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SUMMER BRIDGE PROGRAMS: A QUANTITATIVE STUDY OF THE RELATIONSHIP BETWEEN PARTICIPATION AND INSTITUTIONAL INTEGRATION
USING TINTO’S STUDENT INTEGRATION MODEL AT A MID-SIZED, PUBLIC UNIVERSITY IN MASSACHUSETTS
A thesis presented by
Meaghan L. Arena
to The School of Education
In partial fulfillment of the requirements for the degree of Doctor of Education
in the field of
Education
College of Professional Studies Northeastern University Boston, Massachusetts
June 2013
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Dedication and Acknowledgements
As with any large undertaking, a number of people helped me through my educational
journey. First and foremost, I want to thank my family. My husband Mario’s continued support
and sympathetic ear helped me not only complete coursework while working full time, but also
to articulate my passions in the field of higher education. He helps me maintain balance in my
life and reminds me of what is important. I am forever indebted to my best friend and partner for
everything he’s given me over the days, weeks, months and years this journey has taken. There
will finally be another doctor in the family! I also want to thank Sophie for her continued support
of my writing and for remaining a constant presence in my life no matter how many drafts it
took.
Next, I would like to thank my critical friend, Michael Hoffman, who read my papers as
many times, if not more times, than I did. Finding a friend in a program with limited residency
requirements is difficult in itself, but finding one with the same writing style who will honestly
critique classwork is even rarer, and Mike’s insights, grammar corrections, and knowledge of
APA style saved me on more than one occasion.
Finally, I would like to thank the faculty at Northeastern, who pushed me to learn, think,
read, and write in a way I never knew possible. In particular, I’d like to thank my adviser, Dr.
Kirchoff, and second reader, Dr. Bennett, whose guidance has been invaluable throughout the
dissertation process. Throughout many iterations of this project, Dr. Kirchoff never wavered in
her assertion that indeed I could do this, and helped me to focus both my project and my
methodology while always making sure I felt comfortable with the process. I would not be here
today without the help of Drs. Kirchoff and Bennett.
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Abstract
With six-year degree completion rates for undergraduate students at a dismal 50% nationally
(Weddle-West & Bingham, 2010), many institutions of higher education strive to develop
programming to increase student retention rates. Summer bridge programs, an example of
commonly used retention programs, seek to increase retention rates by integrating students both
academically and socially into their institutions. These programs fit squarely into Tinto’s (1975)
Student Integration Model which states that one reason for student withdrawal is a lack of
institutional integration. This study seeks to determine if successful students, i.e. those who have
graduated or who are nearing graduation, feel more integrated than other at-risk students after
completion of a summer bridge experience at a mid-sized, public University in Massachusetts.
Through survey research, alum and students nearing graduation were asked about their
perceptions of integration using the Institutional Integration Scale and data were analyzed using
SPSS, commercially available statistical software. The Institutional Integration Scale, which is
broken into five subscales, showed a statistically significant level of integration between students
and alum who attended the bridge program and those who did not in only one subscale – the
academic and intellectual development subscale. Female students showed a greater significant
difference than did male students. Implications of these findings include the ability to modify
programming to build on identified programmatic strengths and the ability for higher education
administrators to more clearly understand the connection between Tinto’s (1975) Student
Integration Model and successfully retained students on campus.
Keywords: retention, Tinto, summer bridge program, institutional integration.
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Table of Contents
CHAPTER 1: INTRODUCTION ....................................................................................... 8
Overview ......................................................................................................................... 8
Statement of the Problem ................................................................................................ 9
Significance of the Problem .......................................................................................... 12
National Context ....................................................................................................... 12
Local Context. ........................................................................................................... 12
Personal Context. ...................................................................................................... 13
Theoretical Framework ................................................................................................. 14
Research Question ........................................................................................................ 18
Operationalizing the Dissertation ................................................................................. 18
Limitations & Assumptions .......................................................................................... 19
Delimitations ................................................................................................................. 20
Definition of Terms ...................................................................................................... 21
Summary ....................................................................................................................... 22
CHAPTER 2: LITERATURE REVIEW .......................................................................... 23
Relevant Literature ....................................................................................................... 23
Student Integration Model. ....................................................................................... 23
Retention Problems. .................................................................................................. 28
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Retention Strategies. ................................................................................................. 37
Human Development. ............................................................................................... 43
Gaps in the Literature................................................................................................ 46
Summary. .................................................................................................................. 48
CHAPTER 3: RESEARCH DESIGN ............................................................................... 49
Methodology ................................................................................................................. 49
Research Design ........................................................................................................... 50
Sampling Methodology & Target Population ............................................................... 51
Instrumentation ............................................................................................................. 54
Operationalizing the Instrument with the Framework .............................................. 54
Validity & Reliability ............................................................................................... 55
Role of the Researcher .................................................................................................. 57
Data Collection ............................................................................................................. 58
Data Management ......................................................................................................... 61
Data Analysis ................................................................................................................ 61
Protection of Human Subjects ...................................................................................... 63
Summary ....................................................................................................................... 63
CHAPTER 4: RESULTS .................................................................................................. 65
Context .......................................................................................................................... 65
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Descriptive Statistics ..................................................................................................... 70
Analysis ........................................................................................................................ 80
General Findings and Summary ................................................................................... 92
CHAPTER 5: CONCLUSIONS ....................................................................................... 94
Overview ....................................................................................................................... 94
Interpretation ................................................................................................................. 97
Implications .................................................................................................................. 99
Implications for Practice ........................................................................................... 99
Implications for Theory Advancement ................................................................... 101
Suggestions for Future Research ............................................................................ 102
Conclusion .................................................................................................................. 104
REFERENCES ............................................................................................................... 106
APPENDIX A – Pre-Contact Letter ............................................................................... 117
APPENDIX B – First Reminder Letter .......................................................................... 118
APPENDIX C – Second Reminder Letter ...................................................................... 119
APPENDIX D – Final Reminder Letter ......................................................................... 120
APPENDIX E – Informed Consent ................................................................................ 121
APPENDIX F – Pilot Survey Letter ............................................................................... 124
APPENDIX G – Pilot Survey Thank You ...................................................................... 125
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APPENDIX H – Survey Instrument ............................................................................... 126
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Chapter 1: Introduction
Overview
Recent studies show that a mere 50% of those who enroll in a four-year college or
university graduate within six years (Weddle-West & Bingham, 2010). Even more alarming are
national retention rates for at-risk students, including first-generation, low income students,
students with learning disabilities, and students who speak English as second language, who
often face additional barriers to degree attainment. According to Roach (2008), only 67% of
first-generation and low-income students enroll in a second year of college, compared to 85% of
students without these risk factors. Similarly, a 1996 study indicated that students from families
in the top income quartile completed bachelor’s degrees at a rate of 74% while those from
families in the lowest income quartile completed at a rate of only 5% (Thayer, 2000). These
students are less likely than their counterparts to focus solely on their collegiate experience, thus
potentially impacting their level of integration into the institution and, ultimately, their
graduation rates.
The reasons behind these rates are varied. According to a 2007 study, some faculty feel
that a significant number of incoming freshmen lack the academic preparedness necessary for
collegiate success (Michael, Dickson, Ryan, & Koefer, 2010). Academic preparedness is also
cited by Fincher (2010) as a significant factor in the retention of some students. Additionally,
institutional and social support for at-risk students is often lacking, making retention to
graduation even more difficult (Lundberg, McIntire & Creasman, 2008). These barriers result in
significant student drop out. Institutions of higher education often develop summer bridge
programs to combat these barriers to retention in order to increase graduation rates, particularly
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among first-generation, low-income, and other types of at-risk students including students who
speak English as a second language and students with developmental disabilities. However, as
institutions develop summer bridge programs, they often fail to evaluate the reasons behind their
success. This lack of research means that administrators are unable to modify and enhance
programming to better serve the population. Without a complete understanding of the reasons
behind bridge program success, institutions rely on anecdotal evidence pointing to the value of
bridge programming.
The following chapter will first describe the problem of low retention in greater depth
and discuss the significance of the problem both nationwide and for individual institutions in
order to provide a background for the development of summer bridge programming. The
theoretical framework used in the study, Tinto’s (1975) Student Integration Model, is then
discussed. The research question and hypothesis are then outlined, followed by a discussion of
the research design and population and how they are operationalized in the dissertation. Finally,
the limitations of the study are discussed and key terms are defined.
Statement of the Problem
Despite previous studies on graduation rates in higher education, the problem of low
completion rates persists in nearly every institution across America (Delmont, 2011; Roach,
2008; Thayer, 2000; Tinto, 1975; Weddle-West & Bingham, 2010). The problem, then, is how to
keep the students engaged on campus and how to ensure their academic success until they
graduate. Improving a student’s overall connection to the university, both academically and
socially, is one way to prevent their departure (Tinto, 1975). Summer bridge programs, often
available to students in the summer prior to freshmen year, are designed to provide extra
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academic support while introducing students to their peers, thus socially integrating the students
into the university (Strayhorn, 2011). Qualified candidates for these programs are typically at-
risk students, including first generation students, low-income students, students with disabilities,
and students speaking English as a second language.
Westfield State University offers such a program, known as the Urban Education
Program. The program is somewhat of a misnomer since residence in an urban area is not a
prerequisite for admission to the program. Rather, students interested in enrolling in the Urban
Education Program must apply separately when they submit their application for admission to
the University. The Urban Education Program, founded in 1968, has as its main goal the ability
to help at-risk first-generation students, low income students (defined as those eligible for
financial aid), students with learning disabilities, and students who speak English as a second
language to graduate from the institution by integrating them into the fabric of Westfield State
University both academically and socially. The program’s philosophy is one of inclusion on
campus, and seeks to turn incoming freshmen into leaders in their community by introducing
them to important academic areas and skills, social events, and on-campus resources. The Urban
Education Program hosts a summer bridge experience for admitted students in the summer prior
to their freshmen year.
The summer bridge program exposes students to resources available on campus, provides
study skills, socialization, and affords participants the opportunity to earn college credits during
the program by completing summer coursework as part of the bridge program experience. These
skills are in line with Tinto’s (1975) Student Integration Model. Admittance to the Urban
Education Program is selective and is based on recommendations and prospective student
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interviews. In 2012, more than 500 students inquired and 151 were accepted into the program.
Not all accepted students enroll at the University or elect the Urban Education Program, and
roughly 100 students participated in the bridge program in the summer of 2012. Although the
program received more than 500 inquiries, not all students completed their applications and were
often missing one or more components to the application, including letters of recommendation.
In the data collection phase of this study, institutional data mining further articulates enrollment
trends in the Urban Education Program. The bridge program itself is a 5-week experience in
which students live on campus during the week, attend scheduled classes, tutoring sessions, and
other events, and return home on the weekends. Evening social events are also held in the
residence halls during the bridge program. The bridge program is free to accepted students.
The purpose of this study is to explore the relationship between participation in a bridge
program and integration scores (Tinto, 1975) as measured by the Institutional Integration Scale
(French & Oakes, 2004) of at-risk students who have graduated from a mid-size public
university in Massachusetts. Specifically, the study surveys students who entered Westfield
State University as first-time freshmen between 2001 and 2006 and who are considered at-risk
students but whom have since successfully graduated, as well as current students on track to
graduate in May, 2013, to determine the extent to which enrollment in the program resulted in
variation in their perceptions of academic and social integration during their collegiate
experience. Although Tinto’s Student Integration Model has been studied in a number of
contexts (Pascarella & Terenzini, 1980; Swail, Redd, & Perna, 2003), it has not yet been
specifically applied to a summer bridge program in a comparative manner. Therefore, the results
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of this study are useful for higher education administrators as they consider how to enhance or
modify summer bridge programs as a tool to improve graduation rates.
Significance of the Problem
Nationally, retention represents a significant issue in higher education, and graduation
rates represent a common measure of retention. Retention is considered such a serious and
significant issue nationwide that conferences, resources and research are dedicated to this topic
alone (Tinto, 2006b). Indeed, even President Obama has challenged colleges and universities to
increase their retention rates in his 2020 College Completion Initiative and is urging states to
incentivize institutions through the use of performance-based funding and other measures (U.S.
Department of Education, 2011). Similarly, as a result of dismal completion rates, the United
States lags behind other countries in terms of an educated populace, ranking tenth in the number
of adults to have attained at least an associate’s degree (Weddle-West & Bingham, 2010).
Similarly, retention is a significant issue at Westfield State University as well,
particularly in programs like the Urban Education Program, which caters to first-generation
students, low-income students, students with disabilities, or students who speak English as a
second language, all of whom are often considered at-risk for withdrawal (Tinto, 1975).
According to Westfield State University’s website, westfield.ma.edu, the annual cost of
attendance for the 2012-2013 academic year ranges from $14,895 to $25,530 depending on a
student’s status as a Massachusetts resident and living options on campus. It is, therefore,
exceedingly important to the financial health of the institution to retain as many students as
possible. This study, therefore, helps Westfield State University gain insight into reasons that at-
risk students graduate from the University, despite the challenges they face as at-risk students.
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Additionally, Westfield State University now has a better understanding of the role of both
academic and social integration, as explored by Tinto (1975), in student retention, graduation,
and success.
Students face a financial impact when they withdraw before the completion of a degree as
well. According to The College Board (2010), in 2009 the median family income for those with a
high school diploma was $48,637 while those with a bachelor’s degree earned $99,707. This
income disparity represents a significant obstacle in some students’ ability to repay student loans.
The importance of retention in higher education cannot be overstated.
Having established the importance of retention to the landscape of higher education, it is
also important to understand the reasons students choose to remain at an institution. While
institutions often establish summer bridge programs in an attempt to retain at-risk students
(Strayhorn, 2011), the reasons these programs are successful are not well-documented. While
institutions can easily review their own graduation rates to determine if their summer bridge
programs are helping to retain students, they often do not understand the reasons behind these
data, making it impossible to enhance or modify the program, or replicate the results in other
types of programming. Understanding the reasons behind successful student retention helps
Westfield State University know what types of programming to implement in the future, and
demonstrates a need for a greater focus on academic achievement in the summer bridge
experience. This knowledge is, therefore, crucial to Westfield State University’s administrators
and program developers. While retention is a broad issue, the reasons that a bridge program is
successful for some students must be researched at the micro level in order to have a robust
understanding of the problem of retention and its solutions.
