electronic database containing descriptive data described below on
every student minus names. Student ID numbers remained in the file so that I could
perform a random sampling for the survey data analysis. In addition to indicating which
students and are currently participating in open enrollment, the data also included the
following:
a. Neighborhood school – the school the student is assigned to based on home
address;
b. Chosen school – the school the student is assigned to based on request;
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c. Age of child – current age at time of study;
d. Grade of child – grade during 2012 – 2013 school year;
e. Home language – language other than English spoken at home;
f. Primary language – primary language (Table 3.1) the student communicates in;
g. Ethnicity (Table 3.2);
h. Gender;
i. English proficiency (Table 3.3);
j. Socio-economic status – low or not low, families that qualify for free or reduced
lunch or have a parent that did not graduate high school meet the district’s criteria
for Low SES.
The following Tables referenced above further illustrate the ethnic and linguistic
diversity of GUSD. Among all students in grades 9 -12, thirty-four languages are spoken
with a degree of fluency ranging from limited English proficiency to fluent. Table 3.4
shows the total number and percent of students at each overall performance level.
Table 3.1. Primary Languages of Students Within GUSD
Arabic
Farsi
Ilocano
Polish
Armenian
Filipino
Indonesian
Punjabi
Assyrian
French
Italian
Romanian
Burmese
Greek
Japanese
Russian
Cantonese
Hindi
Korean
Samoan
Dutch
Hmong
Mandarin
Serbo-Croatian
English
Hungarian
Marathi
Spanish
Source: GUSD data files
Thai
Tigrinya
Turkish
Ukrainian
Urdu
Vietnamese
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Table 3.2. Ethnic and Racial Categories of Students Within GUSD
American Indian / Alaskan Native
Filipino
Asian-Chinese
Hispanic or Latino
Asian-Korean
Pacific Islander-Other
Asian-other Asian
Pacific Islander-Samoan
Asian-Vietnamese
White
Black / African American
Source: GUSD data files
Table 3.3. Student English Proficiency Designations of Students Within GUSD
English Only
Initially fluent English proficiency (at time of first testing)
Reclassified fluent English proficiency
Beginning
Early Intermediate
Intermediate
Early Advanced
Advanced
Source: GUSD data files
The study population included students and families living within the GUSD’s
boundaries, or intra-district transfers. This study does not examine inter-district transfers,
or transfers of students coming from outside of the district’s boundaries. Additionally,
students enrolled in any of the district’s special education centers, alternative schools,
charter schools, or home school were omitted from the study. In my analysis, the
excluded category of race/ethnicity is White, with the exception of students that identify
as White and speak a language other than English at home. Note that the race/ethnicity
category Other Asian is included in this school district’s standard student data to account
for any other Asian ethnicity not specifically listed on the questionnaire. The home
language is other than English category applies to all student regardless of their
70
race/ethnicity and includes students that identify as White, and speak a language other
than English at home, including Albanian, Arabic, Armenia, Assyrian, Dutch, Farsi,
French, German, Greek, Hebrew, Hindi, Hungarian, Italian, Polish, Portuguese, Romania,
Russian, Serbo-Croatian, Turkish, and Ukrainian.
The district’s open enrollment policy states that parents of students may apply to
enroll their child in any grade appropriate school and are willing to provide their own
transportation. A computerized random selection determined which students are
accepted for their choice school. Further, the district stipulates that you must participate
in open enrollment if:

You would like your student to attend a school other than your current school of
residence.

You would like your student who currently attends a K-6 or K-8 school to attend
6th grade at a middle school. (all district middle schools are grades 6-8)

You would like your child to attend a middle school other than their resident K-8
school for 6th, 7th, or 8th grade.

Your student qualifies for the High Achiever Program and you want him/her to
attend a middle school other their resident school.

You would like your child to attend any of the districts six elementary schools,
one K-8 school, one 6-8 middle school, or one 9-12 high school that enroll
exclusively through open enrollment.
71

Your child was overloaded to the school they currently attend, you have not filled
out an intradistrict transfer, and you would like for him/her to remain at the
overloaded site.
Quantitative Methods Used in this Study
I used a quantitative approach in analyzing two sets of data. Within the
frameworks of rational choice theory and social cognitive theory, I examined the actual
behavior and perceptions of parents regarding open enrollment and school choice
decisions. This quantitative approach purposefully used two forms of analyses. First, I
used logistic regression analyses of socio-economic characteristics available in
commonly collected data by the school district to determine which characteristics
correlate with a parent’s likelihood of leaving their home school. This analysis will show
the likelihood increase of leaving a school if an included explanatory variable changes by
one unit while holding all other explanatory variables constant. For dummy explanatory
variables this is a change from not having the measured characteristic to having it. The
second form of quantitative analyses used in this dissertation study is the generation of
Pearson correlation coefficients and a measure of means to measure how well the
variables are related, and to uncover why students and families are participating in open
enrollment and exiting their home/neighborhood schools. Next, I specifically describe
how both the logistic based and survey based research was undertaken.
72
Logistic regression method.
The logistic regression model or logit model used in this study allows me to
predict which independent variables are most likely to be correlated with the family’s
likelihood to participate in open enrollment, the dependent variable. The dependent
variable measures a family’s participation in open enrollment (OE). OE is equal to one if
the student is not attending their neighborhood school as a result of parent request, and
zero if they are attending their neighborhood school. Using the data file obtained from
GUSD, I compared the student’s neighborhood school with the school of actual
attendance to establish the dichotomous variable of zero or one. This study uses multiple
regression because there are more than one independent or predictor variable that is
expected to influence the choice of leaving a neighborhood school. Regression analysis
is appropriate because it allows for the calculation of the influence of one explanatory
variable holding all other included explanatory variables constant.
Dummy variables were created to represent differences in a student’s gender,
home language, race and ethnicity, socio-economic status, and if the overall academic
performance of the student’s home school (as measured by API1) was lower than that of
the chosen school for the 2012-2013 school year. This logistic regression of the
The API is a single number, ranging from a low of 200 to a high of 1000, which reflects a school’s, an
LEA’s, or a student group’s performance level, based on the results of statewide testing. Its purpose is to
measure the academic performance and growth of schools. The API was established by the PSAA, a
landmark state law passed in 1999 that created a new academic accountability system for kindergarten
through grade twelve public education in California.
1
The API is calculated by converting a student’s performance on statewide assessments across multiple
content areas into points on the API scale. These points are then averaged across all students and all tests.
The result is the API. An API is calculated for schools, LEAs, and for each student group with 11 or more
valid scores at a school or an LEA.
73
dichotomous dependent variable, participation in open enrollment, yielded regression
coefficients that indicate how a one-unit change in one of these predictors, holding other
predictors constant, is expected to change the likelihood of a family’s participation in
open enrollment. Throughout this study, I only discuss the influence of an explanatory
variable if the confidence is greater than 90 percent that is exerts a non-zero influence on
participation in open enrollment.
Logistic regression analysis also provided a way to assess how well the predictor
variables, overall, predict the likelihood of participation in open enrollment (Pallant,
2007). Similar to the t-test in linear regression, the Wald statistic used in binominal
regression is used to assess the statistical significance of coefficients. Additionally, I
interpreted the logit coefficient in the form of an “odds ratio.” Using this, I can predict
by how much each variable increases the likelihood that a family will participate in open
enrollment (Pampel, 2000).
The logistic regression methodology relied on demographic and descriptive data
of the 42,228 students enrolled in grades K-12 to determine which characteristics
increased the likelihood that a family would participate in open enrollment. The area of
human behavior, specifically related to the theoretical frameworks germane to this study,
is inherently complex and therefore difficult to make accurate predictions. However,
through a multiple regression I am able to identify those variables which together provide
an estimation of a family’s/student’s likelihood of participating in open enrollment
(Brace, Snelgar, & Kemp, 2012). Most importantly for the policy implications I am
looking to draw, I can separate out the influence of one specific explanatory variable
74
holding the other constant. For instance, I can state with a specific degree of statistical
confidence that if two students are identical in age, grade, home language, ethnicity,
gender, and English proficiency, what effect low socio-economic status (or any of the
other possible explanatory variables just mentioned) has on the decision of their parents
for them to leave their neighborhood school.
Survey-based method.
The second analysis is a Pearson correlation and comparison of means coming
from a second data source. It uses the results from parent surveys to analyze the nine
variables described in Figure 3.5. Surveys were mailed to the study participants selected
through the stratified random sampling procedures described earlier. The survey
instrument used in this study was created by the researcher based on themes and issues
uncovered during the review of relevant literature. The purpose of these two methods
used together is more useful in fully answering my research questions.
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Table 3.4. Descriptions of Variables in Survey
Variable
Description
Participation in
Open enrollment
Participation is yes if the child is enrolled in a school other than
the child's school of residence, also referred to home school or
neighborhood school. The enrollment was a result of parents'
requesting transfer through open enrollment and has not been done
through involuntary transfer or other means.
School Safety
Measures the perception that the choice school is safer and freer
from violence than the neighborhood school
Principal
leadership
Measures the perception that the leadership at the choice school is
more effective and desirable than the principal leadership at the
neighborhood school
School programs
Measures the degree to which the choice school has more
preferred academic and/or extracurricular programs than the
neighborhood
Measures the degree to which the choice was based on the greater
perceived or real academic performance of the choice school over
the neighborhood school
School's
academic
performance
Racial and ethnic
diversity of
school
Measures the degree to which racial and ethnic diversity was a
factor in choice.
Distance and or
transportation
Measures the degree to which distance and/or transportation were
factors in choice.
Peer group
influences
Measures the degree to which parents believe their child will have
an advantage by sending him or her to a school with higher
achieving students.
Note: These variables relate to both participants and non-participants in open enrollment.
Parents were asked to comment on their neighborhood school, choice school, or both.
The final and preliminary survey was piloted on six parents of elementary aged
students who currently participate in open enrollment. These parents are known
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personally to me and based on their knowledge of my study they were asked to pilot the
survey. They were asked to reflect on time to complete survey, clarity of questions and
wording, think-time for each question, redundancies, and any irritation or embarrassment
any questions caused (Iarossi, 2006). The original survey included 41 questions. The
test participants unanimously said it was too long and that several questions seemed to
ask the same thing over again. When it was explained that the goal was to ask two
similar questions in order to increase reliability, the test group agreed that the questions
related specifically to school safety were unambiguous and only needed a few questions.