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Theoretical Framework
Over the past 40 years, retention research has both gained in popularity and shifted in
focus. Student attrition was once viewed as a psychological phenomenon in which students were
blamed for their lack of motivation or ability to persist to graduation (Tinto, 2006b). In 1970,
Spady began to focus on institutional responsibility for student attrition, shifting the onus from
students to institutions. Expanding on Spady’s (1970) work, Tinto (1975) developed his well-
known Student Integration Model, which was the first model of student attrition to address the
connection between academic and social integration and student retention.
The Student Integration Model, based on Durkheim’s 1897 theory of suicide, suggests
that students who are poorly integrated into the academic and social fabric of an institution are
more likely to withdraw than other students (Swail et al., 2003). More specifically, the Student
Integration Model considers formal and informal social and academic experiences in determining
a student’s level of integration at a particular institution (Swail et al., 2003). It is this level of
integration, according to Tinto (1975), which shapes a student’s commitment level, which
influences the students’ ability to continue their education until graduation, known as persistence
or retention (see Figure 1).
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Figure 1. Tinto’s Student Integration Model
Over time, Tinto has continued to research retention and refine his model. In 1988, Tinto
began to identify stages of student withdrawal and drop out and characterized the process as
involving three stages: separation, transition, and incorporation (Swail et al., 2003). During the
separation stage, a student leaves behind former habits, friends, family members, and ways of
life to become a college student (Swail et al., 2003). The transition stage, according to Swail et
al. (2003), is when students contend with the stresses related to the separation stage as well as the
fact that they are not yet fully integrated into the campus community. Finally, the incorporation
stage signifies integration into a new environment and acceptance as a member of a new
community (Swail et al., 2003). Students who drop out, according to Tinto, generally do so
because of a disconnection in one of the first two stages (Tinto, 1988). Therefore, the focus of
both retention research and retention programming is largely centered around the separation and
transition stages of student development.
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Similarly, in 1993, Tinto identified five specific factors shown to influence persistence,
including: student goals, commitments, institutional experiences, integration, and high school
outcome, also thought of as academic preparedness (Porchea, Allen, Robbins, & Phelps, 2010).
Tinto’s model of Student Integration includes psychosocial factors as well, although academic
preparedness is generally considered one of the strongest predictors of student persistence,
(Porchea et al., 2010).
Furthermore, in 2006, Tinto expanded on his Student Integration Model by addressing the
need for students to integrate academically and the role faculty play in this integration. Tinto
(2006a) outlined several conditions for student learning that are central to their integration and,
thus, persistence. First, according to Tinto (2006a), is the need for high expectations from
faculty. In order to promote student learning, faculty must provide clear and consistent
expectations that force students to study the given material. Knowledge and passion for a
particular subject breeds integration (Tinto, 2006a). Next, Tinto (2006a) contends that support is
an essential condition for learning. As students progress from the separation to transition stages,
they often need help and support from faculty, staff, and the curriculum (Tinto, 2006a).
Third, timely, accurate, and sensitive feedback on assignments and activities are another
condition of student learning (Tinto, 2006a). Students who understand their strengths and
weaknesses or who experience a sense of improvement in a particular area are also more likely to
integrate into an institution (Tinto, 2006a). Finally, according to Tinto (2006a), involvement is
paramount to integration and, thus, persistence. Students who are more involved in learning tend
to become more socially integrated as well, and also have a deeper level of intellectual
development, which also aids in integration and persistence (Tinto, 2006a). By identifying
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various student development stages and learning conditions, Tinto’s Student Integration Model
serves as an excellent framework for further research in the area of retention (Cabrera, Nora, &
Castaneda, 1993).
The past four decades have seen a rapid growth in retention research (Tinto, 1998).
Several educational researchers have used the Student Integration Model as the basis for the
development of their own retention theories, including notable researchers such as Cabrera, et al.
(1993), Bean (1982), Stage (1989), and Brower (1992). Yet, Tinto’s Student Integration Model,
now more than 35 years old, still stands as one of the preeminent and most accepted retention
models in the field. This theoretical lens provides insight into low completion rates amongst at-
risk students – first generation students, low-income students, students with disabilities, and
students speaking English as a second language. And so, while Universities generate data
directly correlating summer bridge participation and graduation rates, there’s little to no research
that ascertains this group’s perception of their level of student integration during their college
experience, to include a comparison between alum who participated in the summer bridge
program and at-risk students who did not participate. Thus, this dissertation provides a more
robust insight into the proposition around integration and academic success and the extent to
which summer bridge programs may be shaping that experience.
Additionally, the Student Integration Model provides a framework that is both
comprehensive and proven, and allows researchers to examine many facets of student
development and integration, academic preparedness, and the relationship between student and
institution. This, in turn, allows for the examination of specific institutional programming
against the backdrop of the model, resulting in further insight into student retention.
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Research Questions and Hypothesis
• What is the relationship between perceived levels of institutional integration (Tinto,
1975) for at-risk alum who enrolled as first time freshmen between 2001 and 2006 and
students in their last semester of coursework who participated in a summer bridge
program and those who did not, at a mid-sized, public university in Massachusetts?
o Hypothesis: There is a positive correlation between summer bridge program
participation and perceived levels of institutional integration.
Operationalizing the Dissertation
This quantitative study examines successful Westfield State University students and alum
to identify factors relevant to their success. Specifically, the study surveys Westfield State
University alum and current students in their last semester of study who completed the summer
bridge program offered through the Urban Education Program and at-risk alum and students in
their last semester of study who did not participate in the Urban Education Program. The survey,
based on Tinto’s (1975) Student Integration Model, is previously validated and assesses
students’ level of integration with five subscales: two academic integration scales, two social
integration scales, and an overall integration scale.
By using a previously validated survey relating to Tinto’s (1975) Student Integration
Model, a comparison of integration levels between the students and alum who participated in the
Urban Education Program and those who did not can be made. Because respondents have either
already graduated from Westfield State University or are in their last semester of study, the study
population represents students retained by the University, which is also in conjunction with
Tinto’s (1975) Student Integration Model.
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A multivariate analysis of variance was used to determine if the average integration
scores on the five integration subscales were significantly different between the population of
students and alum who participated in the Urban Education Program and those who did not.
These results were then used to make recommendations for the Urban Education Program in
terms of areas of continued focus or new focus, and to determine significant factors in the
successful retention of students at Westfield State University.
Limitations & Assumptions
Multiple limitations should be noted for this study. First, because some alum were asked
to recall feelings and attitudes from as many as 12 years ago, these respondents may exhibit
recall bias. Overall feelings and attitudes may have changed in this period of time due to
employment or lack thereof, admission into graduate programming, or other factors. The elapsed
time between freshmen year and pre-freshmen experiences like the Urban Education Program
and receipt of the study survey should be considered another limitation of the study.
Additionally, because this study is relational and not experimental, limited conclusions
can be drawn. Understanding the levels of integration felt by students who have successfully
been retained by Westfield State University tells nothing about the integration levels of those
who withdrew, and nothing about the level of integration these particular at-risk students would
have felt had they not participated in the summer bridge experience. Therefore, the overall effect
of the Urban Education Program cannot be measured by this study, and this should be considered
a limitation as well.
Similarly, several assumptions were made throughout the research study. First, it is
assumed that Tinto’s (1975) Student Integration Model, the theoretical framework chosen for the
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study, remains relevant and is applicable to the study population and the Urban Education
Program. Although the literature suggests that the Student Integration Model provides a
foundation for research across many types of programming and institutions, it is nonetheless
assumed that students who graduate from the Urban Education Program do so because of
integration into the institution gained directly from the Urban Education Program. However,
there are other reasons that these students may be successful having nothing to do with
integration.
Further, it is assumed that the study population is an appropriate sample given the
relatively short period of time between their participation in the Urban Education Program and
this research study. However, this assumption may prove incorrect given that the Urban
Education Program was originally a 6-week program which has recently transformed into a 5-
week program. Perhaps students who attended the 6-week program have differing experiences
and different perceptions of integration. However, for convenience, the most recent cohorts of
students were sampled.
Delimitations
In addition to limitations and assumptions, several delimitations of the study should be
noted. First, because the population of survey respondents was drawn exclusively from one
institution, a comparison of integration levels between institutions and programs is not possible.
Additionally, this limited sampling strategy does not account for other factors on campus,
available to all students, which may impact integration levels at Westfield State University but
which may differ at other institutions. The survey sample and location should be considered a
delimitation of this study.
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Additionally, the survey instrument, the Institutional Integration Scale, should also be
considered a delimitation of the study. Because the survey instrument was created and previously
validated by another researcher, it is not specific to the Urban Education Program and to this
research study and the subscales may not all be appropriate and valid for the study population.
Therefore, the survey instrument chosen by the researcher should also be considered a
delimitation of the study.
Definition of Terms
At-risk students: For the purpose of this study, at-risk students shall refer to students who meet at
least one of the following criteria: first generation student, low-income student, student with
documented learning disabilities, student who speaks English as a second language.
At-risk summer bridge program alum: At-risk students who participated in the Urban Education
summer bridge program at Westfield State University and who subsequently graduated from the
University.
At-risk University alum: At-risk students who attended Westfield State University and
subsequently graduated, but who did not attend the Urban Education summer bridge program.
Institutional Integration: An overall measure of integration at a College or University, typically
consisting of both academic and social integration combined into one general term.
Low-income students: The Urban Education program defines low-income students as those
receiving financial aid. For the purpose of this study, that definition will be used throughout.
Summer bridge program qualified applicant: Students who meet the criteria of an at-risk student,
who apply to the Urban Education Program, are accepted into the Urban Education Program
and/or who participate in the summer bridge program.
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Summary
Given the importance of retention in a national, local, and personal context, a study such
as this that compares alum who participated in a summer bridge program with at-risk alum who
did not participate in a bridge program was warranted. The study is important to the field of
higher education because it illuminates the reasons students choose to persist to graduation at
Westfield State University, which in turn, allows administrators to make more informed
decisions regarding retention programming at the University. By comparing the perceived levels
of integration of both groups, Tinto’s (1975) Student Integration Model is operationalized in
Westfield State University’s Urban Education Program. The next chapter will explore the
guiding literature of this study in order to further provide context to the issue of retention and
this research study.
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Chapter 2: Literature Review
In order to understand and apply Tinto’s (1975) Student Integration Model, an extensive
review of the literature was required. This chapter first discusses the Student Integration Model
posited by Tinto as the seminal author in the field of retention research as well as other
researchers who have used Tinto’s work as a foundation and modified the Student Integration
Model for their own purposes. The chapter then examines research directly related to retention
problems and the aforementioned research question specifically. Research on retention strategies
is also discussed, as is human development as it relates to this study, and gaps in the literature are
identified.
Relevant Literature
The Student Integration Model. Tinto himself has conducted comprehensive research
into retention over the past four decades, and a thorough review of his work, its evolution,
limitations, and critiques was an essential starting point. A cursory look at Tinto’s own research
and writing provided at least six seminal articles on the topic of retention and the Student
Integration Model. After initially proposing his Student Integration Model in 1975, Tinto
continued his research into retention and added to the body of research in the field by branching
into specific retention strategies including learning communities (Tinto, 1998) and stages of
withdrawal (Tinto, 1988). Furthermore, Tinto (2006a) described lessons learned, ways to
restructure the learning environment, and conditions necessary for learning and persistence.
Finally, after further research, Tinto himself recognized the limitations of the Student Integration
Model and offered an honest critique of his framework (Tinto, 1982). These limitations,
according to Tinto (1982), included the Student Integration Model’s inability to distinguish
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between a student who withdraws from higher education entirely and one who simply transfers
to another institution, a lack of attention to the financial impact of attrition on both student and
institution, and a lack of attention to race, gender, and social status.
Tinto was not the only author to further analyze, critique, and add to the Student
Integration Model, however. By applying Tinto’s (1975) model to various groups, other authors
have contributed to the body of knowledge surrounding retention. For example, Lee, Donlan and
Brown (2011) elaborated on Tinto’s (1975) model by applying it to American Indians and
Alaskan natives in predominantly White institutions. Further, Longwell-Grice and Longwell-
Grice (2008) explored how well Tinto’s (1975) model fits first-generation students, and Janes
(1997) applied the Student Integration Model to African American nursing students.
Understanding these and other express applications of Tinto’s (1975) theory provided a robust
background with which to begin further research.
Similarly, Meyer, Bruwelheide, and Poulin (2009), relying on Tinto’s (1975) model of
student retention, surveyed students in an online library media certification program in an
attempt to discover the reasons for their retention. Because Tinto’s (1975) model was the
foundation for the study, the authors focused on social and academic integration, which are also
the cornerstones of summer bridge programs. Understanding the reasons behind the success of
specific retention initiatives allowed for a comparison between those programs and summer
bridge programs, again helping to determine the value of bridge programming.
Additionally, other researchers, including Cabrera, et al. (1993), Bean (1982), Stage
(1989), and Brower (1992), have modified Tinto’s (1975) theory based on their own research.
Understanding the connections between the models used and ultimately adapted by these
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researchers provided a comprehensive view of the uses and limitations of Tinto’s (1975) model.
While Tinto’s (1975) Student Integration Model stressed academic, social and overall integration
as primary factors influencing student attrition, Bean’s (1982) Student Attrition Model focused
mainly on external factors like family approval, student attitudes, and a student’s intent to
graduate as main contributing factors in retention. Both Tinto (1975) and Bean (1982) agreed
that institutional fit was an important factor in student retention, but Bean’s (1982) Student
Attrition Model brought a different perspective on factors influencing student retention.
Likewise, Cabrera et al. (1993) sought to combine the Student Integration Model and the
Student Attrition Model in order to achieve a single model of retention that accounted for both
internal and external variables in attrition. The unnamed but complex model derived by Cabrera
et al. (1993) pointed out that the Student Integration Model was indeed underestimating the
external factors associated with student retention including the students’ intent to graduate and
the overall approval from family members. Failing to account for this factor should be
considered a weakness of Tinto’s (1975) Student Integration Model. However, the model
studied by Cabrera et al. (1993) also noted that Bean’s (1982) Student Attrition Model
underestimated the role of social integration and goal commitment, particularly as they relate to
external factors like support from family. In this way, Tinto’s (1975) Student Integration Model
more accurately captured some factors of student persistence. Therefore, although Cabrera et al.
(1993) were able to merge two seemingly complementary retention theories, the final model
contains multiple weaknesses and was, therefore, not as pure as either of the original models of
attrition.
26
Additionally, Stage (1989) used Tinto’s (1975) Student Integration Model as a backdrop
for a modified model, acknowledging that Tinto’s (1975) model explained the general process of
retention and attrition but failed to address the notion that some factors within the model were
more important to individual students than other factors. By introducing a factor known as
motivational orientation, Stage (1989) conducted a “Tinto-based” (p. 385) analysis which studied
students in three types of motivational orientations with Tinto’s (1975) Student Integration
Model as the overall framework of the study. Stage’s (1989) model remains useful for
researchers seeking additional information on the motivational factors of students at their
institutions, but narrows the focus of the Student Integration Model significantly.
Similarly, Brower (1992) took the Student Integration Model a step further and
contended that the study of retention actually consisted of two steps: static integration and life
tasks. Static integration, according to Brower (1992), is measured by the Student Integration
Model and consists of unchangeable factors like whether a student’s goals match with those of
their institution. Brower (1992) asserted, however, that retention has a second phase. By
studying life tasks, or student activities over a period of time, it was possible to determine if
certain activities helped improve students’ overall level of institutional integration (Brower,
1992). In other words, Brower (1992) argued that integration was not a one-time measurement
but rather something that both student and institution could impact over a period of time.
Building on Tinto’s (1975) Student Integration Model in this way is useful for practitioners
seeking to develop interventions to improve levels of institutional integration as students advance
through their educational experience.
27
Awareness of criticisms of Tinto’s (1975) model by other researchers in the field
enhanced the credibility of the model and its uses. Liu (2002), for example, criticized Tinto’s
methodology and asserted that each question Tinto helped to answer lead only to another
question. Liu (2002) further noted that Tinto failed to address key issues with his research
including whether integration is a process or an outcome and whether a student must integrate
into the institution as a whole or into one group, like a fraternity or sorority. These issues may
call into question components of Tinto’s work and were, therefore, important to consider in the
review of the literature.
Figure 2 shows selected key authors who have contributed to the literature and research
regarding Tinto’s (1975) Student Integration Model.
Framework authors
Terenzini & Pascarella (1978) (+ others)Focuses on attrition, pre-college characteristics, freshmen year experiences, and interactions between demographic factors and perceptions
Swail, Redd & Perna (2003)Overview of Tinto's SIM. Stages of withdrawal discussed. Lengthy descriptions of factors (academic preparedness, commitment to goals, etc.)
Spady (1970)Shifts onus of withdrawal from student to institution. Tinto's SIM expands on this notion.
Bean (1982)Developed Student Attrition Model, taking external factors into account, like family support
Cabrera, Nora & Castanada (1993)Combines Tinto & Bean. Model very complex and highlights weaknesses of both. Rarely used.
Stage (1989)Says some factors in SIM more important than others to particular students. Introduces motivation and narrows the SIM significantly
Brower (1992)Integration not static, can be changed over time. Is a longitudinal model that studies how integration changes by student
Liu (2002)Critical of Tinto. Is integration a process or an outcome? Integrate into entire university or subgroup like sorority?
Lee, Donlan and Brown (2011)Applies SIM to American Indians and Alaskan Natives in predominantly White institutions
Longwell-Grice and Longwell-Grice (2008) Applies SIM to first-gen onlyJanes (1997) Applies SIM to African American nursing studentsMeyer, Bruwelheide, and Poulin (2009) Applies SIM to online library certification program
Porchea, Allen, Robbins & Phelps, (2010)Psychosocial factors in SIM: personality, biographical data, motivation, self-regulation skills. Studied Community College students
Figure 2. Selected Key Authors Contributing to the Literature on the Student Integration Model.
28
Retention Problems. Although Tinto himself has contributed a great deal to the study of
retention, a holistic review of retention programming from other researchers was important for a
well-rounded view of the subject. To address the research question, which sought to determine
the relationship between summer bridge program participation and perceived institutional
integration as compared to at-risk students who did not participate in the bridge program, it was
essential to understand which groups are least likely to persist at the undergraduate level and
why. A review of the literature noted that students who fall into one of the aforementioned at-
risk categories have a higher chance of withdrawal from an institution. First-generation students,
for example, often face challenges their peers do not, including different financial and time
constraints, inability to cope with stress, and lower levels of academic preparedness (Ishitani,
2006; Mehta, Newbold, & O’Rourke, 2011; Thayer, 2000). First-generation student status and
receipt of financial aid is, therefore, often an indicator of students deemed to be at-risk.
Similarly, many researchers have identified specific characteristics of students deemed at
risk for withdrawal from institutions of higher education. Features such as underachievement at
the high school level (Balduf, 2009) which may be caused by factors such as documented
disabilities or English spoken as a second language, for example, as well as low levels of
engagement on campus (Shinde, 2010), and a minimal enrollment duration (Ryan & Glenn,
2004; Terenzini & Pascarella, 1978) make the likelihood of student attrition greater. A closer
look at the factors affecting persistence at the undergraduate level provided a basis to begin
research to answer the research question (Figure 3).
29
Retention Problems
Balduf (2009)Underachievement in high school leads to withdrawal. Not academically prepared
Shinde (2010) Low level of campus engagement leads to withdrawl
Ryan & Glenn (2004)Minimal enrollment duration leads to withdrawal (more likely to withdraw in first year)
Figure 3. Key Researchers Studying Retention Problems.
Although many factors were known to affect college student retention (Balduf, 2009;
Bean, 1982; Brower, 1992; Spady, 1970; Tinto, 1975), perhaps none was more salient to colleges
and universities than the role of financial aid on student persistence to graduation, particularly
since financial aid is typically received by first-generation students and other students deemed at-
risk for withdrawal. Research in this area was incongruent, however, particularly as it related to
financial aid awards for low-income and first-generation college students (Alon, 2007; Chen &
St. John, 2011; Mendoza, Mendez, & Malcolm, 2009).
Originally created in 1965 through the Higher Education Act, Guaranteed Student Loans,
now known as Stafford Loans, were intended to increase access to higher education for low and
middle-income students who otherwise could not afford to attend (Mendoza et al., 2009; Wessel,
Bell, McPherson, Costello, & Jones, 2006). Unfortunately, although federal loans help make
higher education more affordable, it is unknown whether financial aid alone significantly
impacts a student’s likelihood of persistence to graduation. In a 2007 study, Alon noted that for
each $1,000 in additional subsidized loan money awarded, the likelihood of first-year retention
increased by 4.3% (p. 299). Similarly, Alon (2007) noted that Hispanic and Black students who
received no financial aid were substantially less likely to persist to graduation than were their
White counterparts. Mendoza et al. (2009) also reported a connection between financial aid and
30
retention at the community college level. In the same study, however, Mendoza et al. (2009)
also pointed out that this connection doesn’t necessarily exist with other demographics of
students. Similarly, Chen and St. John (2011) pointed to mixed results as well, and commented
that in a national study, financial aid was linked to retention in 48 states, but that in a study in
Indiana, no statistically significant link was found between financial aid and student retention.
The literature, therefore, was rife with contradictions regarding the direct role of financial aid in
student retention (Alon, 2007; Chen & St. John, 2011; Mendoza et al., 2009) but it was clear that
receipt of financial aid and financial need remains a risk-factor for student attrition.
Despite incongruous findings, indirect linkages and important conclusions regarding
financial aid and student retention were possible when certain demographics of students and
types of financial aid were studied. For example, with two-thirds of undergraduate students
receiving some form of financial aid (Diaz-Strong, Gomez, Luna-Duarte, & Meiners, 2011;
Novak & McKinney, 2011) amounting to approximately $155 billion dollars annually (Goldrick-
Rab, Harris, Benson, & Kelchen, 2011b), the issue of student retention is more important than
ever. Unfortunately, however, retention rates in the U.S. have continued to decline (Advisory
Committee on Student Financial Assistance, 2010) resulting in nearly $1 billion in taxpayer
money spent on financial aid to students who dropped out before their second year (Schneider &
Yin, 2011). This staggering figure showed the importance of ultimately improving retention
rates, particularly for financial aid recipients.
Although the direct connection between financial aid and retention was inconsistent,
researchers have noted a clear link between financial aid and other factors that place students at-
risk for withdrawal. Haynes (2008) noted that 34% of incoming undergraduate students were
31
first-generation, low-income students, but barely 40% of these students completed a bachelor’s
degree within eight years of initial enrollment (Goldrick-Rab et al., 2011a). By comparison,
more than 75% of wealthy students completed bachelor’s degrees within eight years (Goldrick-
Rab et al., 2011a). Therefore, a connection existed between personal finances and income and
overall student retention.
Similarly, Chen and St. John (2011) agreed that personal finances affect student attrition
and note that traditionally, students with a lower socioeconomic status have consistently lower
rates of retention than their counterparts with a higher socioeconomic status. Specifically, high
socioeconomic students have a 55% greater chance of persisting to graduation than do their low
socioeconomic peers (Chen & St. John, 2011, p. 652). This trend was echoed by the Advisory
Committee on Student Financial Assistance (2010) who pointed out that in 2003, only 63% of
low and moderate income students who enrolled in a 2-year institution persisted or graduated
after 3 years, while this rate is 72% for high income students. Wessel et al. (2006) emphasized
this point by observing that students from low-income families were eight times less likely to
persist to graduation than other students.
Perhaps as a result of these dismal completion rates, students from low-income families
are increasingly less likely to enroll in institutions of higher education, regardless of their
academic capabilities. In fact, as of 2002, approximately 50% of academically qualified low-
income students chose not to enroll in a four-year institution due to cost (Advisory Committee on
Student Financial Assistance, 2010). This percentage translated to more than 4.4 million
qualified students choosing not to enroll in higher education by 2010 (Herzog, 2008). St. John et
al. (2005) noted, however, that low-income students who choose an institution of higher
32
education based primarily on affordability were more likely to persist to graduation than those
that do not consider cost when choosing an institution.
The Advisory Committee on Student Financial Assistance (2010) contended, however,
that although the percentage of academically qualified low-income students who choose not to
enroll in higher education is staggering, it may be due in part to misinformation regarding tuition
and available financial aid. In fact, students from low-income families were more likely to
overestimate the cost of tuition and underestimate need-based grant amounts than were their
wealthier counterparts (Advisory Committee on Student Financial Assistance, 2010). St. John et
al. (2005) agreed and noted that perceptions of financial barriers can prevent students from
enrolling in institutions of higher education just as frequently as actual financial barriers.
Compounding the issue of financial barriers in higher education, the Advisory Committee
on Student Financial Assistance (2010) asserted that between 1993 and 2008, the net price for
low-income students at two-year institutions of higher education surged almost $1,600 and
increased more than $3,000 at four-year institutions. This has resulted in lower degree
attainment for low-income students who now attain bachelor’s degrees at a rate of just 31%
compared to 38% in 1993 (Advisory Committee on Student Financial Assistance, 2010).
Solving this problem is not as simple as providing additional grant funding, however. Haynes
(2008) contended that providing grant funds to cover the full cost of tuition does not generally
result in higher retention rates. Therefore, financial aid programs alone are not sufficient to
impact retention. Rather, robust student programming is required to assist at-risk students with
their education.
33
Unfortunately, it is not just low income students who are impacted by the cost of higher
education. First generation students and undocumented students also face barriers to degree
attainment due to financial complications. Wessel et al. (2006) observed that the number of high
school graduates was expected to increase 11% between 2000 and 2012. Many of these students
were first-generation students who therefore did not have parents who could assist and advise on
college financial matters from experience (Wessel et al., 2006). This was likely to mean that a
portion of these first-generation college students would not enroll in institutions of higher
education immediately upon high school graduation (Advisory Committee on Student Financial
Assistance, 2010).
Wessel et al. (2006) also pointed out that an increasing number of high school graduates
were immigrant students, speaking English as a second language, who may not have the funds to
support higher education, nor the knowledge and experience of American higher education to
persist to graduation. Indeed, Diaz-Strong et al. (2011) contended that many graduates were
undocumented immigrants. More than 65,000 undocumented immigrants graduate from high
school in the United States each year and yet estimates of the number who enroll in higher
education range from 7,000 to 13,000 annually (Diaz-Strong et al., 2011). If this trend
continues, the ability of the United States to compete on a global scale will be greatly diminished
due to an increasingly unskilled workforce (Diaz-Strong et al., 2011). Therefore, improving
retention rates for all groups of students is critical to building an educated workforce and a stable
economy.
While it was clear that finances have an impact on higher education and degree
attainment, it was important to note that financial aid can provide relief to certain populations
34
under specific circumstances. Many studies, for example, linked financial aid to retention and
noted that as aid increases, so too does retention (Bettinger, 2004; DuBrock, 2000; Goldrick-Rab
et al., 2011a; Gross, 2011; Mendoza et al., 2009; Murdock, Nix-Mayer, & Tsui, 1995; Novak &
McKinney, 2011). Nasser, Nauffal, and Romanowski (2009) noted that this holds true in
Lebanon as well where research has demonstrated a link between financial assistance and student
success in institutions of higher education. Glocker (2011) observed the same trend in Germany
also. In fact, Goldrick-Rab et al. (2011b) contended that every $1,000 in additional financial aid
represented a 3.6% increase in yearly retention in American colleges and universities. A similar
study by Alon (2007) showed an increase in yearly retention between 1.4% and 4.3% with each
$1,000 in additional financial aid. Furthermore, financial aid enabled students to focus on
academics once enrolled, encouraged enrollment, and increased college preparation (Gross,
2011). However, different types of aid applied in different ways and at different times have
varying impacts on retention rates.