Regarding clarity, questions related to principal leadership were described as “confusing”
or “jargony.” The last relevant observation of the pilot group was that the pace of their
response slowed when they reached the question asking if race diversity influenced their
decision to stay at or leave their home school. During the debrief, I probed further on this
observation and one respondent said,
“I wasn’t sure if it was a good thing or a bad thing that I thought about
race. It wasn’t my first consideration, but subconsciously I guess I was
wondering about it (Anonymous, 2013).”
As a result of the feedback from the pilot group, the survey was shortened to the
present 18 questions and terms used specifically in education were replaced with more
common terms.
77
Sampling.
I used a proportional stratified random sampling of students from three selected
high schools within the GUSD. The selection of these three schools was based on the
results of the first logistic regression analysis and enrollment patterns for the 2012-2013
school year. When controlling for all other variables, parents at the three chosen high
schools were likely to exercise choice. Chapter 4 will provide greater detail of the
statistical analysis, however, the graph in Figure 3.4 shows the total numbers of 1)
students that left each school, 2) students that chose the school in lieu of their
neighborhood school, and 3) the total number of students that attend because it is their
neighborhood school.
Figure 3.4. Enrollment Patterns at Study High Schools
The students were divided into two groups; leavers and stayers. Within each
group of leavers and stayers, they were further divided by grade, 9-12. Ten percent from
each of the 8 groups were randomly selected resulting in 487 participants. This method
allowed for each to have an equal chance of selection and for each group to be equally
represented in the study. The goal was to select a large enough representative sample so
78
that the results could be generalized back to the population and school district. This large
sample size was selected in order to minimize the chance of sampling error. Although
specific subgroup data is not studied, chapter five will outline future areas of study. The
surveys sent to the 490 randomly selected parents and families uncovered those, social,
economic, and perceptual factors that have led parents to exercise school choice other
than their neighborhood school. Further, it guided me in understanding parents’ decision
making and the degree of rationality in making schooling choices.
The sample consisted of 490 participants; approximately 54% were female (n =
263), while the rest were male (n = 227). Chapter 4 will provide further descriptive
characteristics of the sample. Correlation coefficients were computed among the nine
school choice variables. The Pearson correlation coefficient index ranges in value from
-1 to +1. A p value of less and .10 (or a 90 percent confidence of a non-zero influence)
was required for significance.
Returned surveys were assigned the dummy variable of one if the respondent was
among the group who participates in open enrollment, or a zero if the respondent did not
participate. Responses the Likert scale questions (1-14 on the survey) were recorded in
SPSS to find the mean and standard deviation values for the independent variables. See
Appendices B and C for complete surveys that were sent to both the families choosing to
exercise choice and leave their neighborhood school, and those families choosing to stay
at their neighborhood school.
All forms of statistical analysis were conducted using Statistical Package for the
Social Sciences (SPSS). This is a widely used tool for analyzing social science data. The
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final level of analysis is the presentation of descriptive data comparing enrollment rates
and trends of the three selected high schools and comparisons of racial and ethnic
characteristics of the sites compared to state and GUSD averages.
The goal is for the obtained results to be generalized across similar population.
The combination of these two methodologies provides for a richer collection of variables
that are necessary for policy recommendations and allows for generalization of the results
across other similar sized and comprised schools and LEAs. These two analyses will be
used together to improve the overall strength of the study (Creswell, 2009).
Role of the Researcher
I am the primary data collector in this study. I am a California high school
administrator and previous middle school principal within the school district study site. It
should be noted that I had no physical interaction with the participants, only with school
district personnel for the purpose of collecting data and delivering surveys to be mailed to
randomly selected participants.
Protection of Participants
All study related materials, surveys, consent forms, and related questions received
University, participating school district, and dissertation committee approval prior to
implementation. As a means of protecting participant confidentiality, respondents are not
identified by name. I, assisted by the school district’s Department of Assessment,
Evaluation and planning, was given access to student / parent information, and assisted
80
with distribution of survey instruments. I did not have access to or know the individual
identities of the study participants. The names of the schools and school district were
changed and pseudonyms’ for each school were used throughout this study.
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Chapter 4
Data Analysis and Findings
Introduction
The purpose of this empirical portion of my study is to uncover the factors leading
to the phenomenon of parents leaving their neighborhood schools and use that
information to inform open enrollment and school improvement policies. Additionally,
this empirical examination seeks to uncover the extent to which schools have the capacity
to change or influence enrollment patterns of their schools; and to what degree do current
school policies influence open enrollment and school choice decisions of parents. Within
the frameworks of rational choice theory (RCT) and social cognitive theory (SCT), I
investigate the following questions:
1. Through logistic regression analysis, what variables (available in this school
district’s standard data files) exert a significant impact on the choice to participate
in open enrollment, both in terms of them having a non-zero influence and the
magnitude of this influence?
2. Through correlation and mean comparison, what factors (available through a selfadministered survey of parents in this school district) are significant in relation to
why families choose to participate in open enrollment and leave their
home/neighborhood school?
3. Through analysis of written survey responses, to what degree do current school
policies influence open enrollment and school choice decisions?
82
School District Data
Descriptive characteristics.
In order to determine which of the demographic variables influence the likelihood
of participation in open enrollment, I first used the standard data collected for every
student in this district to perform several analyses. The goal in all of these analyses was
gain a better understanding of the influence of a change in an expected causal variable to
whether a parent chose to move their child from their neighborhood school to a different
school within the same school district.
Two different types of this analysis are presented next. First, descriptive statistics
of demographic and socio-economic characteristics of all students, and dividing all into
participants in open enrollment and non-participants, are presented. I then offer an
independent samples t-test of whether the difference in the mean value of these
characteristics is statistically significant between the two groups. Second, I present the
results of the binary logistic regression using participation in open enrolment set equal to
one as the dependent variable, and the demographic and socio-economic characteristics
as explanatory variables.
The sample size of 12,352 students represents all students in grades 9-12 and
excludes those students enrolled in continuation school or any of GUSD special
education centers. Table 4.1 offers the mean and standard deviation for the dependent
variable and each explanatory variable for the entire population, and for both participants
and non-participants in open enrollment. The table includes the minimum value,
maximum value, mean, and standard deviation.
83
An independent-samples t test was conducted to evaluate the hypothesis that
students with certain demographic characteristics exercise participation in open
enrollment to a greater degree than students that do not possess those characteristics.
This test evaluates the difference between the means of two independent groups:
participants in open enrollment and non-participants. The t test evaluates whether the
mean value of the test variables for one group, participants in open enrollment, differs
significantly from the mean value of the test variables for the second group, nonparticipants in open enrollment (Green & Salkind, 2008).
Table 4.1 reports the results of the difference in means test. It indicates, using an
asterisk, that eight of these means are different in a statistically significant manner. In
particular, pen enrollment participants were more likely to be assigned to a neighborhood
school with an API lower than the district average, be female, or identify their
race/ethnicity as other Asian. While non-participants were more likely to speak a home
language other than English, come from a low socioeconomic status, identify their race
and Latino, identify their race as South-East Asian. Figures 4.1 through 4.8 display the
comparisons of group means that are statistically significant with a confidence level of 90
percent or higher, the standard deviation for the total population, participants, and nonparticipants, the F-ration to determine whether the variances in two independent samples
are equal, the t-statistic, two tailed significance, the difference in mean, and standard
error difference.
84
Table 4.1. Comparisons of Means of Student Characteristics Between Participants and
Non-Participants Total Population of 12,354 (6,345 Participate in Choice, 6,009 Do Not)
Mean
Variable Name
API of home school lower
than district avg.
Home language is other than
English (All Races)
Standard Deviation
Total
NonTotal
NonParticipants
Participants
Population
participants Population
participants
0.388
0.481*
0.290
0.487
0.478
0.454
0.166
0.134
0.201*
0.500
0.341
0.400
Low SES
0.386
0.353
0.420*
0.372
0.478
0.494
Female
.0531
0.566*
0.493
0.487
0.496
0.500
Home language is other than
English (White)
0.062
0.051
0.074*
0.499
0.219
0.262
Hispanic or Latino
0.168
0.159
0.177*
0.241
0.366
0.382
African American
0.071
0.069
0.073
0.374
0.253
0.260
Native American
0.019
0.019
0.019
0.256
0.137
0.135
Pacific Islander
0.009
0.009
0.010
0.136
0.094
0.098
South-East Asian
0.009
0.002
0.005*
0.096
0.113
0.069
East Indian
0.003
0.002
0.004
0.113
0.049
0.062
Filipino
0.016
0.015
0.017
0.058
0.121
0.129
Korean
0.003
0.003
0.003
0.125
0.053
0.059
Japanese
0.001
0.001
0.001
0.056
0.033
0.026
Chinese
0.003
0.003
0.004
0.030
0.050
0.064
Other Asian
0.005
0.043*
0.035
0.058
0.203
0.183
Note: Participant n = 6345, Non-participant n = 6009, df = 12352. ^ Reported here is the
difference between mean of this variable for non-participant less participant. * Indicates
that a 90 percent level of confidence, the mean reported for this group is greater than the
mean for the other group.
85
Figure 4.1. Comparisons of API Score of O.E. Participants and Non-Participants
Figure 4.2. Comparisons of Home Language of O.E. Participants and Non-Participants
Figure 4.3. Comparisons of Socioeconomic Status of O.E. Participants and NonParticipants
Figure 4.4. Comparisons of Female O.E. Participants and Non-Participants
86
Figure 4.5. Comparisons of White, Non-English Home Language O.E. Participants and
Non-Participants
Figure 4.6. Comparisons of Hispanic or Latino O.E. Participants and Non-Participants
Figure 4.7. Comparisons of South-East Asian O.E. Participants and Non-Participants
Figure 4.8. Comparisons of Other Asian O.E. Participants and Non-Participants
87
Logistic regression.
The comparison of means test only examines the difference in means of
participants versus non-participants on one variable collected by the district. It does not,
however, measure the influence of one of these characteristics on participation in open
enrollment holding other explanatory variables constant. Therefore, a logistic regression
analysis was conducted to determine the impact of one independent explanatory variable
on the decision to participate in open enrollment after simultaneously controlling for all
of the other explanatory variables included in the regression. This methodology can be
thought of in this way. If two students and their parent(s) were identical in all of the
ways race/ethnic and socio-economic status are measured here, except for one of these
characteristics, the logistic regression coefficient will enable an estimation of the
influence of this difference in one characteristic on the decision to participate in open
enrollment. Note the desirable difference in this methodology from the previous
comparison of means, which did nothing to control for other characteristics.
The logistic regression model used sixteen independent variables that were
included as likely causal factors, based in part on my earlier literature review, to
influence participation. More could not be included because of the use of standard data
collected by the school district. As shown in Table 4.2, seven of the independent
variables were determined to exert an influence on participation that we can be confident
is different than zero at a 90 percent or greater confidence level in a two-tailed test (p <
.10). The Exp(B) column in Table 4.3 contains the natural exponent value of the
respective logistic regression coefficient B. To determine how a one-unit change in a
88
respective explanatory variable influence the likelihood of participation, the appropriate
calculation is (Exp(B)-1)*100 (Pampel, 2000). The value this returns indicates the
percentage increase in likelihood that a student with this characteristic, holding other
characteristics constant, is more or less likely to participate in open enrollment.
Conversely, negative values indicate that a student with that characteristic is less likely to
participate in open enrollment, holding other characteristics constant.
Table 4.2. Logistic Regression Results
B
S.E.
Wald
Sig.
Exp(B)
API of home school lower than district
1.014
.041 610.717
.000
2.756*
average
Home language is other than English
-.633
.078 72.746
.000
.515*
Low socioeconomic status
-.389
.042 84.363
.000
.678*
Female
.263
.037 49.672
.000
1.301*
Home language is other than English
.209
.110
3.586
.058
1.232*
(White)
Hispanic or Latino
-.001
.062
.000
.992
.999
African American
-.197
.076
6.690
.010
.821*
-.044
.102
.750
.957
Native American
.138
-.193
.956
.328
.825
Pacific Islander
.197
-.137
.083
.774
.872
South East Asian
.478
-.116
.581
Filipino
.152
.446
.890
.582
1.504
Korean
.474
.220
1.789
.594
.641
Japanese
.742
.424
1.811
.201
.179
Chinese
.475
.672
1.223
.729
4.266
Other Asian
.353
.039
2.074*
Note: *Indicates that this respective influence should be considered statistically
significant from zero at a greater than 90 percent degree of confidence in a two-tailed
test.
See Table 4.3 for statistically significant regression coefficients and their
corresponding variable that impacts open enrollment decisions. The variables in this
table are ordered by the absolute value of their expected influence on a parents’
89
participation in open enrollment. Also note that all of the variables are included in the
model, not only the significant ones.
The data suggests that the API of the student’s neighborhood school is the
greatest indicator of whether that student will participate in open enrollment.
Specifically, if the API of the neighborhood school is below the district average, then
controlling for other variables, the student is 175.6 percent more likely to participate in
open enrollment than a student whose neighborhood school’s API is above the district’s
average. This provides strong evidence that parents leave or fail to enroll their children
in neighborhood schools with academically underperforming students within them. Next
in magnitude of influence are Other Asians who are 107.4 percent more likely to
participate in open enrollment than the excluded category of race/ethnicity being Englishonly speaking white students. Among all races that speak a home language other than
English, however, are 48.5 percent less likely to participate in open enrollment than this
excluded category. Furthermore, African American students, or students of low
socioeconomic status are 17.9 percent and 32.2 percent less likely to participate in open
enrollment respectively. Finally, with all the student and family characteristics included
in the logistic regression remaining constant, a female student is 30 percent more likely
to participate in open enrollment than a male student, and white students whose home
language is other than English are 23.2 percent more likely to participate in open
enrollment.
90
Table 4.3 Statistically Significant Effects on Participation in Open Enrollment
Effective of
Variable
Sig. Exp(B)
Change in
Effect on Participation in Open
Variable
Enrollment
If API of neighborhood school is
API of home school
lower than the district average, the
lower than district
.000 2.756
175.6
student is 176% more likely to
average*
leave.
Other Asian*
Home language is
other than English
(All Races)
.039
2.074
.000
.515
Low socioeconomic
.000
status
0.678
Female
1.301
.000
Students who identify as Asian
ethnicity (other than other Asian
107.4 categories are 107% more likely to
leave than English-Speaking
Whites (excluded category).
Among all races, if student speaks
a language at home other than
-48.5
English, he or she is 48.5% less
likely to leave.
Low SES students are 32% less
-32.2
likely to leave.
30.1
Female students are 30% more
likely to leave.
If student speaks a language at
home other than English and is
.058 1.232
23.2
White, he or she is 23.2% more
likely to leave.
African American students are
17.9% less likely to leave than
African American* .000 0.821
-17.9
English-Speaking Whites
(excluded category).
Note: * Identifies those statistically significant variables that predict students will leave
their neighborhood schools.
Home language is
other than English
(White)
The classification table in Table 4.4 uses the logistic regression results, and the
specific characteristics of a student, to make a fitted prediction of the dependent variable
(zero for no participation, 1 for participation) for them. If the fitted value is (less) greater
than 0.5, they are predicted to (not) participate. The prediction is the compared to the
91
actual observed participation or not. The results of this comparison suggests that if we
knew nothing about our variables and guessed that a person would participate in open
enrollment that we would be overall correct 60 percent of the time. While the specific
prediction for not participating in open enrollment would be correct about 57 percent of
the time, and for participating would be correct about 63 percent of the time.
Table 4.4. Fit of the Logistic Regression Prediction
Classification Table a
Predicted
Participate in Open
Enrollment
0
1
Observed
Step 1
Participate in
Open Enrollment
Percentage
Correct
0
3399
2610
56.6
1
2334
4011
63.2
60.0
Overall Percentage
a. The cut value is .500.
Analysis of Survey Results
Descriptive statistics.
As described in Chapter 3, surveys were mailed to 490 families selected through
the stratified random sampling of students in grades 9 -12 at the three selected high
schools that were identified in the logistic regression as having students with the greatest
likelihood of participating in open enrollment.
Six surveys were returned undeliverable.
The total surveys returned for both participants and non-participants were 59 for a
response rate of 12.1 percent. Demographic data was not asked on the surveys therefore
it is unknown if the response were representative of the district as a whole. The goal of
92
the surveys was to collect and analyze unique parent perception data that is not available
in any standard district files or the GUSD Intradistrict Transfer Application, see
Appendix D for application.
The survey was sent to parents of open enrollment participating students, and
non-participating students. Part one of the survey asked five Likert scale questions
related to school safety. Part two asked nine Likert scale questions related to principal’s
leadership, academic, and social factors. Part three asked four yes or no questions related
to school programs. See Table 4.8 for a descriptive analysis of each question, and
Appendices A & B for the complete surveys. The scale for the surveys was as follows:
1. Not at all
2. A little
3. Moderately
4. Quite a bit
5. Extremely
For questions 15 through 18 where the degrees of opinion were not needed,
parents were asked a series of yes or no questions. Yes was set to a value of one and No
was set to a value of zero.
Table 4.5 Descriptive Statistics of Survey Responses (Questions 1-5)
n
Mean^
Standard Deviation
Which of the following, if any,
Total
NonTotal
NonTotal
Nonare reasons why you left (or
Sample
participants
Sample
participants
Sample
participants
Participants
Participants
Participants
stay at) your neighborhood
school?
Suspensions and or expulsions
59
34
25
1.257
1.265
1.393
0.657
0.666
0.692
Illegal drug and alcohol use
59
34
25
1.497
1.394
2.329
1.007
0.814
1.675
Fights and conflict
59
34
25
1.528
1.455
1.955
0.977
0.891
1.338
Bullying, intimidation, and or
59
34
25
1.322
1.273
1.915
0.794
0.750
1.256
harassment
Nothing specific but an overall
impression that my neighborhood
59
34
25
1.823
1.818
1.374
1.175
1.192
0.857
school is unsafe
Note: ^Variable range in value from 1 to 5; 1) Not at all, 2) A little, 3) Moderately, 4) Quite a bit, 5) Extremely.
93
Table 4.6 Descriptive Statistics of Survey Responses (Questions 6-14)
Which of the following, if any, are
n
Mean^
reasons why you were drawn to (or
Total
NonTotal
Nonstay at) your current / neighborhood Sample Participants participants Sample Participants participants
school?
The principal has a reputation of
59
34
25
2.089
2.092
2.584
success and accomplishment.
The principal ensures that the needs of
59
34
25
2.242
2.249
2.835
all students are met.
Nothing specific, but an overall
impression that my home school is
59
34
25
2.457
2.412
2.996
"better administered" than any other
school that I may have chosen.
Results on statewide tests
59
34
25
3.032
3.033
2.916
Availability of honors or accelerated
59
34
25
3.000
3.000
3.376
classes
Racial or ethnic diversity
59
34
25
1.654
1.673
1.960
Peer group influences
59
34
25
2.566
2.612
3.087
Nothing specific, but an overall
impression that the learning
59
34
25
3.371
3.353
3.433
environment is better at my chosen
school.
Child-care or ease of transporting
59
34
25
2.265
2.302
3.080
student to school
Standard Deviation
Total
NonSample Participants participants
1.269
1.288
1.288
1.329
1.348
1.312
1.421
1.417
1.472
1.424
1.446
1.320
1.495
1.518
1.379
0.988
1.413
0.997
1.407
1.274
1.498
1.592
1.612
1.438
1.650
1.660
1.824
Note: ^Variable range in value from 1 to 5; 1) Not at all, 2) A little, 3) Moderately, 4) Quite a bit, 5) Extremely.
94
Table 4.7 Descriptive Statistics of Survey Responses (Questions 15-18)
n
Mean^
Standard Deviation
Please mark Yes or No to the
following statements if they
influenced your decision to 1)
stay at your neighborhood
Total
NonTotal
NonTotal
NonParticipants
Participants
Participants
Sample
participants Sample
participants Sample
participants
school, or 2) enroll your child
in a school other than your
neighborhood school.
Preferred academic programs
59
34
25
0.383
0.392
0.750
0.486
0.392
0.433
Preferred visual and performing
59
34
25
0.125
0.183
0.417
0.322
0.183
0.493
arts programs
Negative characteristics of
59
34
25
0.254
0.288
0.290
0.420
0.288
0.455
neighborhood school
Positive characteristics of other
59
34
25
0.969
0.954
0.791
0.169
0.954
0.406
schools
Note: Variable range in value of 0 or 1; 0) No, 1) Yes
95
96
Test for equality of means.
Similar to the test conducted on the means of demographic data, an independentsamples t test was conducted to evaluate the hypothesis that certain parent perceptions
work to influence the degree to which students participate in open enrollment to a greater
degree than students whose parent(s) do not have those perceptions. Again, this test
evaluates the difference between the means of two independent groups, participants in
open enrollment, and non-participants. The t test evaluates whether the mean value of the
test variables for one group, participants in open enrollment, differs significantly from the
mean value of the test variables for the second group, non-participants in open enrollment
(Green & Salkind, 2008).