For example, students working on campus through a work study program were more
likely to return to school each year, according to DuBrock (2000). Alon (2007) agreed, and
noted that work study programs have other benefits as well, including limiting the number of
hours a student can work so that time remains for academic coursework and studying. Students
participating in work study were often assigned to different departments each year, resulting in a
familiarity with many departments and administrators, thus integrating them into the fabric of the
institution. This familiarity, according to Alon (2007), can help students persist as well because
they are integrated into the institution through their work in many departments.
35
Conversely, financial aid can also be detrimental to student retention under certain
circumstances. To qualify for any type of financial aid, students and their families must first
complete the Free Application for Federal Student Aid (FAFSA), which many families find both
complex and overwhelming (Mendoza et al., 2009). The process of applying for financial aid
alone is often a deterrent, which can result in no aid awarded to otherwise qualified students who
simply did not apply for it (Mendoza et al., 2009). Mendoza et al. (2009) noted that this is
especially true for first-generation students whose families are unfamiliar with the process.
Novak and McKinney (2011) agreed and noted that millions of students each year were eligible
for financial aid but did not apply for it. Failure to apply for aid ultimately resulted in lower
retention for students, particularly first-year students (Novak & McKinney, 2011). In fact, low-
income students who applied for financial aid have a 122% greater chance of persisting into their
second semester than their low-income peers who did not apply (Novak & McKinney, 2011).
This does not mean, however, that there is a clear connection between receiving financial
aid and retention, nor that there is a clear disconnection. Wessel et al. (2006) noted that financial
aid recipients were more likely to disqualify, or drop below a required minimum GPA, than their
counterparts who do not use financial aid. Similarly, students who receive financial aid were
consistently retained at a lower rate than students who did not (Wessel et al., 2006). The
Advisory Committee on Student Financial Assistance (2010) argued that this is due to the fact
that financial aid awards were not sufficient to ensure either access to education or adequate
retention, particularly for low and middle income students. Miller, Binder, Harris and Krause
(2011) observed that Pell grants, which are a major source of financial aid for lower income
students, cover approximately one-third of tuition at most. Herzog (2008) added, however, that
36
financial aid alone was not enough to impact retention even if aid amounts were greater. Instead,
ample financial aid awards must be coupled with academic support in order to increase student
retention (Herzog, 2008). The Advisory Committee on Student Financial Assistance (2010) took
this notion a step further and advocated for a three-pronged approach to improving retention
rates. This three-pronged approach included increased financial aid awards to promote access,
incrementally increased aid throughout the college experience to improve yearly retention, and
an expanded focus on academic preparation (Advisory Committee on Student Financial
Assistance, 2010). It was apparent, therefore, that retention of first-generation, low income, and
students who speak English as a second language requires a robust on-campus experience and
that there is no quick fix for low retention rates.
Further, Bettinger (2004) contended that as grant funds increase retention decreases.
Programs like the Pell grant program provide money that a student is not required to repay upon
graduation, and as such, the student has not made an investment in their education (Bettinger,
2004). This may mean that students feel less connected to the educational process and less
motivated to persist to graduation since they do not feel a financial impact. Other types of
financial aid have historically had a negative impact on retention as well. Student loans and the
federal work study program which provides students with on-campus jobs were also correlated to
student withdrawal (Alon, 2007; Haynes, 2008; Murdock et al., 1995). Haynes (2008) observed
that students who received financial aid in the form of work study or student loans were less
likely to persist to degree completion. Similarly, Murdock et al. (1995) contended that White
males with work study awards were substantially less likely to persist due in part to the fact that
an on-campus job took time away from academic pursuits, resulting in declining grades and
37
eventually withdrawal. Alon (2007) agreed with this contention and further noted that work
study students can feel isolated from their peers because they need to work while classmates are
participating in academic or social activities. Figure 4 outlines key authors who have contributed
to the body of retention literature through the study of financial aid and its impact on retention
and student persistence.
Financial Aid
Alon (2007)for each $1,000 in additional subsidized loan money awarded, the likelihood of first-year retention increased by 4.3%
Mendoza, Mendez, & Malcolm (2009)Financial aid helps community college retention but not necessarily other populations
Chen and St. John (2011) Contradictions regarding financial aid effectiveness in retention everywhere. 48 states show some retention, Indiana shows none.
Schneider & Yin (2011)$1 billion in taxpayer money spent on financial aid to students who dropped out before their second year
Haynes (2008)
34% of incoming undergraduate students were first-generation, low-income students, but barely 40% of these students completed a bachelor’s degree within eight years of initial enrollment
Haynes (2008)Grants don't necessarily help retain students who don't feel financial responsible for their education
Goldrick-Rab, Harris, Benson, & Kelchen (2011) 75% of wealthy students complete in 8 yearsNasser, Nauffal, and Romanowski (2009) in Lebanon, as financial aid increases, so does retentionGlocker (2011) in Germany, as financial aid increases, so does retentionDuBrock (2000). Work study helps retainHaynes (2008) Work study does not help retain
Figure 4. Key Researchers Contributing to the Body of Retention Literature Through Financial
Aid Research.
Retention Strategies. Addressing the research question also requires extensive
knowledge of retention programs that are successful, as well as those that are not. A wealth of
research concerning proven retention strategies exists and must be reviewed in order to
understand summer bridge programs. Breihan (2007), for example, contends that retention
strategies must consist of three areas: teaching techniques, relationships outside of the classroom,
and recognition of the importance of support structures (p. 95). Reviewing summer bridge
38
programming in light of these three areas allows for a cursory look at whether bridge
programming is considered to impact graduation rates.
Likewise, the literature is rife with examples of retention programming aimed at students
during their first-year of higher education (Belcher, 2010; Braxton, Hirschy, & McClendon,
2004; Wolfe & Kay, 2011). In fact, Wolfe and Kay (2011) also discuss the perceived impact of
first-year programming for students. Programming extending throughout the entire first year of
the college experience most often aims at increasing the level of student integration (Belcher,
2010), which is in line with Tinto’s (1975) Student Integration Model and the research question.
Even though this type of programming has a further reach than summer bridge programming, the
underlying theory remains constant and is, therefore, useful to review to answer the research
question.
However, answering the question will ultimately require a comprehensive understanding
of the foundations, limitations, and successes of summer bridge programs directly. An extensive
review of the literature on summer bridge programs provides a wealth of background
information on their benefits. For example, Michael, Dickson, Ryan, and Koefer (2010) provide
a series of best practices for successful summer programming for incoming freshmen, and
Maggio, White, Molstad, and Kher (2005) expertly outline the impact of summer programming
on student achievement. Using Tinto’s (1975) Student Integration Model, Maggio et al. (2005)
examine several variables in summer bridge programming in an attempt to determine whether
bridge programming plays a significant role in student achievement, and thus, in retention.
Examining studies with research questions similar to the proposed research question is important
for consistency and to gain a complete understanding of retention programming.
39
Fortunately, a plethora of retention and summer bridge program research exists in the
field. Some research focuses on specific groups of students, such as low-income or
underrepresented students (Ackermann, 1991; Keim, McDermott, & Gerard, 2010; Murphy,
Gaughan, Hume, & Moore, 2010; Payne & Dusenbury, 2007; Strayhorn, 2011), while others
more generally evaluate the effect of bridge programming on academic preparedness (Garcia &
Paz, 2009; McCurrie, 2009). Understanding previous research in this area helps to understand
how faculty and students perceive summer bridge programming. This understanding is necessary
to draw conclusions about whether Westfield State University’s Urban Education alum perceive
a higher level of integration than at-risk alum who did not participate in the program. By
reviewing the literature on both retention and summer bridge programming, the application of
Tinto’s (1975) Student Integration Model to Westfield State University’s summer bridge
program follows naturally. Similarly, the stated research question adds to the breadth of
knowledge in this field by directly applying the Student Integration Model to a summer bridge
program to compare perceptions bridge program participants with other University students.
Strayhorn (2011), for example, focused his research on summer bridge programs, which
he defined as programs designed to bridge high school coursework with the rigors of collegiate
work in an intensive summer program. A web-based survey conducted by Strayhorn (2011)
asked 55 low-income, freshmen students of color at a predominantly White institution in the
southeast about their attitudes and behaviors before the summer program and after. Strayhorn
(2011) believed that low-income students of color are likely to benefit from a summer program
that enhances their academic and social skills. Indeed, after analyzing the data, he concluded
that students participating in a summer bridge program showed improved academic skills
40
(Strayhorn, 2011). Other positive behaviors including increased self-esteem and positive beliefs
about one’s abilities also resulted (Strayhorn, 2011).
Similarly, Stolle-McAllister (2011) studied the University of Maryland - Baltimore
County’s famous Meyerhoff Summer Bridge Program in order to determine the reason for its
apparent success. Although Stolle-McAllister (2011) used Bordieu’s social capital theory as a
framework for the study, it is nonetheless an applicable comparison to Westfield State
University’s Urban Education Program. Bordieu’s social capital theory states that students with
parents who attended college have more social capital and ability to understand collegiate
structures because their parents have prepared them for both the social and academic aspects of
higher education (Stolle-McAllister, 2011). Tinto’s (1975) Student Integration Model notes that
a risk factor for withdrawal is a student’s status as a first generation college student, and
therefore is aimed at the same population. Stolle-McAllister (2011) ultimately discovered that
the Meyerhoff Summer Bridge Program helped students academically, socially, and
professionally, since professional mentorship is a hallmark of the program.
Also in 2011, Stolle-McAllister partnered with Sto. Domingo and Carrillo to further
study the Meyerhoff Summer Bridge Program. Using Tinto’s (1975) Student Integration Model
as a framework, the researchers conducted a series of focus groups to better understand student
perceptions of the program and to learn what factors contributed most to retention (Stolle-
McAllister et al., 2011). The researchers ultimately discovered, based on trends in the data, that
there were five key components that made the Meyerhoff students more likely to persist:
financial support, the summer bridge program itself, formation of a Meyerhoff identity,
belonging to the Meyerhoff family, and the development of networks (Stolle-McAllister et al.,
41
2011). Several of these factors are present in other summer bridge programs as well, including
the Urban Education Program at Westfield State University. The development of identity and
sense of belonging as well as the formations of networks noted in the Meyerhoff Summer Bridge
Program are all facets of academic, social, and institutional integration, which are the goals of
the Urban Education Program. The findings of Stolle-McAllister et al. (2011) highlight the
effect of summer bridge programming and are important to consider when contemplating the
Urban Education Program.
Additionally, Keim et al. (2010) studied a summer bridge program at a community
college in Arizona in order to determine if the program improved Hispanic student retention at
the institution. The findings were similar to Stolle-McAllister’s (2011) in that the program was
determined to improve retention for Hispanic students. Unlike the Meyerhoff program, however,
the community college summer bridge program studied by Keim et al. (2010) assisted students
by instilling a sense of confidence in them. Students reported a greater ability to ask for help,
speak up in class, and felt a sense of belonging since they were able to relate to the presenters
and instructors in the summer bridge program. Although integration was hinted at in this study,
the major contributions of this summer bridge program were increased levels of academic
preparedness and an improved self-esteem.
Likewise, Murphy et al. (2010) studied a summer bridge program at Georgia Tech in
order to determine if the program assisted underrepresented minority students to complete their
education. Using Tinto’s (1975) Student Integration Model, Murphy et al. (2010) concluded that
indeed participation in the summer bridge program was linked to a greater likelihood of
graduation. Interestingly, this was not true of all populations, however. While women and
42
students from wealthier programs were more likely to benefit from the summer bridge program,
African American students and Georgia residents were less likely to see an increase in retention
rates because of participation in the bridge program (Murphy et al., 2010). This finding is
important to note because summer bridge program research typically indicates an
overwhelmingly positive result in terms of increased retention, while this study indicates that this
type of retention programming may be less effective for certain populations.
Finally, Ackermann (1991) studied both first-time students and transfer students at the
University of California – Los Angeles to determine the effects of a summer bridge program on
the academic, personal, and social development of underrepresented and low-income students
throughout their first year of study. Relying on multiple theoretical frameworks, including
Tinto’s (1975) Student Integration Model, Ackermann (1991) observed that the bridge program
impacted student retention as well as academic, personal and social development. However, the
impacts on academic, personal and social development varied amongst subgroups of students.
For example, black and Latino students ranked non-academic goals and objectives, like increased
self-esteem, as their highest achievement after the summer bridge program while Filipino
students ranked this factor as their lowest level of achievement (Ackermann, 1991). Regardless,
students who participated in the program were retained at a higher rate than those who did not,
although their overall GPAs were lower. Figure 5 shows selected authors who have contributed
to retention strategies and who were researched for this study.
43
Retention Strategies
Breihan (2007)3 prongs to retention: teaching, relationships outside of the classroom, support structures
Wolfe and Kay (2011) First year programming successful at retaining students (beyond just summer bridge)
Michael, Dickson, Ryan, and Koefer (2010) Best practices for summer programming. Relates to Breihan's 3 prongsMaggio, White, Molstad, and Kher (2005) Summer programming impacts retentionGarcia & Paz (2009) Summer bridge research focusing on academic preparednessMcCurrie (2009) Summer bridge research focusing on academic preparednessAckermann (1991) Summer bridge research focusing on low income/underrepresented studentsKeim, McDermott, & Gerard (2010) Summer bridge research focusing on low income/underrepresented studentsMurphy, Gaughan, Hume, & Moore (2010) Summer bridge research focusing on low income/underrepresented studentsPayne & Dusenbury (2007) Summer bridge research focusing on low income/underrepresented students
Strayhorn (2011)students participating in a summer bridge program showed improved academic skills & increased self-esteem and positive beliefs about one’s abilities
Stolle-McAllister (2011)
University of Maryland - Baltimore's famous Meyerhoff Bridge program using Bordieu's social capital framework. Program helped students academically, socially, and professionally
Keim et al. (2010) Summer bridge program in Arizona. Does it help Hispanic students? Yes, by instilling confidence
Murphy et al. (2010) Georgia tech bridge program helped out of state students, but not in state students.
Ackermann (1991)
first time & transfers at UCLA, relying on multiple theoretical frameworks, SIM, she observed that the bridge program impacted student retention as well as academic, personal and social development.
Figure 5. Retention Strategies Researchers.