Tables 4.8 and 4.9 report the results of the difference in means test. They indicate
seven of these means are different at a confidence level of 90 percent or greater. An
additional two variables approach this threshold. For the dummy variables representing
participants in open enrollment, only one, a positive characteristic of another school was
higher for non-participants (0.968) as compared to participants (0.791.) As reported by
the survey respondents, this suggests that the overall positive perceptions of a school
besides their neighborhood school were the greatest indicator that a parent would choose
to participate in open enrollment.
Table 4.6 also shows, at a confidence of 89.9 percent, that the principal’s ability
to meet the needs of all students results in a greater likelihood that parents remain at their
neighborhood school than it draws them to other schools. While this may be a result of
parents reporting their lived experiences and relationships with administration it reveals
97
that principal leadership can be a quantifiable characteristic. Parents of students that have
never attended the neighborhood school have a limited ability to report on the
competency of the school principal however. Also of note is the perception among
participating parents that their neighborhood school is unsafe. Although parents did not
indicate specifically that drugs, fights, or bullying were concerns, the difference in mean
of 0.444 favored those participating parents. The responses tend to show that while
parents could not point to one thing in particular as a concern, the overall perception that
the neighborhood school was unsafe was greater for them than for non-participating
parents.
Childcare or ease of transportation was greater for non-participating families.
This finding may be interpreted to suggest that distance from other schools may be a
significant barrier for parents’ participation in open enrollment. Additional factors
favoring non-participating parents were the availability of preferred academic programs
and the availability of preferred visual and performing arts programs. With 75 percent of
non-participating parents indicating that preferred academic programs was a factor in
them staying at their neighborhood school, versus 36.5 percent of participating parents
indicating that preferred academic programs is what drew them to another school
supports the conclusion parents do exercise of degree of rationality when making school
choice decision. Although the difference in mean was slightly less for preferred visual
and performing arts programs (-.288), it was still a greater factor for non-participating
parents.
98
Lastly, the most significant variable leading to participation in open enrollment
was the overall perception of positive characteristics of other schools as compared to the
neighborhood school. Nearly 97 percent of participant respondents indicated that the
overall positive characteristics of other schools and not negative characteristics of the
neighborhood school influenced their decision to participate in open enrollment.
Table 4.8 Comparisons of Means of Survey Responses (Questions 1-14)
Total Respondents 59 (34 Participate in Choice, 25 Do Not)
Mean
Standard Deviation
Variable Name
NonNonParticipants
Participants
Suspensions and or expulsions
1.265
participants
1.393
Illegal drugs & alcohols
1.394
2.329*
0.814
Fights and conflict
1.455
1.955*
Bullying, intimidation, and or
harassment
1.273
Nothing specific, but an overall
impression that neighborhood
school is unsafe
0.666
Sig.
participants
0.692
.430
t
Sig. (2Mean
Std. Error
tailed) Difference^ Difference
-.718
.476
-.128
.178
1.675
.000 -2.834
.006
-.934
.330
0.891
1.338
.023 -1.722
.090
-.500
.290
1.915*
0.750
1.256
.007 -2.450
.017
-.642
.262
1.818
1.374
1.192
0.857
.050
1.584
.119
.444
.280
The principal has a reputation of
success and accomplishment
2.092
2.584
1.288
1.288
.931 -1.452
.152
-.493
.339
The principal ensures that the
needs of all students are met
2.249
2.835*
1.348
1.312
.606 -1.668
.101
-.586
.351
Nothing specific, but an overall
impression of better administration
2.412
2.996
1.417
1.472
.768 -1.540
.129
-.584
.379
Results on statewide tests
3.033
2.916
1.446
1.320
.304
.317
.752
.117
.367
Availability of honors or
accelerated classes
3.000
3.376
1.518
1.379
.569
-.976
.333
-.376
.385
Racial or ethnic diversity
1.673
1.960
0.997
1.274
.091
-.970
.336
-.287
.296
Peer group influences
2.612
3.087
1.407
1.498
.651 -1.247
.218
-.475
.381
99
Nothing specific, but an overall
impression that the learning
environment is better
3.353
3.433
1.612
1.438
.134
-.197
.845
-.080
.406
Child Care or Ease of
Transportation
2.302
3.080*
1.660
1.824
.266 -1.705
.094
-.778
.456
Note: Participant n = 34, Non-participant n = 25, df = 57. ^ Reported here is the difference between mean of this variable for
non-participant less participant. *Indicates that a 90 percent level of confidence, the mean reported for this group is greater
than the mean for the other group. Variables range in value from 1 to 5; 1) Not at all, 2) A little, 3) Moderately, 4) Quite a bit,
5) Extremely
Table 4.9 Comparisons of Means of Survey Responses (Questions 15-18)
Total Respondents 59 (34 Participate in Choice, 25 Do Not) on 4 Yes or No Questions
Mean
Standard Deviation
Variable Name
Sig.
t
Sig. (2Mean
Std. Error
NonNonParticipants
Participants
tailed) Difference^ Difference
participants
participants
Preferred Academic
0.365
0.750*
0.481
0.433
.071 -3.163 .003
-.385
.122
Programs
Preferred Visual and
0.417*
0.326
0.493
.000 -2.704 .009
-.288
.107
Performing Arts Programs 0.129
Negative Characteristics
of Neighborhood School
Positive Characteristics of
Other Schools
0.232
0.290
0.406
0.455
.239
-.516
.608
-.058
.113
0.968*
0.791
0.171
0.406
.000
2.278
.027
.176
.077
100
Note: Participant n = 34, Non-participant n = 25, df = 57. ^ Reported here is the difference between mean of this variable for
non-participant less participant. * Indicates that a 90 percent level of confidence, the mean reported for this group is greater
than the mean for the other group. Variable range in value of 0 or 1; 0 No, 1 Yes.
101
Summary
Demographic characteristics including race, ethnicity, home language, and
socioeconomic status are not statistically significant predictors of participation in open
enrollment after controlling for those characteristics and using White English only
speaking as the excluded category. As reported by survey respondents, among both
participants and non-participants in open enrollment, the availability of honors or
accelerated classes and the impression that the overall learning environment is better, led
both groups to either stay at their neighborhood school or leave their neighborhood
school to participate in open enrollment.
While the surveys were strongly suggestive of trends and parent perception, the
logistic regression results are the strongest evidence of who is participating in district
open enrollment. Further, the number of surveys returned compared to the sample size,
and the lack of any second language surveys returned at all limit the degree to which the
survey results can be generalized across the entire district. Chapter 5 provides
recommendations and additional ways to further this study.
102
Chapter 5
Conclusions and Recommendations
Introduction
The inspiration of this study came during my time as the principal of a middle
school that experienced ten years of declining enrollment. At an enrollment peak of
1,200 students the school offered a wide variety of both academically rigorous courses
and an ample selection of enrichment and elective classes. During my tenure as
principal, we had 600 students and struggled to maintain a master schedule that could
meet the needs of our growing diverse student population and be identified as a
destination school in the community. As the school district developed and implemented
its open enrollment policy, my school’s resources dwindled as the student enrollment
shrank. Going through the school artifacts and speaking to those with historical
knowledge, it became clear that the school had once been a gem, and with declining
enrollment and other factors, the school had lost its luster.
My first-hand experience witnessing students who chose to remain at their
neighborhood school not have the same access to programs that their peers in other
schools led to my alarm. I began to ask myself how I can influence school policy in so
that no matter a child’s zip code, cultural background, or socioeconomic status, he or she
could be assured that by remaining at their neighborhood school, they will have the same
high quality education and programs offered to them. From that, I chose to use this
103
dissertation as a way to investigate this issue for those students and families that have
historically been marginalized and forgotten about in our schools and communities.
The remainder of this final chapter includes an overview of the purpose of the
study and reintroduces the groups that made up the study participants. This chapter
continues with a refamiliarization with the research methods and questions, a summary of
the findings, and closes with five recommendations for school leaders intending to
implement or improve open enrollment policy.
Overview
The purpose of this study was to reveal the factors leading to the phenomenon of
parents leaving their neighborhood schools and use that information to inform open
enrollment and school improvement policies. Additionally, this study sought to uncover
the extent to which schools have the capacity to change or influence the enrollment
patterns of their schools; and to what degree do current school policies influence open
enrollment and school choice decisions of parents? The groups of parents analyzed in
this study were both the parents of high school students who had chosen to enroll their
child in a regular public school other than their assigned school of attendance, and those
who remained at their neighborhood school.
Research Questions
This study uses both qualitative and quantitative methods research. I used these
strategies to explore the characteristics of those who choose to participate, and not
104
participate in open enrollment, and to study the first hand perceptions of parents at the
center of the phenomenon of enrolling their children in public schools other than their
neighborhood schools. In order to understand the perceptions of parents choosing to
enroll their child in a school other than their home school, this study specifically perform
these research tasks:
1. What variables (available in standard data files) exert a significant impact on the
choice to participate in open enrollment, both in terms of them having a non-zero
influence and the magnitude of this influence?
2. Through correlation and mean comparison, what factors are significant in relation
to why families choose to participate in open enrollment and leave their
home/neighborhood school?
3. To what degree do current school policies influence open enrollment and school
choice decisions?
Summary of Findings
The findings of this study suggest that the statistically significant indicators of
participation in open enrollment are if the child’s neighborhood school has a lower API
than the district average, if the child is female, students are identified as White but speak
a language other than English at home, or if the child identifies as Other Asian when selfreporting race and ethnicity. The study also suggests that among all races of students
whose home language is other than English, is of low socioeconomic status, or is African
105
American, they have a decreased likelihood of participating in open enrollment.
Referring back to Table 4.3 in chapter four, you will recall that, if the API of the
neighborhood school is below the district average, then controlling for other variables,
the student is 175.6 percent more likely to participate in open enrollment than a student
whose API of neighborhood school is above the district average. Next, are Other Asians
who are 107.4 percent more likely to participate in open enrollment than the excluded
category of race/ethnicity, which is English speaking, White. African American students
are 17.9 percent less likely than this excluded category. Furthermore, a student of any
race/ethnicity whose home language is not English is 48.5 percent less likely to
participate in open enrollment. In contrast to this previous group, White students that
speak a language other than English at home are 23.2 percent more likely to participate
in open enrollment than the excluded category. A low socio-economic student is also
32.2 percent less likely to participate than a higher socio-economic student. Finally,
holding the characteristics included in the logistic regression constant, a female student is
30 percent more likely to participate in open enrollment than a male.
This study further finds that the overall positive characteristics of other schools
was the most statistically significant perceptual factor leading to participation in open
enrollment, while ease of transportation and the belief that the principal meets the needs
of all students were the greatest perceptual factors in determining if parents stay at their
neighborhood school. Preferred academic programs and visual/performing arts
programs, specifically the International Baccalaureate, special education, band, drama,
106
and sports were factors for both participants and non-participants. However, the
difference in mean between these two variables favored those who chose to stay at their
neighborhood school.
Research question 1. What variables (available in standard data files) exert a
significant impact on the choice to participate in open enrollment, both in terms of them
having a non-zero influence and the magnitude of this influence?
Research question one was addressed using the quantitative data obtained from
the school district. Through logistic regression analysis, Figures 5.1 and 5.2 display
which characteristics were significant indicators (with a confidence level of 90 percent or
greater) that students with these characteristics would have an increased or decreased
likelihood of participating in open enrollment.
Figure 5.1. Characteristics likely to increase and Decrease Participation in Open
Enrollment
107
Figure 5.2. Graphical Representation of Numerically Significant Factors that Influence
Open Enrollment Decisions – From Logistic Regression
Research question 2. Through correlation and mean comparison, what factors
are significant in relation to why families choose to participate in open enrollment and
leave their home/neighborhood school?
Research question two was addressed using the quantitative data from the parent
surveys. As described earlier, participation in open enrollment was more closely tied to
overall school academic performance and the overall positive characteristics of the
school. Specific factors and perceptions linked to school safety were not closely related
to participation in open enrollment. However, the rating of the overall impression that
the neighborhood school was unsafe was slightly higher for participants than non-
108
participants. As reported in Chapter 4, the confidence of this finding at less than 90
percent suggests more that the lived experiences of those that stayed at their
neighborhood school are stronger than the perceptions of families that have not sent their
child to the neighborhood school. The response from participant parent in Case 26
reinforces the conclusion that lived experiences are more powerful than perceptions
alone. “Older siblings went to neighborhood school and left due to environment there”
(Anonymous Case 26, 2013).
Figure 5.4 shows the results for the comparison of means from the parent surveys.
Among the 14 Likert scale questions with ranges from 1 to 5, the parent perceptions with
a numerically significant difference are listed in Figure 5.3. This figure further illustrates
the degree to which non-participating parents rated transportation and school safety
perceptions higher than parents participating in open enrollment.
The parent survey also included four yes or no questions related to academic
programs. Figure 5.4 illustrates that preferred academic and visual and performing arts
programs were significant factors in parents choosing to stay at their neighborhood
school. While overall positive characteristics of other schools was a significant factor in
parents choosing to participate in open enrollment. The lack of district provided home to
school transportation is an additional factor that forces many parents to keep their
children in their neighborhood schools. Transportation and / or child care were greater
factors for non-particpants in open enrollment than participants.
109
Figure 5.3. Mean Scores of Statistically Significant Parent Perceptions Regarding
Academic Programs
Research question 3. To what degree do current school policies influence open
enrollment and school choice decisions?
Research question 3 was addressed through the qualitative written responses to
the parent surveys, the responses to questions 14 – 16 on the survey, and through an
examiniation of the open enrollment application found in Appendix C. The findings
suggests that programtic decisions and policies related to which schools offer which
programs appear to be the significant policy related factors affecting school choice
decisions. Additionally, transportation and distance appear to be factors that contribute to
both participation and non-participation in open enrollment. Although transportation and
child care were were more significant for nonparticipants, the following comments from
particpating parents indicate that district boundaries force parents force parents to
particpte if they want their child to attend the school closer to their homes.
110
“We live one mile from our current school. Our neighborhood school is six miles away”
(Annonyous Case 9 participant, 2013).
“None of these were the reason I didn’t send my children to the neighborhood school.
The reason I didn’t send my children to the neighborhood school was because [it] was not
the closest school to my house. I live closer to open enrollment schools than
neighborhood schools” (Annonymouse Case 18 participant, 2013).
“This school is closer and more academic” (Annonymous Case 10 participant, 2013).
Figure 5.4 above shows that in regards to programs, three quarters of nonparticpating parents indicated that prefferred academic programs and nearly half of all
non-participating parents indicated that preferred visual and performing arts programs
were reasons why they stay at their neighborhood school. Table 5.1 list the programs that
non-participating parents specifically identifed as preferred.
111
Table 5.1. Programs that Influence Parents’ Decision to Stay at Their Neighborhood
School
Programs That Influenced Parents to Stay at their Neighborhood School
Advance Placement (AP) classes
Art
AVID (Advancement Via Individual Determination)
Band
Choir
Drama
Evening of the Arts
GATE program
High Achiever classes
Home Economics
International baccalaureate
International studies
Junior ROTC
Morning sing
PTA sponsored plays
Talent shows
Table 5.2 below, in contrast, lists the peferred programs specifically identified by
particpating parents. Since not all parens submitted written responses, these two tables
are not meant to represent all of the possible programitc choices. However, they are
further indicators that parents do in fact exercise a certain degreee of rationality when
making enrollmen decisions.
112
Table 5.2. Programs that Influenced Parents’ Decision to not Enroll Their Child at the
Neighborhood School
Programs That Influenced Parents’ Decision to not Enroll at their Neighborhood
School
Clubs
Cross country team
Drama
Field trips
GATE program
International baccalaureate
Japanese
Marching band
Desire to not be on a block schedule
Polytechnic institute
Radio and TV
Rapid learner program
Special education program
Sports
Track and field
The following direct quotes from parents were provided on the paretn surveys.
They provide greater insight into the thought process and specific reasons for particpation
in open enrollment.
“We stay at our neighborhood school because our student wants to stay with her friends.
As parents, we prefer another high school” (Case 15, non-participant)
“Band at home school needs more support monetarily and administratively” (Case 15,
non-participant).
113
“My son is not involved with these programs, but I have seen on the district website
programs offered at the school and some videos of what the students have done” (Case
11, non-participant).
“We wish [School B], our neighborhood school, had a better music program” (Case 7,
non-participant).
In response to peer group influences, “It’s where all their friends are” (Case 7, nonparticipant).
“The other important factor was that our current high school student wanted a different
experience than his brothers. He wanted to go to a new school with new students and to
make new friends” (Anonymous Case 1 participant, 2013)
“Since transferring to [charter school], classes she was getting F in she is now getting a
B” (Case 29, participant)
In regards to questions 17 & 18, “Definitely both. If you take the Baccalaureate program
out of [School B] test results, its one of the most poorly performing schools in the district.
So if your student is not in that program it’s a bad environment. [School A] has
outstanding test results across the board and college prep is encouraged for all students.
But its ethnically/socioeconomically diverse as well” (Case 26, participant)
114
Discussion
School choice advocates have long pointed to the benefits afforded to minorities
and families in poverty that are able to exit their often failing school for another school.
As discussed in Chapter 2, state and federal laws requiring that districts allow transfers of
students that attend any one of the state’s consistently low-performing or persistently
dangerous schools reinforce this belief. The statistically significant findings of this study
reveal that when controlling only for race and ethnicity, African American students were
less likely to participate in open enrollment than White students. Further, low
socioeconomic students, students whose home language is other than English, and male
students were also less likely to participate in open enrollment, see Figure 5.2.
The findings of this study are consistent with those of Farrell, Jr. & Mathews
(1990), George & Farrell, Jr., (1990), Jones-Wilson, Arnez, & Asbury (1992), and
Johnson (2006). I contend that lack of transportation, cultural barriers, and economics
are powerful forces in limiting the access of historically disadvantaged students to quality
schools. Furthermore, transportation related issues are reasons for staying at the
neighborhood school. Providing choice alone, without concerted efforts to change
underperforming schools only avoids the complex and often difficult task of real school
reform. The most importing factor, however, in choice to leave is if the neighborhood
school has a lower API scoe than the district average.
Returning to the theoretical frameworks that served as the backdrop for this study,
it is clear that a certain degree of rationality and social awareness were factors in parents
115
excersicing choice for their child. Beginning with rational choice theory, we accept that
human decision-making is based on their need to maximize self-interest. I can infer from
the results of the parent surveys that motivaion, goal attainment, and personal advantage
were driving factors in the decsion-making process for parents. The desire for preferred
academic programs implies that parents undertook some research in examining programs.
As described in Chapter 1, non-particpants in open enrollment are also choosers,
in that they are making the choice to stay. Rational choice theory can also help to explain
this. When transportation and child care are significant factors for non-particpants, it
logically follows that it is irrational for those parents to change schools. Or it is more
likely that keeping their child at their neighborhood school is a greater maximizer of their
resources. Although not specifically answered by this study, it can be argued then that
social cohesives, ability to particpate in after school activities, cost of transportation, and
maintaining peer group are more or as important to parents as association with higher
achieveing students.
Social cognitve theory, in contrast, considers human emotions and experiences in
examining decision-making. This study revealed that peer-group influences were not an
overt driver of choice, however the fact that the most prevalant factor in choice was the
home school’s API shows that parents did prefer to have their children attend school with
higher performing students. I conclude that parents are more willing to describe their
child as high achieveing and therefore want them to be around other similar ability
students, rather than describe them as low-achieveing and want them to be around higher
116
achieving students. It is a nuance that is not explored in this study, but social cognitive
theory supports the idea that self-identification, pereived social status, prestige, and social
power are all powerful contextual factors related to choice.
As described in Chapter 1, the core assumption regarding social cognitive theory
is that environment, people, and behavior are three factors that are constantly influencing
each other. Parents belived that by selecting the new school that were choosing the
environment that provides the greatest opportunity for success and social support. The
choice of a new school also provided the opportunity for observational learning with the
goal of their child acquiring skills by watching the outcomes and actions of others.
Lastly, by being surrounded by other high achieveing students, parents hoped for greater
reinforcements through intrinsic rewards and incentives. SCT holds that “learners are
proactively engaged in their own development and can make things happen by their
actions” (Jabbarifar, 2011, p. 118). Parents of choosers then are relying on this theory to
function in order for their child’s self efficacy to improve and they in turn increase their
confidence in performing school related tasks.
The findings of this study reveal that students whose home language is other than
English, African American students, and lowa socioeconomic student are less likely to
pursue those goals. Whereas females, other Asians, and non-English speaking White
students are more likely to exercise school choice as a means of fullfilling the goals
described above.
117
Policy Implications
Although this study did not overtly seek to evaluate the educational effectiveness
of choice programs, I did not find that choice policies alone improve the efficiency or
effectiveness of traditional public schools. The forces of a market-driven system are
extremely powerful when parents choose to leave underperforming schools. School
principals and teachers cannot ignore the repelling affect of below average API scores.
Equipped with this awareness, school district leaders must provide site principals and
teachers with the needed resources in order to successfully transform into a high
achieving school. This is true in and out of open enrollment environments.