Human Development. To have a robust understanding of retention issues and the role of
integration, a review of human development literature was also required. Drewery (2011), for
example, contended that humans experience “critical periods” (p.13) in their development during
which major transformations take place. The transformation from adolescence to adulthood is
one such critical period, as are other major life changes, including marrying, and having children
(Drewery, 2011). However, Drewery (2011) also pointed out that as life expectancies rise and
populations fragment in terms of education, employment, and skills, it becomes increasingly
more difficult for adolescents to experience critical periods in their development in the same time
44
frame as previous generations. This, according to Drewery (2011), means that individual
experiences become lost in the scientific search to quantify human development, which forces
individuals to attempt to fit into an antiquated and inflexible model of development. As
adolescents struggle to fit into this model, a new phase of human development was identified –
that of the “emerging adulthood” (Drewery, 2001, p. 14). In this phase, individuals seek to build
identity and experiment with the instability of being between a child and an adult (Drewery,
2011). This phase of human development is particularly salient to college students who, while
no longer under the direct auspices of their parents, feel a sense of independence yet are still
reliant on parental finances and a traditional home life, to some extent.
It is during this period of development that Guiffrida (2009) suggested that institutions
should focus on identity development and on building intrinsic motivation in students. Rather
than focus solely on academics and finances, Guiffrida (2009) argued that institutions aiming for
student success must also tend to the developmental needs of students as well, and that
encouraging students to participate in a variety of on-campus activities and social programs may
ease this critical transition to adulthood and to a collegiate environment. Similarly, Richards
(2011) suggested that early European universities existed primarily to modernize the indigenous
population, but that the focus on academic curriculum has resulted in a lack of attention to
socialization, something that indigenous populations were aware of the need for. Therefore, an
increased focus on socialization in institutions of higher education is needed, according to
Richards (2011), in order to help students properly develop into well-rounded adults.
Additionally, Ranis, Stewart and Samman (2006) insisted that the Human Development
Index (HDI), which lists just three categories of human needs, is indeed lacking in complexity
45
and that other needs have also been identified and must also be nurtured. Bodily well-being,
material well-being, and mental development, the three cornerstones of the Human Development
Index, are no longer sufficient to describe developmental needs of humans, and students, in a
modern context (Ranis et al., 2006). In fact, Ranis et al. (2006) list 11 additional categories of
need that they recommend for inclusion in the HDI, including social relations, empowerment,
community well-being, and environmental conditions. These categories, according to Ranis et
al. (2006) are equally important in a holistic view of human development as the initially
identified needs in the HDI. These additional categories are also particularly relevant to students
in their transition from high school to college and from adolescence to emerging adulthood and
to independence.
Finally, the social component of learning is also prevalent in andragogy and adult
learning studies. Merriam, Caffarella, and Baumgartner (2007), for example, stressed the
importance of social context in adult learning, and also noted that 83% of adults ages 25 to 34
have completed a high school education, while only 65% of adults over age 65 have done so.
This means that as our society prepares to educate a larger population of adults, and does so in a
social context while recognizing the importance of social integration for adult learners, we must
also provide our emerging adults with a social foundation as well, so that they are equally
prepared as today’s adults are to enter the workforce and engage in lifelong learning throughout
their careers and lifetimes. Similarly, Roberson (2002) asserted that traditional views of
andragogy and Malcolm Knowles’ theory of how adults learn is incomplete because it does not
focus on the social aspect of adult learning. While Knowles’ theory articulated that adults learn
differently from children in that adults are self-directed, have experiences which color their
46
views and their learning experiences, are ready to learn and engage in problem-solving activities,
and have a different sense of motivation than younger learners, it fails to address the social needs
of adult learners (Roberson, 2002). Given that social integration is a component of learning
throughout the development from adolescence to emerging adulthood and into independent
adulthood, it is important to have an understanding of the role of social integration and social
context for this study. Figure 6 outlines key researchers in the field of human development as it
relates to retention research and this research study.
Human Development
Drewery (2011)
Humans experience critical periods when transitions take place. As skills/education fragment, people experience critical periods at different times, forcing some to conform.
Drewery (2011)"Emerging adulthood" emerges from struggle to conform. Between two stages. Particularly relevant to college students
Guiffrida (2009) Focus on identity development during emerging adulthood. Institutions must also focus on developmental needs to retain students
Richards (2011) European universities used to exist to socialize. Current focus on academic curriculum means we don't socialize students
Ranis, Stewart and Samman (2006)
Human Development Index has 3 parts: bodily well-being, material well-being, mental development. More needed like social relatoinships, empowerment, community well-being
Merriam, Caffarella, and Baumgartner (2007)stressed the importance of social learning for adults, and as students drop out, they become adults who never learned socialization
Roberson (2002)
Malcolm Knowles’ theory of how adults learn is incomplete because it does not focus on the social aspect of adult learning. Knowles’ theory articulated that adults learn differently from children in part bc they are self-motivated and have life experiences
Figure 6. Researchers in the Area of Human Development.
Gaps in the Literature. Although there are numerous studies on Tinto’s (1975) Student
Integration Model, retention, and summer bridge programs, a gap in the literature exists
nonetheless. Most summer bridge research examines whether the program leads to higher
graduation rates for at-risk students (Braxton et al., 2004; Buck, 1985; Garcia, 1991; Gold, 1992;
Maggio et al., 2005; Murphy et al., 2010). Others explore the benefits of summer bridge
47
programs in relation to another goal, like improved academic performance alone (Fitts, 1989;
GlenMaye, Bolin, & Lause, 2010; Payne & Dusenbury, 2007), transition or adjustment in the
first year (Ackermann, 1991; York & Tross, 1994), or improved attitude towards library
resources (Haras & McEvoy, 2007). Some researchers study a specific population, like transfer
students (Keim et al., 2010), those who enroll in science, technology, engineering, or math (Zhe,
Doverspike, Zhao, Lam, & Menzemer, 2010), or high school students who participate in a bridge
program and subsequently enroll in a variety of institutions (Kallison & Stader, 2012; Moore,
Moore, Grimes, Millea, Lehman, Pearson, Liddell, & Thomas, 2007).
Two studies are similar to this research study but vary in important ways (see Figure 7).
The first study, by Wolfe and Kay (2011) seeks to explore summer bridge program participants’
level of commitment to the institution, but fails to compare these levels to a population of
students who did not participate. Similarly, Strayhorn (2011) also aims to determine sense of
belonging to a particular institution but again, does not compare these findings to those from a
population of students who have not participated in the bridge program. Finally, this study
examines success stories – at-risk students who have graduated from or are about to graduate
from Westfield State University - to understand the difference in institutional integration felt by
those who participated in the summer bridge program and those who did not. Strayhorn (2011)
and Wolfe and Kay (2011) both study current bridge program participants, so the connection to
retention is missing from their studies. A study of perceived level of integration, connected to
retention, is thus missing from the literature. This study aims to fill that gap by using Tinto’s
(1975) Student Integration Model as a backdrop for student integration at Westfield State
48
University as perceived by two different groups of at-risk students who were retained by the
institution.
Gaps
Wolfe and Kay (2011) Similar to this study, but does not compare integration levels to those who didn't participate. Studied current bridge participants so no success story.
Strayhorn (2011) Similar, looks at sense of belonging, but doesn't compare groups. Studied current bridge participants, so no success story.
Figure 7. Similar Research Studies.
Summary
By examining existing literature on retention, Tinto’s (1975) Student Integration Model,
and summer bridge programming, a robust understanding of the foundation of the research study
emerges. While some research focuses on students typically deemed at risk, other research
focuses on theories of student withdrawal and possible solutions, including summer bridge
programs as a means to both academically and socially integrate students into an institution. The
next chapter will operationalize this literature by describing the methodology and sampling for
the proposed study.
49
Chapter 3: Research Design
The purpose of this chapter is to describe the research design and methodology for the
study. This chapter is organized into nine sections including: methodology used, research
design, sample design, instrumentation, role of the researcher, data collection, data management,
data analysis, and the protection of human subjects.
Methodology
This quantitative, correlational study seeks to determine the relationship between
perceived levels of institutional integration (Tinto, 1975) for at-risk alum who enrolled as first
time freshmen between 2001 and 2006 and students in their last semester of coursework who
participated in a summer bridge program and those who did not, at a mid-sized, public university
in Massachusetts. Although an experimental methodology would allow the researcher to more
clearly demonstrate causation, this design was not appropriate for this study given that students
and alum self-selected whether to apply to the Urban Education Program. As such, the
researcher was not able to assign participants to groups, and thus, a correlational methodology
was used.
To determine correlation, a survey was used to measure perceived levels of integration
for the survey population so that a comparison between integration levels of students who
participated in the Urban Education Program and those who did not could be made. This design
allowed the researcher to answer the research question and to determine whether students and
alum who participated in the Urban Education Program perceived a greater level of academic,
social, and overall integration into Westfield State University, thereby resulting in their
successful graduation.
50
Research Design
This research study explored the relationship between participation in a summer bridge
program and perceptions of institutional integration through a comparison of at-risk students and
alum who participated in a summer bridge program and those who did not. Utilizing Tinto’s
(1975) Student Integration Model, this quantitative study uncovered participants’ perceived level
of academic and social integration through a quantitative survey which was completed by alumni
and students in their last semester before graduation at a mid-sized, public university in
Massachusetts. These scores were compared to a control group of at-risk students who did not
participate in the bridge program. The hypothesis for the research question is there is a positive
correlation between summer bridge program participation and perceived levels of institutional
integration.
This study used purely quantitative methods for data collection and analysis. Creswell
(2009) contends that quantitative research is appropriate to determine the relationship between
variables. In this case, the goal of the study was to determine the relationship between
participation in the summer bridge program and perceived integration by comparing at-risk
students and alum who participated in the bridge program with those who did not. Therefore, a
quantitative approach was warranted. A quantitative approach allowed the researcher to collect
data and perform statistical analyses through closed-ended questionnaires and institutional data.
This approach was limited, however, in that the perceptions of student integration levels were
quantified and the researcher did not delve into the reasons behind these perceptions or the
components of the bridge program that led to these perceptions. The emotional element of the
program, including student feelings, was not explored, which is a limitation to the study.
51
In order to best determine the relationship between variables, a correlational study was
conducted. Although correlational studies provide only partial evidence of causation (Vogt,
2007), an experimental design in which causation could be more clearly demonstrated was not
appropriate for this study. Experimental research designs, according to Vogt (2007), require the
random assignment of study participants into groups, which was not possible with the current
study. Additionally, Fraenkel and Wallen (2009) note that correlational research is appropriate
for studies seeking to determine the relationship amongst variables, which fits with the goal of
this study. Prediction of likely future outcomes is also possible with correlational research,
which is an added benefit of this study (Fraenkel & Wallen, 2009). Although a causal-
comparative design was considered for the proposed study, causal-comparative research helps to
explain differences among groups of people (Fraenkel & Wallen, 2009) and at the outset, it was
unknown if differences exist. The problem of potentially weak findings, however, was a
limitation of the correlational method (Fraenkel & Wallen, 2009).
Sampling Methodology & Target Population
In order to generate an appropriate sample, at-risk students who first enrolled at Westfield
State University as first-time freshmen between 2001 and 2006 were surveyed. The population
included a group who participated in Westfield State University’s Urban Education summer
bridge program (at-risk summer bridge program alum) and a group who did not (at-risk
University alum). Because both four-year and six-year graduation rates were taken into account,
the last year of entry possible for the study is 2006. Between 43 and 53 students enroll in the
summer bridge program each year, making a six-year sample size approximately 300 potential
survey respondents. Fraenkel and Wallen (2009) assert that a final sample of at least 50 students
52
is required for a correlational study such as this one, and surveys typically yield a 25% return.
Therefore, six years of alum yield at least 50 final participants from both groups - those who
participated in the bridge program and those who did not. Students were selected using
purposive sampling, defined by Fraenkel and Wallen (2009) as the selection of students based on
desired characteristics or status, which in this case are qualities that deem a student to be at-risk,
including first generation student status, low-income students, students with learning disabilities
and students who speak English as a second language. A survey with primarily closed-ended
questions was distributed electronically in order to measure respondents’ level of integration
using the Institutional Integration Scale (IIS) as modified by French and Oakes (2004).
Ultimately, however, due to inaccurate email addresses and other factors, a sufficient
sample of summer bridge program alum was not achieved using the original sampling selection
noted above. Therefore, the sample was expanded to include currently enrolled students who are
on track to graduate at the end of this semester (Spring, 2013). These students are those with at
least a 2.0 GPA or higher, those with a minimum of 105 earned credit hours, and those identified
by the registrar’s office as having completed curricular requirements at the end of the semester.
This additional sample included students who participated in the summer bridge program and
those who did not, and provided a sample large enough for analysis, according to Fraenkel and
Wallen (2009).
There were, however, limitations to this sampling strategy. Because the Institutional
Integration Scale asks respondents to recall their institutional experiences, some respondents may
exhibit recall bias given that they first attended college a number of years ago. It was not
possible, given the study design, to survey more recent participants without extending the scope
53
of the study. Additionally, generalizability of the study may be limited due to the specificity and
uniqueness of the bridge program in this study. Finally, because the population for the study was
drawn from the researcher’s home institution, generalizations about other bridge programs were
not possible and the researcher took care to take nuances of Westfield State University and the
Urban Education Program into account when drawing conclusions about the data obtained. The
sample population should be considered a limitation of the study.
Participants were identified by institutional records and were recruited through the use of
an online survey invitation. A gift certificate raffle was provided as incentive and participants
submitted surveys anonymously. A series of meetings between the researcher and the
administrators of the bridge program took place to foster an open relationship. Finally, IRB
approval was sought in December, 2012 and modifications to the survey language were made in
order to protect the respondents and to obtain clear data.
In addition, it is important to understand the impact of the sampling strategy, the
admissions process, and the self-selection of participants on the overall research study. The
initial pool of students and alum at Westfield State University was narrowed considerably by
restricting the study population to specific years of entrance into the University. Further,
because the Urban Education Program’s admissions process includes essays and interviews, the
nature of the acceptance process is subjective. This subjectivity may mean that only stellar
students are accepted, thus narrowing the differences between the students who participated in
the summer bridge program and those that did not. Similarly, not all students accepted into the
Urban Education Program choose to attend Westfield State University and the Urban Education
Program. Since the Urban Education Program is optional and not a requirement for any student,
54
acceptance into the program does not guarantee that a student will attend the program.