We also cannot rule out the potential benefits of such policies. Improved
outcomes for choosers and matching families with programs appear to be the two most
relevant outcomes of choice. Future and current policies must also consider equity and
the impact of dissolving social cohesion. Further, this study confirms that the poor,
African American, and students who speak a language other than English are not
significant participants when it comes to school choice. Therefore, it is problematic for
policy makers to predict that choice programs will more greatly benefit traditionally
underserved students since there is yet to be strong or conclusive evidence in support of
this.
A discussion of policy would be incomplete without acknowledging the important
role school boards, superintendents, principals, teachers, parents, and community play in
the overall debate. Educating each on finance, equity, non-monetary resources, and
118
potential disparities in spending related to minorities is key (Darden & Cavendish, 2011).
As California begins to rebound from the recession and more money is available to
schools, school policy makers must resist trying to solve the education gap by adding
programs alone. As a new weighted funding formula for schools makes its way through
the state’s legislature, superintendents must ensure that all stakeholders are well informed
and school choice policies remain only a part of a broader educational improvement
strategy.
Recommendations
The following recommendations are intended for practitioners and officials at all
levels of pre-K – 12 education. Support of open enrollment policies should be contingent
upon a concurrent effort to support and improve underperforming schools. It is important
to acknowledge that this broader discussion of school improvement would include
decreasing drop out rates, the disproportionality of suspension and expulsions of Black
and Latino students, chronic absenteeism, cigarette, alcohol, and drug abuse, teen
pregnancy, school violence, teacher evaluation and retention, improved public health, and
finance reform among others. Additionally, these recommendations are based on the
current K-12 funding model and that no additional funding is available. Therefore,
implementation of these recommendations may require the shifting of budget priorities.
Based on the findings of this study, I recommend the following bold changes and
or enhancement to any existing open enrollment policy:
119
1.
Ensure that all high schools have the option to offer all of the programs that the
community desires.
2.
Provide more and better information to the most vulnerable groups regarding
choices. (Speakers of languages other than English, African American, low
socioeconomic)
3.
Add transportation to foster more participation
4.
Tap into the educational aspirations of the poor.
1. Ensure that all high schools have the option to offer all of the programs that the
community desires.
With the understanding that there are a finite number of marching-band leaders,
teachers of languages other than English, music instructors, and others with specialty
skills, school district leaders must ensure that those highly sought after programs are not
clustered in geographic locations that favor any particular group. Additionally, schools
should not be forced to decide between being using their teaching allotment to offer
support classes or Advanced Placement classes. The results of the survey strongly
indicate that programs, in additional to overall achievement, are powerful forces driving
choice. It has already been establish that several disadvantaged groups are less likely to
exercise choice. Rather than forcing them to go to certain programs, we have a moral
imperative to bring those programs that we know increase academic success to them.
120
In the event the creation of new programs is cost prohibitive, the transfer of
desirable programs to under-enrolled schools may be an option to dealing with the
economies of scale. It is foreseeable that a policy of transferring programs in order to
create desirable schools where they currently do not exist will lead to protest. Although I
have spent little time discussing school leadership, this creates a tremendous opportunity
for school leaders to build relationships across communities. The protest, however, may
never come. Take for example the International Baccalaureate program. Based on the
survey responses, it is the most desirable program of open enrollment participants and it
is offered at only one site. That program then could be offered anywhere and still attract
students.
With high school enrollments in GUSD ranging from 700 to 2000 students,
district leaders may consider capping enrollment in order to balance student body sizes.
2. Provide more and better information to the most vulnerable groups regarding
choices. (Speakers of languages other than English, African American, lowsocioeconomic)
A search of the GUSD high school web sites by me, someone who is well versed
and knows well how to navigate K-12 education, discovered as many as six different
names for what qualifies as a course catalog. They include 1) Course Catalog, 2) Course
Description Handbook, 3) Majors and Career Exploration, 4) School Handbook, 5)
Career Handbook, and 6) Course Handbook. This alone can confuse the savviest parents.
121
Therefore, providing clear, thorough, and accurate, and consistent information to parents
must be a major tenet of any open enrollment plan. Parents who are unable to access the
“grapevine” of knowledge described by Ball and Vincent (1998), or the adequate social
capital, are at an extreme disadvantage compared to those parents that are well connected
or have a network of other parents who provide information. Speakers of languages other
than English and those with out access to these social networks are commonly left
without the information they need which only further compounds the problem that school
choice advocates are looking to solve. Providing parents with this information will lead
to one of two outcomes. First, more information about the programs available will lead
to more choice. Or second, parents will learn about the programs offered at their
neighborhood schools and want to stay. The goal I am suggesting is to not force families
out of their neighborhood schools, but to provide them with information in order to make
informed decisions.
Schools and school districts must endeavor to balance the informal information
gathering and exchanges among parents with accurate, formalized means of
disseminating information. Below list the main sources of information for parents:

“Grapevine” of knowledge

Parent information nights held by the school

School website

School information sheets provided at the central enrollment office

School visitation days
122
Parents then are presumed to have accessed these resources, thoughtfully considered
the pros and cons carefully weighing all options, and then come to an informed rational
decision before being asked to complete a one-page transfer application. An emerging
practice among school districts is to require parents who are requesting an out of district
transfer to tour their home school. It is unclear if this practice is an effort to retain
students at their home school or just provide an additional hurdle, but with 51 percent of
GUSD students participating in open enrollment, extending that requirement to
intradistrict transfers also would place too high a burden on school sites. What we do
know from my research is that perception about a school and the actual lived experiences
of parents that actually send their child to that school are not always congruent. Again, at
the center of any school choice policy must be the commitment to providing all families
with accurate and timely information.
I further recommend the examination of the course catalogs for every high school to
ensure parity.
3. Add transportation to foster more participation.
School choice programs can sometimes further stratify and segregate
communities. GUSD does not provide home to school transportation for students unless
required by their individualized education plan. However, a plan that limits
transportation to targeted groups low-income, low-performing, language minority can
manage costs and still meet the educational needs of all of its students. Although
123
transportation in itself is expensive, the cost of remediation and credit recovery for high
school students is even more so.
I also recommend school districts map all schools and calculate drive times and
distances from school to school and provide that information to parents along with
transfer applications.
4. Tap into the educational aspirations of the poor.
Status attainment was not specifically reviewed in this study, however the work of
Peter Blau (1918-2002) and Otis Duncan (1921-2004) forced sociologists to ask the
question of how do people attain status and under what conditions can they be upwardly
mobile. Broadly, status attainment refers to a person’s position in society or class. Not
only does family income and education influence attainment, so does one’s own ability
and effort. Blau and Duncan (1967) discovered that men whose fathers held high-status
jobs had increased odds of themselves attaining high status. They found a greater
correlation, however, between education and status attainment. But what is clear from
their research is that it was much better to start at the top than at the bottom (Lin, 1999).
With this understanding coupled with the knowledge that not all families have the
resources to participate in open enrollment, I recommend that GUSD form organized
outreach to those communities least likely to participate in open enrollment and work to
organize and invest their human resources to improve the educational outcomes of
students in their communities. By leveraging the direct ties that each of them have, the
124
community will work together to advance the group as a whole rather than an individual
student at a time. Figure 5.2 is simplified representation and modification of a social
capital conceptual framework. It demonstrates how social cohesion and social capital
work together to produce desired educational results.
I recommend a combination of paid and volunteer workers to implement such a
plan. The ability of community members to volunteer is directly tied to economic
factors. As discussed in Chapter 1, higher rates of volunteering, among other things,
result from higher education. Therefore, school leaders cannot make the mistake of
presuming that communities in poverty will have the resources to sustain a completely
volunteer run program.
Figure 5.4. Conceptual Framework of Educational Goal Attainment
1. Connectedness
2. Values
1.
2.
3.
4.
Social Support
Social Leverage
Informal Social Support
Community Participation
125
While these recommendations advocate for expanded school choice, it would be
irresponsible, unethical, and immoral to not consider the following arguments. With any
of the recommendations it is important to account for the years of marginalization
experienced by ethnic and language minority groups. Improvement efforts will often
been met with suspicion, doubt, a sense of panic, or uncertainty (Ball & Gewirtz, 1997).
If not done carefully, school choice programs can work to destabilize the very system that
is the basis for our democracy. Widespread, unrestricted open enrollment may also drain
the financial resources of the most needy communities and lead to further racial, ethnic,
and economic stratification. The ultimate challenge for school districts will be
implementing a policy that minimizes the harm to some while improving the outcomes
for all.
Future Research
Under the umbrella a school choice are a variety of options. Included are interand intradistrict transfers, public charter schools, private schools, home schools, and
online schooling. The results of this study, as it relates to intradistrict transfers may be
enhanced by further research in the following areas:
Qualitative Interviews

While the parent surveys exposed many of the perceptions of participants and
non-participants, one-on-one interviews or focus groups would further uncover
the nuances associated with school choice.
126
Longitudinal Study of Participants in Open Enrollment

The long-term benefits of open enrollment can only be known by matching
identical cohorts of students from both groups and comparing their progress over
time.
Further Examination of Cultural Barriers to School Choice

The knowledge that African American, low socioeconomic, speakers of languages
other than English, and male students do not participate in open enrollment in
significant numbers is not enough to inform policy. What is missing is insight
into the kitchen table conversations that happen in homes across the state prior to
and during the open enrollment period.
Examination of different theories that may apply to school choice
•
This study briefly touched on goal attainment and social capital as additional
forces driving parent choice. Additional research my further explore the link
between these two theories and parent participation in open enrollment
A new policy problem has emerged
•
The original policy problem statement asserted that choice leads to the
deterioration of neighborhood schools in urban areas. What has emerged from
my study is a second problem; increased choice has led to enrollment patterns that
do not represent the communities of the neighborhood schools or choice schools.
Future research may explore the link between the achievement gap, social
participation, and enrollment patterns.
127
Appendix A
Probability in Finding a School Attribute Important
The change in the probability of finding a school attribute important, 1582 parents in
New York City suburbs.
Hi Scores
Black
Asian
Hispanic
Other
College
HS Grad
Private
New York
.089*
(.036)
.078
(.070)
.054
(.039)
-.026
(.055)
-.088*
(.034)
.155*
(.035)
.011
(.030)
.025
(.031)
.300
26.99
0.00
.03
Values
-.097*
(.025)
-.057
(.048)
-.115
(.031)
-.041
(.043)
.085*
(.033)
-.074**
(.047)
.163*
(.030)
-.029
(.028)
.228
115.46
0.00
.13
Discipline
Diversity
.0633**
-.001
(.031)
(.016)
1.77*
-.067*
(.069)
(.011)
.177*
- .063*
(.032)
(.018)
.058
.036
(.050)
(.035)
-.066*
.068*
(.024)
(.016)
-.001
-.027
(.024)
(.034)
.040
-.085
(.021)
(.010)
.050*
-.001
(.021)
(.017)
.135
.095
105.40
102.61
0.00
0.00
.14
.15
Obs. Prob.
Chi2
P > Chi2
Pseudo R2
Notes: *probability <. 05,
**probability <. 10,
All significances are two tailed.
Numbers n parentheses are standard errors. Numbers above standard error
represent the change in probability for a discrete change in the independent
variable from 0 to 1 (Schneider, Marschall, Teske, & Roch, 1998).
128
Appendix B
Survey to Parents Participating in Open Enrollment
Section One
Which of the following were reasons why you left your neighborhood school?
1
Student suspensions and/or expulsions
2
Illegal drug and alcohol use
3
Fights and conflict
4
Bullying, intimidation, and/or harassment
5
Nothing specific, but an overall impression that my neighborhood school was
"unsafe."
not at all
1
a little
2
RATING
moderately
3
quite a bit
4
extremely
5
not at all
1
a little
2
RATING
moderately
3
quite a bit
4
extremely
5
Section Two
Which of the following were reasons why you were drawn to your current
school?
6
The principal has a reputation of success and accomplishment.
7
The principal ensures that the needs of all students are met.
8
Nothing specific, but an overall impression that my chosen school is "better
administered" than my neighborhood school.
9
Results on statewide tests
10
Availability of honors or accelerated classes
11
Racial or ethnic diversity
12
Peer group influences
13
Nothing specific, but an overall impression that the learning environment is
better at my chosen school than at my neighborhood school.
14
Child-care or ease of transporting student to chosen school
Section Three
Please mark Yes or No to the following statements if they influenced your decision to enroll your child in a school other than your
neighborhood school.
yes
no
yes
no
yes
no
yes
no
My neighborhood school did not offer the preferred academic programs.
If yes, please list any programs
15
My neighborhood school did not offer the preferred visual and/or performing arts programs.
If yes, please list any programs
16
Overall, the decision to leave my neighborhood school more based on negative characteristics that pushed me
17
away from it.
18
Overall, the decision to leave my neighborhood school was more based on the positive characteristics of my
chosen school that pulled me toward it.
129
Appendix C
Survey to Parents not Participating in Open Enrollment
Section One
Which of the following, if any, are concerns at your neighborhood school?
1
Student suspensions and/or expulsions
2
Illegal drug and alcohol use
3
Fights and conflict
4
Bullying, intimidation, and/or harassment
5
Nothing specific, but an overall feeling that my neighborhood school is
"unsafe."
not at all
1
a little
2
RATING
moderately
3
quite a bit
4
extremely
5
not at all
1
a little
2
RATING
moderately
3
quite a bit
4
extremely
5
Section Two
Which of the following, if any, are reasons why you stay at your neighborhood
school?
6
The principal has a reputation of success and accomplishment.
7
The principal ensures that the needs of all students are met.
8
Nothing specific, but an overall impression that my home school is "better
administered" than any other school that I may have chosen.
9
Results on statewide tests
10
Availability of honors or accelerated classes
11
Racial or ethnic diversity
12
Peer group influences
13
Nothing specific, but an overall impression that the learning environment is
better at my neighborhood school than any other school that I may have
chosen.
14
Child-care or ease of transporting student to school
Section Three
Please mark Yes or No to the following statements if they influenced your decision to stay at your neighborhood school.
15
yes
no
yes
no
yes
no
yes
no
My neighborhood school offers the preferred academic programs.
My neighborhood school offers the preferred visual and/or performing arts programs.
If yes, please list any programs
16
Overall, the decision to stay at my neighborhood school is more based on negative characteristics of other
17
schools that keeps me here.
Overall, the decision to stay at my neighborhood school is more based on positive characteristics of this school
18
that keeps me here.
130
Appendix D
GUSD Intradistrict Transfer Application
131
References
Abell, P. (1990). Denzin on rational choice theory. Rationality and Society , 2 (4), 495499.
Adler, N. E., Boyce, T., Chesney, M. A., Cohen, S., Folkman, S., Kahn, R. L., et al.
(1994, January). Socioeconomic status and health: The challenge of the gradient.
American Psychologist , 49 (1), pp. 15-24.
Akey, T., Plucker, J. A., Hansen, J. A., Michael, R., Branon, S., Fagan, R., et al. (2008).
Study of the effectiveness and efficiency of charter schools in Indiana.
Bloomington: Center for Evaluation and Education Policy.
Anonymous. (2013, January 19). Survey Test. (C. A. Morris, Interviewer)
Arsen, D., & Ni, Y. (2008). The competetive effect of school choice policies on
performance in traditional public schools. East Lansing: Great Lakes Center for
Educational Research & Practice.
Aud, S., Fox, M. A., & Kewal-Ramani, A. (2010). Status and trends in the education of
racial and ethnic groups. National Center for Education Statistics. Washington,
DC: U.S. Department of Education.
Ball, S. J., & Gewirtz, S. (1997). Grls in the education market: Choice, competition and
complexity. Geneder and Education , 9 (2), 207-222.
Ball, S. J., & Vincent, C. (1998). 'I heard it on the grapevine': 'Hot' knowledge and school
choice. British Journal of Sociology of Education , 19 (3), 377-400.
132
Ballou, D., Goldring, E., & Liu, K. (2006). Magnet schools and student achievement.
Vanderbilt University. New York: National Center for the Study of Privitazation
in Education.
Baranowski, T., Perry, C. L., & Parcel, G. S. (1997). How individuals, environments, and
health behavior interact: Social cognitive theory. In K. Glanz, F. M. Lewis, & B.
K. Rimer (Eds.), Health behavior and health education: theory, research, and
practice (2nd Edition ed., pp. 153-178). Jossey-Bass.
Beaudin, B. Q. (2003). Interdistrict Magnet Schools and Magnet Programs in
Connecticut. Bureau of Evaluation and Educator Standards, Division of
Evaluation and Research. Hartford: Connecticut State Department of Education.
Bennett, M., & Sani, F. (2008). Childrens subjective identification with social groups: A
self-stereotyping approach. Developmental Schience , 11 (1), 69-75.
Betts, J. R., Rice, L. A., Zau, A. C., Tang, Y. E., & Koedel, C. R. (2006). Does school
choice work? Effects on student integration and achievement. San Francisco:
Public Policy Institute of California.
Brace, N., Snelgar, R., & Kemp, R. (2012). SPSS for Psychologists (5th Edition ed.).
New York: Palgrave Macmillan.
California Department of Education. (2012, May). 2011–12 Academic Performance
Index Reports: Information Guide . Retrieved June 10, 2012, from California
Department of Education:
http://www.cde.ca.gov/ta/ac/ap/documents/infoguide12.pdf
133
California School Boards Association. (2010, November). CSBA Sample Board Policy.
Retrieved September 30, 2012, from California School Boards Association:
http://www.csba.org/en/Services/Services/PolicyServices/~/media/938CE5EC32
DE4943A06530DD3903F05D.ashx
Carlson, D., Lavery, L., & Witte, J. F. (2011). The determinants of interdistrict ope
enrollment flows: Evidence from two states. University of Wisconsin-Madison,
Educational Evaluation and Policy analysis. Madison: American Educational
Research Association.
Center for Education Reform. (2009). K-12 Facts. Retrieved 2011 йил 6-May from
http://www.edreform.com/Fast_Facts/K12_Facts/
Christensen, B., Eaton, M., Garet, M. S., Miller, L. C., Hikawa, H., & DuBois, P. (2003).
Evaulation of the magent schools assitance program, 1998 grantees. U.S.
Department of Education, Office of the Under Secretary Policy and Program
Studies Service. Washington, D.C.: American Institutes for Research.
Cookson, P. W. (1994). School choice: The struggle for the soul of American education.
Binghampton, NY: Vail-Ballou.
Crain, R. L., Allen, A., Thaler, R., Sullivan, D., Zellman, G., Little, J. W., et al. (1999).
The effects if academic career magnet education on high schools and their
graduates. Berkeley: National Center for Research in Vocational Education.
Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods
approaches (3rd Edition ed.). Los Angeles, CA: Sage Publications.
134
Culter, D. M., & Lleras-Muney, A. (2008). Education and health: Evaluating theories and
evidence. (R. F. Schoeni, J. F. House, G. A. Kaplan, & H. Pollack, Eds.) Making
Americans healthier: Social and economic policy as health policy , 29-60.
Darden, E. C., & Cavendish, E. (2011). Achieving resource equity within a single school
district: Erasing the opportunity gap by examining school board decisions.
Education and Urban Society. Washington, DC: Sage.
de Souza Briggs, X. (1997). Moving p versus moving out: Neighborhood effects in
housing mobility programs. Housing Policy Debate , 8 (1), pp. 195-234.
Dee, T. S. (1998). Competition and the Quality of Public Schools. Economics of
Education Review , 17 (4), 418-427.
Delpit, L. (1995). Other people's children: Cultural conflict in the classroom. New York,
New York: New Press.
Denzin, N. K. (1990). Reading rational choice theory. Rationality and Society , 2 (2),
172-189.
Dillon, E. (2008). Plotting school choice: The challenges of crossing district lines.
Washington, D.C.: Education Sector.
Dynarski, S., Hoxby, C., Loveless, T., Schneider, M., Whitehurst, G., & Witte, J. (2010).
charter schools: A report on rethinking the federal role in education. The
Brookings Institute, Brown Center on Education Policy. Washington, DC: The
Brookings Institute.
135
Education Commisson of the States. (2012). Education Commission of the States-Helping State Leaders Shape Education Policy. Retrieved July 25, 2012, from
Choice of Schools:
http://www.ecs.org/html/issue.asp?issueid=22&subissueid=326
Edwards, B., Crane, E., Barondess, H., & Perry, M. (2009). California's charter schools:
2009 update on issues and performance. EdSource. Mountain View, CA:
EdSource.
Farrell, Jr., W. C., & Mathews, J. E. (1990). School choice and the educational
opportunities of African american children. The Journal of Negro Education , 59
(4), 526-537.
Foster, K. M. (2004). Coming to terms: A discussion of John Ogbu's cultural-ecological
theory of minority academic achievment. Intercultural Education , 15 (4), 369384.
Fowler, F. C. (2002, September/October). The great school choice debate. The Clearing
House , 76 (1), pp. 4-7.