Therefore, survey respondents who did not attend the Urban Education Program may have
elected to opt out on their own, again possibly eliminating differences between those who
attended the program and those who did not. Understanding how the respondent groups formed
is critical to having a robust view of the context and limitations of the study.
Instrumentation
The Institutional Integration Scale, originally developed by Pascarella and Terenzini
(1980) and subsequently modified by French and Oakes (2004) to improve reliability and
validity, was the primary research instrument. The researcher had obtained permission to use
this instrument on September 30, 2012. The Institutional Integration Scale was chosen because
of its ability to quantify perceived levels of academic, social, and institutional integration, a core
component to this study. Questionnaires were sent electronically to the predetermined sample
and ordinal data was collected. Ordinal data, according to Fraenkel and Wallen (2009) is data
that ranks respondents in terms of the degree to which they possess predetermined
characteristics, in this case their level of integration. Institutional data in the form of four and six
year graduation rates was also collected. To ensure the validity of the study, Cronbach’s Alpha
was used to reconfirm the validity of the survey subscales with this study sample population.
Using a previously validated survey instrument like the Institutional Integration Scale allowed
the researcher to reconfirm validity with the data collected rather than establish initial validity of
a new survey.
Operationalizing the Instrument with the Framework. According to French (2009),
the modified Institutional Integration Scale measures two facets of integration: the faculty factor
55
and the student factor. Both factors contain elements of social and academic integration, as
studied in Tinto’s Student Integration Model. Since these elements are not mutually exclusive,
French and Oakes (2004) contend that it is appropriate to study both elements together within the
constructs of student experiences with faculty and with other students. French (2009) also
articulates that the faculty and student factors are further broken into subcategories. The faculty
factor consists of questions belonging to the so called interactions with faculty and faculty
concern for student development and teaching subscales while the student factor features
questions belonging to the peer-group interactions, academic and intellectual development, and
institutional and goal commitment subscales (French, 2009). The Institutional Integration Scale
distributes its 33 questions amongst these subscales. For example, survey questions one and two
belong to the academic and intellectual development subscale (see Appendix H), questions 12
and 13 are part of the peer-group interactions subscale, questions 24, 25, and 26 are contained
within the interactions with faculty subscale, questions 28 and 29 belong to the faculty concern
for student development and teaching subscale, and questions 32 and 33 are part of the
institutional and goal commitment subscale (French, 2009). By categorizing and subcategorizing
questions in the Institutional Integration Scale, a better understanding of the relationship between
the survey instrument and Tinto’s Student Integration Model was possible.
Validity, Reliability, and Generalizability. The most concerning threat to validity and
reliability of the results of the study was that of recall bias. Given the purpose and scope of the
study, participants will have entered as first-time freshmen as much as four to 12 years prior to
completing the research survey. The researcher, therefore, asked participants to recall their
experiences. Given the amount of elapsed time, it was possible that respondents felt a different
56
way about their experiences in the wake of employment, or lack thereof, or a host of other life
experiences. Urging respondents to think just about their experiences at the University and not
about the opportunities ultimately afforded helped to prevent recall bias. This bias was a greater
threat to the at-risk summer bridge program alum since the bridge program occurs in the summer
prior to freshmen year, which is at the start of the collegiate experience. The survey questions,
however, asked about institutional integration throughout their time at the University and not just
in the first year of study, which meant respondents were asked to recall more recent experiences
as well.
Similarly, the researcher needed to account for non-responses when analyzing the data. It
was expected that 25% of the sample would respond to the survey (Fraenkel & Wallen, 2009),
and institutional data including most email addresses for alum were inaccurate, further reducing
the response rate. Therefore, a large number of non-responses affected the validity of the study.
Furthermore, because the researcher used purposive sampling instead of random sampling, there
was the potential that respondents included primarily students and alum with a positive
experience, interested in bolstering the Urban Education Program. An area for future study may
include a similar study in which a larger sample is used in order to use a random sampling
strategy.
Additionally, Cronbach’s Alpha was used to reconfirm the validity of the survey
instrument by confirming the validity of the subscales. Using a previously validated survey
instrument like the Institutional Integration Scale allowed the researcher to reconfirm validity
with the data collected rather than establish initial validity of a new survey. Therefore, the threat
to validity and reliability was minimized with the use of a pre-validated survey instrument,
57
though it should be noted that ultimately not all of the five survey subscales were shown to be
valid.
Finally, generalizability of this study was limited by the unique and specific nature of
Westfield State University’s Urban Education summer bridge program. Although summer bridge
programs are not wholly uncommon in the literature (Ackermann, 1991; Garcia & Paz, 2009;
Keim et al., 2010; McCurrie, 2009; Murphy et al., 2010; Payne & Dusenbury, 2007; Strayhorn,
2011), no two programs are exactly alike, nor do they serve exactly the same population of
students. Given the combination of myriad factors specific to Westfield State University’s Urban
Education Program, including program duration, academic coursework, social integration
activities, and student population, it is unlikely that the results of the proposed study will be
directly applicable, and therefore generalizable, to another summer bridge program.
Nonetheless, the results add to the breadth of literature on the topic of integration and retention
and provide higher education administrators with factors to consider when aiming to improve
retention.
Role of the Researcher
Understanding the context of the researcher’s goals and relationships within the study is
an important component to the research. Because I am not intimately involved in summer bridge
programming at any level within my institution, the likelihood of bias in favor of either the
program or the students was minimal. Additionally, my review of anonymous data and survey
responses provided few ethical challenges. However, the research study has the ability to impact
my relationship with bridge program coordinators as well as their relationships and employment
at the University. The outcome of the study may ultimately impact funding levels for the
58
program and, therefore, conclusions were carefully drawn. Creswell (2009) notes that
researchers must anticipate the consequences of conducting research at the chosen location and
asserts that subjects at the research location should receive a final copy of all data and
manuscripts. As such, discussions with the program coordinators and staff were on-going and
support for the research was pledged.
On a personal note, as a first generation college student myself, I understand the
challenges faced by students like those in the Urban Education Program at Westfield State
University. This experience may have caused me to assume certain results from the study, and it
was important to draw conclusions based solely on the data and not my own collegiate
experiences.
Data Collection
IRB approval was obtained in late January, 2013. Data collection began in February,
2013 and progressed in four phases. The first phase of data collection involved gathering
institutional data including information specific to the Urban Education Program, as well as
information on specific curriculum, program structure, the number of inquiries received, and
enrollment trends for each of the study years. The identification of the study sample also took
place in phase one with institutional data mining.
Phase two of data collection was the administration of the survey instrument
questionnaire. The questionnaire was piloted using a small sample of current students and alum
that were then precluded from completing the official survey. This pilot, according to Fraenkel
and Wallen (2009), can help to address poorly worded questions or other instrument issues prior
to its large scale release. The pilot was sent ten days prior to the large scale survey and
59
contained a section for completer comments and suggestions and necessary adjustments were
then made prior to sending the questionnaire to the larger population. A pre-survey email was
then sent to the study sample, indicating the purpose and importance of the survey which was to
follow. This pre-survey email was sent several days prior to the full survey.
An email questionnaire was then sent electronically through Survey Monkey, a
commercially available survey program. The questionnaire consisted of 33 questions from the
Institutional Integration Scale, and eight demographic questions with a ninth question for those
who completed the summer bridge program. Respondents were also afforded the opportunity to
provide general comments about their experience at Westfield State University with an open
ended question at the end of the questionnaire. This semi-structured, open-ended question
provided respondents with the opportunity to provide the researcher with additional information
on the reasons for their success at the institution, whether it was the Urban Education Program or
another reason. Finally, there was an opportunity for respondents to enter their email addresses
with the note that email addresses are used solely to inform the winners of the gift certificate and
were not matched to survey answers in any way. Questions were entered into Survey Monkey by
the researcher. Respondents selected answers on a 5-point Likert scale by clicking the radio
button next to the corresponding answer. For demographic questions, radio buttons were also
used but respondents only used a Likert scale question in this section if they completed the
summer bridge program, so that they ranked their perceptions on the importance of the bridge
program to their graduation. Participants were allotted one week in which to respond and the
questionnaire was resent multiple times to obtain a sufficient sample size. The researcher also
extended the survey completion date and expanded the sample to achieve the appropriate sample
60
size. A gift card raffle incentive was provided to entice students and alum to respond to the
questionnaire. Phase two of data collection began in early February, 2013.
Phase three of data collection then commenced and descriptive statistics for the two
groups, bridge participants and non-participants were explored. This allowed the researcher to
calculate means, medians, frequencies, distributions, and other such descriptive information
about both groups of students (Fraenkel & Wallen, 2009) for comparison. Survey responses were
also cleaned in preparation for data analysis. To clean the data, survey responses in Survey
Monkey were first saved and uploaded into SPSS, a commercially available data analysis
software package. Responses were then examined for incomplete answers. Respondents who
completed only part of the survey were eliminated entirely from participation. Additionally,
respondents who did not participate in the Urban Education Program were examined to ensure
their fit as at-risk students by confirming that their answers to the demographic section of the
questionnaire contained at least one risk factor, either first generation college student, student
who received financial aid, student who speaks English as a second language, or student with a
learning disability. Although all respondents met these criteria, the researcher closely examined
these responses in order to eliminate those who did not meet at least one at-risk student criteria.
Once the data were cleaned, the subset data were saved and used for all future analyses. The
final phase of data collection compared the results from phase three to the institutional data
gathered in the first phase so that an overall picture of the student body and the sample groups
emerged.
One potential threat to internal validity was the length of time between when the
respondents studied at Westfield State University and receipt of the questionnaire. Respondents’
61
answers may be different in the wake of employment or other opportunities than at the close of
their collegiate experience. In order to minimize this threat, the sample chosen represented the
most recent cohorts for which a four-year and six-year graduation rate can be calculated and
contained only current students on track to graduate at the end of the current semester.
Data Management
Data were collected through Survey Monkey, a commercially available website primarily
used for survey development and distribution. All questions required an answer, except for
demographic questions and open-ended questions. This eliminated partial survey responses for
the integration subsections of the survey, however some students exited out of the survey prior to
completion and were eliminated from the study pool. Additionally, since demographic questions
and open-ended questions were optional, some respondents chose to skip some of these
questions. However, data determining Urban Education Program participants and integration
levels were adequately collected.
Data were stored in Survey Monkey, to which only the researcher had access. During the
data analysis phase of the study, the researcher downloaded a pre-formatted SPSS data file from
Survey Monkey, and uploaded it into SPSS, a commercially available statistical analysis
program for manipulation. At that time, survey questions were grouped by subscale and
individual social, academic, and overall subscales were created in SPSS.
Data Analysis
This study used SPSS, a computer-based program to analyze the data. SPSS, according to
Vogt and Johnson (2011) is used to analyze most statistical models, which made it an appropriate
choice for the proposed study. Using SPSS, the study utilized multivariate analysis of variance
62
(MANOVA), which is an extension of the analysis of variance method (ANOVA). An ANOVA
is used to determine the statistical significance of differences between two groups (Vogt &
Johnson, 2011). The MANOVA essentially completes the same task but is used when there are
multiple dependent variables (Huberty & Morris, 1989). In the case of the current study, the
mean institutional integration score of both groups was being compared, but because the
Institutional Integration Scale allows the researcher to look at academic integration separately
from social integration and overall institutional integration, more than one dependent variable
existed, and the MANOVA was thus warranted. It is important to note that according to Huberty
and Morris (1989), using multiple ANOVAs is not the equivalent of utilizing a MANOVA. In
fact, doing so may lead to inaccurate results in some cases. The goal of the MANOVA,
according to Huberty and Morris (1989), is to determine and analyze underlying constructs, like
levels of integration, and thus they suggest carefully choosing dependent variables. Similarly,
they note that an ANOVA and MANOVA are indeed separate analysis techniques each of which
with a specific purpose, and selecting the proper method is wholly dependent upon the variables
to be studied (Huberty & Morris, 1989). Since the current study had multiple dependent
variables, the MANOVA was the appropriate choice to determine statistically significant
differences, or lack thereof, between the two study populations.
To ensure the validity of the study, Cronbach’s Alpha was used to reconfirm the validity
of the survey instrument via the surveys subscales. The researcher used a previously validated
instrument in order to reconfirm validity with collected data rather than establish validity anew.
Survey questions were grouped into their respective subscales using SPSS and Cronbach’s Alpha
63
was calculated using the subscales of grouped questions. Data were secured in a commercially
available software program, SPSS, to which only the researcher had access.
Protection of Human Subjects
No immediate threat to human subjects existed as a result of the study. Respondents
participated in an anonymous questionnaire, and responses were compiled and presented as
aggregate data. The identity of the participants were initially be known by the researcher as
institutional records were required to target the appropriate sample. However, the researcher was
not aware of how individuals responded to particular survey questions. The quantitative nature
of the proposed study eliminated direct and personal interaction between the participants and the
researcher, further protecting the human subjects.
One threat that was possibly perceived by participants was a breach in anonymity. Some
alum were either employed at the University, in a graduate program at the University, or both. If
these study participants were unsure of the level of anonymity provided, they may have hesitated
to either praise or criticize the University in their answers for fear of retribution in the workplace
or classroom. This fear was mitigated by a thorough explanation of the study, its uses, the data
collection process, and the aggregate manner with which results were presented.
Summary
The information presented in the literature review, coupled with staggering low retention
rates nationwide (Delmont, 2011; Roach, 2008; Weddle-West & Bingham, 2010) made retention
a relevant and important topic in higher education. By focusing on summer bridge programming
at Westfield State University, and by utilizing Tinto’s (1975) Student Integration Model as a
framework, this study contributes to the field of retention research by focusing on integration – a
64
factor theoretically associated with higher levels of retention (Tinto, 1975). By examining at-risk
students who graduated or who are about to graduate, a picture of success emerged and the
researcher and other higher education administrators now have data to help determine what
makes bridge programs successful. Chapter four of this study will also include an introductory
section discussing the context of summer bridge programs as it related to Westfield State
University and Tinto’s (1975) Student Integration Model. Indeed, Tinto’s (1975) Student
Integration Model provided a robust framework through which to view the problem of student
integration and attrition, and the wealth of research on successful retention programs allowed for
a clear understanding of those programs and the program at Westfield State University. By using
the Institutional Integration Scale, a previously validated survey instrument, the researcher was
able to gauge the level of integration for both graduating students and alum of the summer bridge
program and at-risk students and alum that chose not to participate in the program. The
relationship between participation in the bridge program and perceived levels of integration was
then determined. Because this research addressed retention as it related to integration and the
summer bridge program, a comprehensive view of summer bridge programs and the reasons for
their success emerged and rendered this research important to the field of higher education.