Frankenberg, E., Siegel-Hawley, G., & Wang, J. (2010). Choice without equity: Charter
school segregation and the need for civil rights standards. Los Angeles, CA: The
Civil Rights Project/Proyecto Derechos Civiles at UCLA.
Frey, A., Ruchkin, V., Martin, A., & Schwab-Stone, M. (2009). Adolescents in transition:
School and family characteristics in the development of violent behaviors entering
high school. Child Psychiatry & Human Development , 40 (1), 1-13.
136
Fullan, M. (2006). Change theory: A force for school improvement. Centre for Strategic
Education. Victoria: Centre for Strategic Education.
Fuller, B., Burr, E., Huerta, L., Puryear, S., & Wexler, E. (1999). Abundant hopes, scarce
evidence of results. University of California, Berkeley and Stanford University.
Berkeley, CA: Policy Analysis for California Education.
Gallup. (2011, August 19). Parents, Americans Much More Positive About Local
Schools. Retrieved June 10, 2012, from Gallup:
http://www.gallup.com/poll/149093/Parents-Americans-Positive-LocalSchools.aspx
Gamoran, A. (1996). Student achievement in public magnet, public comprehensive, and
private high schools. Educational Evaluation and Policy Analysis , 18 (1), 1-18.
George, G. R., & Farrell, Jr., W. C. (1990). School choice and African American stuents:
A legislative view. The Journal of Negro Education , 59 (4), 521-525.
Goodman, R. H., & Zimerman, W. G. (2000). Thinking differently: Recommendations for
21st century school board/superintendent leadership, governance, and teamwork
for high student achievment. New England School Development Council.
Arlington: Educational Research Service.
Green, S. B., & Salkind, N. J. (2008). Using SPSS for windows and Macintosh: analyzing
and understanding data (5th Edition ed.). Upper Saddle river, NJ: Pearson.
Green, S. (2002). Rational choice theory: An Overview. Baylor University.
137
Heebner, A. L. (1995). The impact of career magnet high schools: Experimental and
qualitative. Journal of Vocational Educational Research , 20 (2), 22-55.
Herrmann, A. M., Burroughs, N., & Plucker, J. A. (2009). Open Enrollment in K-12
Public Education. Center For Evaluation & Education Policy , 7 (3).
Hill, P. T., & Lake, R. J. (2010). The charter school catch-22. Journal of School Choice:
Research, Theory, and Reform , 4 (2), 232-235.
Hoxby, C. M. (2009, May 5). Charter school research and economics. (S.-M. Institute,
Interviewer)
Hoxby, C. M. (2000). Does Competition among Public School Benefit Students and
Taxpyers? The American Economic Review , 90 (5), 1209-1238.
Hoxby, C. M. (2009, May 5). The promise and performance of charter schools: Drivers
of educational improvement in the U.S.? Lecture . St. Louis, Missouri: St. Louis
University.
Hoxby, C. M. (2002). Would school choice change the teaching proession? The Journal
of Human Resources , 37 (4), 846-91.
Hoxby, C. M., & Murarka, S. (2009). Charter schools in New York city: who enrolls and
how they affect their students' achievement. National Bureau of Economic
Research. Cambridge, MA: National Bureau of Economic Research.
Hsieh, C.-T., & Urquiola, M. (2006). The effects of generalized school choice on
achievement and stratification: Evidence from Chile's voucher program. Journal
of Public Economics , 1477-1503.
138
Iarossi, G. (2006). The power of survey design: a user's guide for managing surveys,
interpreting results, and influencing respondents. Washington, DC: The World
Bank.
Jennings, J. L. (2010). School choice or schools' choice? Managing in an era of
accountability. Sociology of Education , 83 (3), 227-247.
Jimerson, L. (2002, September/October). Interdistrict open enrollment: The benign
choice? The Clearing House , 76 (1), pp. 16-19.
Johnson, H. B. (2006). The American dream and the power of wealth: Schools and
inheriting inequality in the land of opportunity. New York, NY: Routledge.
Johnson, H. B., & Shapiro, T. M. (2003). Good neighbors, good schools: Race and the
"good choices" of white families. In A. Doane, & E. Bonilla-Silva (Eds.), White
out: The continuing significance of racism. New York: Routledge.
Jones-Wilson, F. C., Arnez, N. L., & Asbury, C. A. (1992). Why not public schools?
Journal of Negro Education , 61 (2), 125-137.
Kahlenberg, R. D. (2006). Helping children move from bad schools to good ones. New
York: The Century Foundation.
Koedel, C., Betts, J. R., Rice, L. A., & Zau, A. C. (2009). The integrating and segregating
effects of school choice. Peabody Journal of Education , 84 (2), 110-129.
Krueger, A. B., & Lindahl, M. (2000). Education for growth: Why and for who?
Cambridge: National Bureau of Economic Research.
139
Lareau, A. (2002). Invisible inequality: Social class and childrearing in Black families
and White families. American Sociological Review , 67 (5), 747-776.
Lauen, D. L. (2007). Contextual explanations of school choice. Sociology of Education ,
80 (3), 179-209.
Ledwith, V. (2010, February). The influence of open enrollment on scholastic
achievement among public school students in Los Angeles. American Journal of
Education , 116 (2), pp. 243-262.
Levin, H. M. (2012). Some economic guidelines for design of a chrter school district.
Economics of Education Review (31), 331-343.
Marshall, M. N. (1996). Sampling for qualitative research. Family Practice (13), 522525.
Martinez, V. J., Goodwin, R. K., Kemerer, F., & Perna, L. (1995). The consequences of
school choice: who leaves and who stays in the inner city. Social Science
Quarterly , 76 (3), 485-501.
McMahon, W. W. (2004). The social and external benefits of education. In G. Johnes, &
J. Johnes (Eds.), International handbook of the economics of education (pp. 221259). Northampton, MA: Edward Elgar Publishing.
McNamara Horvat, E., Weininger, E. B., & Lareau, A. (2003). From social ties to social
capital: Class differences in the relations between schools and parent networks.
american Educational Research Journal , 40 (2), 319-351.
140
Menard, S. (2002). Applied logistic regression analysis. University of Colorado, Institute
of Behavioral Science. Thousand Oaks: Sage.
Miron, G., Evergreen, S., & Urschel, J. (2008). The impact of school choice reforms on
student achievement. Westen Michigan University, The Evaluation Center.
Boulder, CO: Education Public Policy Interest Center.
Morris, J. E. (1997). Voluntary desegregation in St. Louis, Missuri: Impact on
partnerships among schools, African-American Families, and communities. St.
Louis: Vanderbilt University.
Moustakas, C. (1994). Phenomenological research methods. Los Angeles, CA: Sage
Publications.
Muhammad, A. (2009). Transforming school culture: How to over come staff division.
Bloomington, IN: Solution Tree Press.
National Household Education Surveys Program. (2010). Trends in the Use of School
Choice: 1993 - 2010. US Department of Education.
Ogbu, J. U., & Simons, H. D. (1998). Voluntary and Involuntary Minorities: A CulturalEcological Theory of School Perfomrance with Some Implications for Education.
Anthropology & Education Quarterly , 29 (2), 155-188.
Orfield, G., Losen, D., Wald, J., & Swanson, C. B. (2004). Losing our future: How
minority youth are being left behind by the graduation rate crisis. The Civil
Rights Project at Harvard University. Cambridge: Harvard Education Publishing
Group.
141
Orfield, M., & Wallace, N. (2007). Expanding edcational opportunity through school and
housing choice. CURA Reporter , 37 (2), 19-26.
Pallant, J. (2007). SPSS Survival Maual: a step by step guide to data analysis using SPSS
for Windows (3rd Edition ed.). New york: Open university Press.
Pampel, F. C. (2000). Logistic Regression: A Primer. thousand Oaks, CA: Sage.
Peterson, P. E., Woessmann, L., Hanushek, E. A., & Lastra-Anadon, C. X. (2011).
Globally challenged: Are U.S. students ready to compete? Harvard university,
Harvard's Program on Education Policy and Governance. Cambridge: Harvard
University.
Public Policy Forum. (2002, July 8). Districts say convenience for parents, not
competition, is result of open enrollment. Research Bief , 90 (7), pp. 1-6.
Public Policy Forum. (2012, February). Significant growth in school choice: More
schools, more students, fewer limits on income eligibility. Reserch Brief , 100 (1),
pp. 1-12.
Ridenour, C., Lasley, II, T. J., & Bainbridge, W. L. (2001). The impact of emerging
market-based public policy on urban schools and a democrataic society.
Education and Urban Society , 34 (1), 66-83.
Schneider, B., Swanson, C. B., & Riegle-Crumb, C. (1998). Opportunities for learning:
Course sequences and positional advantages. Social Psychology of Education , 2,
25-53.
142
Schneider, M., Marschall, M., Teske, P., & Roch, C. (1998). School choice and culture
wars n the classroom: What different parents seek from education. Social Science
Quarterly , 79 (n), 489-501.
Smrekar, C., & Goldring, E. (1999). School choice in urban America. New York, Neew
York: Teachers College Press.
Stuart, M. (1993). Choosing a secondary school: Can parents' behaviour be described as
rational? Research.
Stucke, M. E. (2009, December 14). Auditing self interest. America , pp. 10-14.
Teske, P., & Schneider, M. (2001). What research can tell policy makers about school
choice. Journa of Policy Analysis & Management , 20 (4), 609-631.
The Civil Rights Project. (2010). Charter schools' political success is a civl rights failure.
The University of California, Los Angeles. Los Angeles: The University of
California.
Thompson, M. N., & Dahling, J. J. (2012). Perceived social status and learning
experiences in social cognitive career theory. Journal of Vocational Behavior
(80), 351-361.
Tooley, J. (1993). A Market-Led Aleternative for the curriculum: Breaking the Code.
London: Tufnell.
143
U.S. Department of Education. (2007). Giving parents options: Strategies for informing
parents and implementing public school school choice and supplemental
educational services under No Child Left Behind. Washington, D.C.: Office of
Innovation and Improvment.
United States Census Bureau. (2012). Metropolitan and micropolitan. Retrieved June 6,
2012, from http://www.census.gov/population/metro/data/metrodef.html
Wells, A. S. (1996). African-American students' view of school choice. In B. Fuller, R. F.
Elmore, & G. Orfield (Eds.), Who chooses? Who loses?: Culture, institutions, and
the unequal effects of school choice (pp. 25-49). New York, New York: Teachers
College Press.
Whitty, G., & Edwards, T. (1998). School Choice Policies in England and the United
States: An Exploration of Their Origins and Significance. Comparative Education
, 34 (2), 211-227.
Young, T. W., & Clinchy, E. (1992). Choice in public education. New york, New York:
Teachers college Press.