65
Chapter 4: Results
This chapter will present the statistical results of the data collected and analyzed in the
study. The chapter contains three subsections: the context of the bridge program and the study,
descriptive statistics of the data sample, and analysis of survey results.
Context
The focus of this study, the Urban Education Program, first known as Alternatives for
Individual Development, was funded by the Commonwealth of Massachusetts in 1968. Based on
its early success, the program quickly received institutional funding as well, and is now fully
funded by Westfield State University. Although the program was always referred to as the
Urban Education Program on the campus of Westfield State, it is in fact a misnomer since
participants are not required to originate in an urban setting. Instead, first generation college
students, students who speak English as a second language, those with documented learning
disabilities, and low-income students, defined as students who receive financial aid, are eligible
to apply to the Urban Education Program.
The Urban Education Program requires a separate and additional application from the
University application. This application process typically also includes letters of
recommendation, the submission of transcripts, application to the University, personal
interviews, and five one-page essays. Acceptance is based largely on the perceived level of need
the student demonstrates. Some students who meet participation criteria but who demonstrate a
high level of resiliency in their grades, essays, or interviews, are deemed overqualified, and not
in need of the bridge experience. Similarly, students who put very little effort into the application
process or who did not complete the process are also rejected. Students who are perceived to
66
have a genuine desire to succeed in college but who possess one or more of the aforementioned
risk factors are ideal candidates for acceptance. Upon acceptance into the University and the
program, students participate in a free summer bridge program in the summer prior to freshmen
year. This experience, referred to by some as “academic boot camp” has shifted from a six week
residential experience to a five week residential experience in 2007. The summer bridge
experience is the heart of the Urban Education Program, though students remain connected,
albeit informally, to the Urban Education Program staff throughout their tenure at the University
through individual mentoring relationships.
The summer bridge experience itself consists of five weeks on campus, though students
go back to their hometowns on the weekends. Although the day time academic curriculum and
evening social events have shifted and evolved over time, the outline of the program has largely
remained consistent. The hallmark of the summer bridge program is the First Year Experience
class, in which students gain important knowledge including resources available on campus,
academic success strategies including study skills and note taking, and information on how to
best utilize library resources. Students received one academic credit for the First Year
Experience class until the mid-2000s, at which point the credits were eliminated from this aspect
of the Urban Education Program.
Additionally, students complete other academic requirements during the summer bridge
experience as well. A non-credit writing workshop is a staple of the program and provides
students with additional writing support, a factor critical to their ultimate success at Westfield
State. Further, each student participates in a three credit math class and an additional three credit
core class. Massachusetts public institutions all subscribe to the common core of study, a
67
grouping of introductory classes deemed necessary for collegiate success. Core classes are easily
transferrable between institutions and provide foundational knowledge in main subject areas. The
core class offered through the Urban Education summer bridge program has varied over time as
the common core has been updated and modified, as instructors move on to other institutions,
and as other factors deem necessary. Most often, students participate in a science core class, like
Astronomy, a Cultural Geography class, a Sociology class, a Philosophy class or a Speech class.
Evening social activities are also an important component of the Urban Education
Program. Peer counselors, who live in the dormitories with students, receive extensive training
on modeling appropriate dormitory behaviors, socializing students, and identifying students
struggling to integrate. Peer counselors provide a robust agenda of activities for students in the
evenings, including basketball games, volleyball games, ice cream parties, ice breakers, local
field trips, talent shows, awards night, and movie nights all designed to integrate students with
others in the program and with the campus in general. Prior to 2009, peer counselors also took
students on a field trip to New York City, though this trip has been eliminated due to budget cuts.
Peer counselors report that these activities often cement student relationships early on and help
promote lifelong friendships among Urban Education students.
As a result of the Urban Education Program’s early success with retaining at-risk students
at the University, a greater focus was placed on disability and tutoring services at the institution.
Until 1990, therefore, Urban Education staff also handled disability and tutoring services, but
these services were split out into their own departments after 1990, allowing the Urban
Education staff to focus once again on summer bridge programming and the mentoring of at-risk
students. Throughout its tenure, the Urban Education Program has had just three Directors, the
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most recent of whom began as Director in 1992 and is, herself, an Urban Education alumnus.
Besides the Director, the Urban Education Program has two other year-round staff, one of whom
is also an Urban Education Program alumnus. In the summer, additional staff members are hired
to work with the students in the dormitories, and include one peer counselor for every 10
students, a Residence Director, an Assistant Residence Director, four senior staff, and two
program coordinators. This size and organizational structure has remained relatively consistent
throughout the program’s history.
The number of initial inquiries and completed applications to the Urban Education
Program has varied over time. Due to database software changes in 2004, peripheral data
regarding inquiries and application numbers are no longer available. However, the most recent
data indicate that over 500 students inquired about the Urban Education Program for the 2012
summer cohort by attending an information session or open house, requesting an application, or
contacting the Urban Education Program office directly. Ultimately, 151 students were accepted
into the summer 2012 cohort and just over 100 chose to attend both Westfield State University
and the Urban Education Program. This represents the largest cohort of Urban Education
Program students to date. Table 1 shows historical enrollment trends in the Urban Education
Program.
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Table 1 Urban Education Program enrollment trend Cohort Enrolled Summer 2001 43 Summer 2002 45 Summer 2003 47 Summer 2004 49 Summer 2005 51 Summer 2006 53 Summer 2007 60 Summer 2008 73 Summer 2009 99 Summer 2010 72 Summer 2011 81 Summer 2012 102
In the summer of 2001, the first year included in this study, 43 students participated in the Urban
Education Program. This number rose slowly but steadily until 2007, 2008 and 2009, during
which times more sizable jumps in enrollment were experienced. However, 2010 and 2011
showed a rather sharp decline in enrollment, before a sharp increase in 2012 to 102 enrolled
students.
Descriptive Statistics
The survey sample consisted of students who enrolled as first time freshmen at Westfield
State University between 2001 and 2006 inclusive and who have since graduated. Students who
participated in the Urban Education Program and at-risk students who met eligibility
requirements but who did not enroll in the Urban Education Program were both sampled. The
initial survey invitation was sent to 4,587 email addresses. However, due to logistics with
institutional data maintenance, the initial list contained both inactive or invalid email addresses
and multiple email addresses for the same individual. For example, all Westfield State
70
University students are assigned an institutional email address, but also inform the institution of
their personal email addresses upon graduation. Personal email addresses do not overwrite
institutional addresses and are not cross checked. Similarly, some students use their personal
addresses exclusively, leaving their institutional email address full and thus no longer valid.
After multiple email contacts, this initial sample yielded 115 survey respondents, but only two
who had participated in Urban Education.
Subsequently, the Urban Education Program staff and other faculty and administrators on
campus posted the survey invitation on targeted Facebook groups, send personal emails to Urban
Education alum, and called Urban Education alum with whom they are still in contact to solicit
more responses. While this effort yielded additional Urban Education respondents, the number
grew only to 24. At that point, it was determined that a wider sample population was needed,
and the survey invitation was then sent out to currently enrolled Westfield State University
students on track to graduate at the end of the current semester. Only students with 105 or more
earned credits and with a grade point average of 2.0 or higher and who are pre-targeted by the
University registrar as having met curricular requirements for graduation were selected for this
additional sample. This additional sample resulted in 278 additional email addresses.
After more than three weeks, the survey was closed and 150 responses were collected.
Of the respondents, 50 or one-third were male, and 100 or two-thirds were female (Table 2).
However, in the overall population of undergraduate students at Westfield State University, 47%
are male and 53% female. Because survey respondents are disproportionally female as compared
to the overall student body, survey results may not be truly representative of the Westfield State
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University student population. Using the Descriptive Statistics function in SPSS, a gender
breakdown (Table 2) and graduation year frequency chart were generated (Table 3).
Table 2 Gender breakdown
Are you male or female?
Frequency Percent
Male 50 33.3
Female 100 66.7
Total 150 100.0
Most of the respondents, 112 or 74.7%, were alum while 38 or 25.3% were current students on
track to graduate at the end of the current, Spring 2013, semester (Table 3).
Table 3 Graduation year
What year did you graduate from WSU?
Frequency Percent
2005 25 16.7
2006 18 12.0
2007 12 8.0
2008 19 12.7
2009 23 15.3
2010 11 7.3
2011 3 2.0
2012 1 .7
I have not yet graduated 38 25.3
Total 150 100.0
Additionally, by using the Descriptive Statistics function within SPSS, it was noted that 52
respondents, or 34.7% participated in the Urban Education Program while the remainder, 98 or
65.3% did not participate (Table 4). Of the 98 respondents who did not participate in the Urban
72
Education Program, all exhibited at least one at-risk criteria and were eligible for the Urban
Education Program.
Table 4 Urban Education Program participation
Did you participate in the Urban
Education program while attending
WSU?
Frequency Percent
Yes 52 34.7
No 98 65.3
Total 150 100.0
The 33-question survey instrument consisted of two categories, faculty and student,
broken into a total of five subscales: interactions with faculty, faculty concern for development
and teaching, peer group interactions, academic and intellectual development, and institutional
and goal commitment. The interactions with faculty subscale largely measured non-classroom
interactions with faculty, and aligns with Tinto’s (1975) notion of social interaction. When
Cronbach’s Alpha was performed on the interactions with faculty subscale to confirm its validity
with the sample population, a score of .869 was achieved. According to Muijs (2011), scales are
validated for the sample when a Cronbach’s Alpha score of at least .7 is reached. Therefore, the
interactions with faculty subscale was determined to be valid for the sample population in this
study. To verify each subscale, the researcher used SPSS to select cases and manually assigned
each survey question to the appropriate subscale in accordance with the French and Oakes
(2004).
The second subscale, faculty concern for development and teaching, contained questions
designed to gauge whether students believed their faculty members were genuinely interested in
73
helping them develop academically, and thus is aligned with Tinto’s (1975) academic integration
concept. When Cronbach’s Alpha was performed on this subscale, it, too, was shown to be valid
for the sample population, with a score of .878. In terms of the student subscales, the third
subscale, peer group interactions, measures both interpersonal relationships between students and
overall alignment of values and attitudes between students on campus. This subscale is
considered a social integration subscale and was also shown to be valid for the sample
population with a Cronbach’s Alpha score of .854.
The fourth subscale, academic and intellectual development, contained questions related
to academic interests without mentioning the role of faculty members. Questions like “I am
satisfied with my academic experience at Westfield State University” measure the perceptions of
overall intellectual growth of the student and are considered to be an academic integration
subscale. This subscale, too, was deemed valid after running Cronbach’s Alpha on survey
questions in this subscale, as selected using SPSS, and obtaining a value of .744. The final
subscale, institutional and goal commitment, measures the student’s overall perception of their
experiences with goal attainment and their belief that Westfield State University is specifically
linked to individual achievements. This subscale measures the overall level of integration, as
described by Tinto (1975). Unfortunately, the Cronbach’s Alpha value for this subscale was just
.541, below the threshold of .7 and, therefore, it is not considered a valid subscale for this
population. Although some researchers use .5 as the Cronbach’s Alpha threshold, this subscale
is nonetheless less likely to measure integration for the sample population than are the other
subscales. The Cronbach’s Alpha values for the faculty subscales are listed in Tables 5.
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Table 5 Faculty Subscales
Name of Subscale Link to Tinto
Cronbach's Alpha Value
Interactions with Faculty Social 0.869 Faculty Concern for Development & Teaching Academic 0.878
Additionally, Table 6 shows the Cronbach’s Alpha values for the student subscales: Peer Group
Interactions, Academic & Intellectual Development, and Institutional & Goal commitment. Only
the Institutional & Goal Commitment subscale produced a Cronbach’s Alpha value lower than
the accepted threshold of .7.
Table 6 Student Subscales
Name of Subscale Link to Tinto
Cronbach's Alpha Value
Peer Group Interactions Social 0.854
Academic & Intellectual Development Academic 0.744
Institutional & Goal Commitment Overall 0.541
Finally, means and medians were collected for each subscale and each group of students
– those who attended the Urban Education Program and those who did not (Tables 7, 8) by using
the central tendency function within SPSS, which is a statistical menu within the frequencies
menu of the program. Muijs (2011) contends that when a variable is not truly continuous with an
75
unlimited number of values, the mean is not as useful because it will be a meaningless value in
between values with meaning. When reviewing data holistically, a mean score is unlikely to be
important to a researcher looking for trends, although the mean remains an important statistical
tool when exact computations are performed for quantitative analysis. Because the mean is a
specific number between Likert-scale scores, it is more appropriate for use in statistical analysis
but not as relevant to holistic data observations. When variables are ordinal, however, as they are
in Likert-scale surveys, the median is a more descriptive statistic because it will provide a true
score (Muijs, 2011). The median, therefore, will always be a whole number on the Likert-scale,
which is likely to be more important to researchers looking at overall trends when not interested
in exact statistical analyses. Because each subscale contains numerous but differing numbers of
questions, and because the researcher wanted to both perform specific calculations and observe
general trends, both the mean and the median were calculated.
Table 7 Subscale mean and medians for those who attended the Urban Education Program
InteractionsWith
FacultySocial
FacConcernDev
AndTeachAcad
emic
PeerGroupInter
actionsSocial
AcadIntellectDe
vAcademic
InstAndGoalCo
mmitOverall
Mean 25.4898 17.3200 33.3830 42.3725 22.3725
N 49 50 47 51 51
Median 26.0000 17.0000 35.0000 42.0000 22.0000
Similarly, subscale means and medians were calculated using the central tendencies function
within SPSS for respondents who did not attend the Urban Education Program (Table 8).
76
Table 8 Subscale mean and medians for those who did not attend the Urban Education Program
InteractionsWith
FacultySocial
FacConcernDev
AndTeachAcad
emic
PeerGroupInter
actionsSocial
AcadIntellectDe
vAcademic
InstAndGoalCo
mmitOverall
Mean 25.0417 17.3918 33.0313 40.4947 22.5816
N 96 97 96 95 98
Median 25.5000 17.0000 34.0000 42.0000 23.0000
Additionally, mean, median, standard deviation, and range was calculated for each survey
question and grouped by subscale. The institutional and goal commitment subscale, the only
subscale not revalidated through Cronbach’s Alpha, contains just five questions, two of which
have standard deviations close to 1.0 (Table 9).
Table 9 Subscale: Institutional & Goal Commitment. Cronbach’s Alpha Score: .541
Getting good grades
was important to me
during my time at
WSU.
While at WSU, I
performed
academically as
well as I anticipated.
During my time at
WSU, it was
important for me to
graduate from
college.
It was important for
me to graduate from
Westfield State
University
specifically.
I am confident that I
made the right
decision in choosing
to attend WSU.
N Valid 150 150 149 149 149
Missing 0 0 1 1 1
Mean 4.6800 4.2400 4.8993 4.1275 4.5638
Median 5.0000 4.0000 5.0000 5.0000 5.0000
Std. Deviation .57135 .90990 .32351 1.06091 .74727
Range 3.00 4.00 2.00 4.00 3.00
Minimum 2.00 1.00 3.00 1.00 2.00
Maximum 5.00 5.00 5.00 5.00 5.00
This means that respondents answered these questions differently from other students in the
group. High standard deviations may mean that the question, as worded, does not hold the same
77
meaning to each respondent, resulting in significantly different answers. This may be one reason
that the institutional and goal commitment subscale was not validated using Cronbach’s Alpha.
Future studies should examine these questions carefully and consider rewording those with high
standard deviations to ensure that the questions are quantifying perceptions in the same way for
each student. The interactions with faculty subscale contains six questions with just one high
standard deviation, thus meaning that the subscale was validated using Cronbach’s Alpha (Table
10).
Table 10 Subscale: Interactions with Faculty – Cronbach’s Alpha score: .869
I was satisfied
with
opportunities to
meet and
interact
informally with
faculty members
while at WSU.
Many faculty
members I had
contact with at
WSU were
willing to spend
time outside of
class to discuss
issues of interest
and importance
to students.
I developed a
close, personal
relationship with
at least one
faculty member
while at WSU.
My non-
classroom
interactions with
faculty members
while at WSU
positively
influenced my
intellectual
growth and
interest in ideas.
My non-
classroom
interactions with
faculty members
while at WSU
positively
influenced my
personal growth,
values, and
attitudes.
My non-
classroom
interactions with
faculty members
while at WSU
positively
influenced my
career goals and
aspirations.
N Valid 149 149 150 149 149 148
Missing 1 1 0 1 1 2
Mean 4.2013 4.2685 4.1933 4.2013 4.1678 4.1554
Median 4.0000 4.0000 4.0000 4.0000 4.0000 4.0000
Std. Deviation .78826 .84334 1.02123 .89276 .81707 .87063
Range 4.00 4.00 4.00 4.00 4.00 4.00
Minimum 1.00 1.00 1.00 1.00 1.00 1.00
Maximum 5.00 5.00 5.00 5.00 5.00 5.00
Similarly, the faculty concern for teaching and development subscale, which contained
just four questions, had relatively low standard deviations for each individual question, with no
78
standard deviations near 1.0. Again, this subscale was validated through Cronbach’s Alpha
(Table 11).
Table 11 Subscale – Faculty Concern for Development & Teaching – Cronbach’s Alpha Score: .878
Many faculty
members I had
contact with while
at WSU were
genuinely
outstanding or
superior teachers.
Many faculty
members I had
contact with while
at WSU were
genuinely interested
in students.
Many faculty
members I had
contact with while
at WSU were
genuinely interested
in teaching.
Many faculty
members I had
contact with while
at WSU were
interested in helping
students grow in
more than just
academic areas.
N Valid 148 149 149 148
Missing 2 1 1 2
Mean 4.2703 4.3423 4.4295 4.3108
Median 4.0000 4.0000 5.0000 4.0000
Std. Deviation .78761 .69527 .64990 .73634
Range 3.00 3.00 3.00 3.00
Minimum 2.00 2.00 2.00 2.00
Maximum 5.00 5.00 5.00 5.00
The peer group interactions subscale, containing eight questions, produced four questions with
standard deviations over 1.0 but was nonetheless validating using Cronbach’s Alpha, due in part
to the greater number of questions comprising this subscale than previously mentioned subscales
(Table 12).
79
Table 12 Subscale: Peer Group Interactions. Cronbach’s Alpha Score: .854
I developed
close
personal
relationships
with other
students
while at
WSU.
The student
friendships
I developed
at WSU
were
personally
satisfying.
It was easy
for me to
meet and
make friends
with other
students
during my
time at
WSU.
During my
time at
WSU, I was
satisfied
with my
dating
relationship
s.
During my
time at WSU,
many
students I
knew would
be willing to
listen and
help me if I
had a
personal
problem.
Most
students at
WSU had
values and
attitudes
similar to
mine.
I was satisfied
with the
opportunities to
participate in
organized extra-
curricular
activities while
at WSU.
I was happy
with my
living/reside
nce
arrangement
at WSU.
N
Valid 149 150 149 150 149 150 147 149
Missin
g
1 0 1 0 1 0 3 1
Mean 4.4899 4.4733 4.2081 3.7400 4.1074 3.7733 4.1973 3.9530
Median 5.0000 5.0000 5.0000 4.0000 4.0000 4.0000 4.0000 4.0000
Std. Deviation .84324 .81674 1.09220 1.27142 .97358 1.06277 .94100 1.08637
Range 4.00 3.00 4.00 4.00 4.00 4.00 4.00 4.00
Minimum 1.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00
Maximum 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00
Finally, the academic and intellectual development subscale contained the greatest number of
questions than any other subscale (10), and had only three questions with a standard deviation of
1.0 or greater. Again, this subscale was validated using Cronbach’s Alpha (Table 13).
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Table 13 Subscale: Academic & Intellectual Development. Cronbach’s Alpha Score: .744
Most of
my
courses
at
Westfiel
d State
Universit
y were
intellectu
ally
stimulati
ng.
I am
satisfied
with my
academic
experien
ce at
Westfiel
d State
Universit
y.
I am more
likely to
attend a
cultural
event (e.g.,
a concert,
lecture, or
art show)
now as
compared
to before
college.
I am
satisfied
with the
extent
of my
intellect
ual
develop
ment
while at
WSU.
In addition
to required
reading
assignments
, I read
many of the
recommend
ed books for
my courses
at WSU.
My
interest
in ideas
and
intellect
ual
matters
increase
d during
my time
at
WSU.
I had an
idea
about
what I
wanted
to
major
in
during
my
Freshm
en year.
My
academic
experience
at WSU
has
positively
influenced
my
intellectual
growth and
interest in
ideas.
My
interpersonal
relationships
with other
students
while at
WSU has
positively
influenced
my
intellectual
growth and
interest in
ideas.
My
personal
relationship
s with other
students
while at
WSU
positively
influenced
my
personal
growth,
values, and
attitudes.
N
Valid 150 148 150 150 149 149 150 150 150 150
Missin
g
0 2 0 0 1 1 0 0 0 0
Mean 4.2800 4.4865 3.7067 4.3400 3.1275 4.1678 4.0000 4.4333 4.2800 4.3200
Median 4.0000 5.0000 4.0000 4.0000 3.0000 4.0000 5.0000 5.0000 4.0000 5.0000
Std. Deviation .56900 .67498 1.12654 .67386 1.27496 .96844 1.30564 .66974 .86015 .97154
Range 3.00 3.00 4.00 3.00 4.00 4.00 4.00 3.00 3.00 4.00
Minimum 2.00 2.00 1.00 2.00 1.00 1.00 1.00 2.00 2.00 1.00
Maximum 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00
Analysis
By using multivariate analysis of variance (MANOVA), the statistical difference in
integration subscale scores between the group who participated in the Urban Education Program
and the group that did not can be determined (Huberty & Morris, 1989; Vogt & Johnson, 2011).
It is important to note that a significance level of .05, which signifies a 95% confidence interval,
is regarded by most researchers as the standard level of significance needed to determine that a
difference exists between groups (Muijs, 2011). Values of .05 and under, therefore, indicate a
81
significant difference between the two groups. For this study, a MANOVA was run using SPSS
statistical software and the subscale scores of each group were compared. The MANOVA
function in SPSS is located first in the analyze menu, then under general linear model. The
researcher then chose multivariate due to the multiple dependent variables present in the study.
Only one subscale, the academic and intellectual development subscale, which is a measure of
academic integration, was shown to be statistically different between the group who participated
in the Urban Education program and the group that did not (Table 14). The other subscales all
demonstrated significantly higher values and thus a statistical difference between the two groups
cannot be concluded for the remaining subscales.
Table 14 MANOVA results
Variable Subscale Significance
Participation in the Urban Education Program
Interactions With Faculty (Social) .346
Faculty Concern for Development & Teaching (Academic)
.956
Peer Group Interactions (Social) .653
Academic & Intellectual Development (Academic) .040
Institutional & Goal Commitment (Overall) .533
Similarly, the multivariate analysis of variance was also calculated by gender in order to
determine if the Urban Education Program was more useful for males or females. Tables 15 and
16 show the results of this MANOVA. It should be noted that the academic and intellectual
development subscale was still the only subscale to show a statistically significant difference
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between female Urban Education Program participants and female students and alum who did
not attend the program. The significance score for this subscale is even more dramatic for
female students than for the population at large.
Table 15 MANOVA results – females only
Variable Subscale Significance
Participation in the Urban Education Program
Interactions With Faculty (Social) .383
Faculty Concern for Development & Teaching (Academic)
.452
Peer Group Interactions (Social) .252
Academic & Intellectual Development (Academic) .018
Institutional & Goal Commitment (Overall) .494
Conversely, when subscale scores for males were calculated (Table 11), none of the subscales
showed a statistical difference between those who participated in the Urban Education Program
and those who did not, although it should be noted that the gender breakdown of survey
respondents does not match that of the overall University population. While the University as a
whole enrolls 53% female undergraduates, 66.7% of survey respondents were female, which
may skew the impact of the program on female students.
83
Table 16 MANOVA results – males only
Variable Subscale Significance
Participation in the Urban Education Program
Interactions With Faculty (Social) .701
Faculty Concern for Development & Teaching (Academic)
.273
Peer Group Interactions (Social) .284
Academic & Intellectual Development (Academic) .912
Institutional & Goal Commitment (Overall) .952
Finally, multivariate analysis of variance results were also calculated by graduation year
to determine if modifications to the Urban Education Program over time have been successful.
Results are shown in Tables 17 – 23. Only one respondent graduated in 2011, and thus it is not
possible to calculate multivariate analysis of variance scores for this graduation year. Similarly,
no respondents graduated in 2012 and thus no MANOVA results were calculated for 2012. It
should also be noted that MANOVA results by graduation year may not be indicative of
differences that may exists between those who attended the Urban Education Program and those
who did not due to the relatively low number of respondents in each group. When viewed by
graduation year, none of the subscales indicate a statistically significant difference in perceptions
between those who participated in the Urban Education Program and those who did not.
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Table 17 MANOVA results – Graduated in 2005
Variable Subscale Significance
Participation in the Urban Education Program
Interactions With Faculty (Social) .165
Faculty Concern for Development & Teaching (Academic)
.538
Peer Group Interactions (Social) .251
Academic & Intellectual Development (Academic) .842
Institutional & Goal Commitment (Overall) .179
As with those who graduated in 2005, Table 18 below indicates that no statistically significant
difference in integration was shown between those who participated in the Urban Education
Program and those who did not when looking only at students who graduated in 2006.
Table 18 MANOVA results – Graduated in 2006
Variable Subscale Significance
Participation in the Urban Education Program
Interactions With Faculty (Social) .879
Faculty Concern for Development & Teaching (Academic)
.704
Peer Group Interactions (Social) .508
Academic & Intellectual Development (Academic) .824
Institutional & Goal Commitment (Overall) .939
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As with previous graduation years, students who graduated in 2007 (Table 19) did not show a
statistically significant difference in integration levels between those who participated in the
Urban Education Program and those who did not.
Table 19 MANOVA results – Graduated in 2007
Variable Subscale Significance
Participation in the Urban Education Program
Interactions With Faculty (Social) .676
Faculty Concern for Development & Teaching (Academic)
.753
Peer Group Interactions (Social) .481
Academic & Intellectual Development (Academic) .135
Institutional & Goal Commitment (Overall) .772
Continuing the trend of previous graduation years, the 2008 graduates again show no statistically
significant difference in integration levels (Table 20) between students who participated in the
Urban Education Program and those who did not.
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Table 20 MANOVA results – Graduated in 2008
Variable Subscale Significance
Participation in the Urban Education Program
Interactions With Faculty (Social) .815
Faculty Concern for Development & Teaching (Academic)
.604
Peer Group Interactions (Social) .595
Academic & Intellectual Development (Academic) .994
Institutional & Goal Commitment (Overall) .480
Again, no statistically significant difference in integration levels was perceived by those who
participated in the Urban Education Program and those who did not for graduates in 2009 (Table
21).
Table 21 MANOVA results – Graduated in 2009
Variable Subscale Significance
Participation in the Urban Education Program
Interactions With Faculty (Social) .540
Faculty Concern for Development & Teaching (Academic)
.723
Peer Group Interactions (Social) .105
Academic & Intellectual Development (Academic) .332
Institutional & Goal Commitment (Overall) .974
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Examining the last of the graduated students, no statistically significant difference in perceived
integration levels was noted for 2010 graduates between students who participated in the Urban
Education Program and those that did not participate (Table 22).
Table 22 MANOVA results – Graduated in 2010
Variable Subscale Significance
Participation in the Urban Education Program
Interactions With Faculty (Social) .376
Faculty Concern for Development & Teaching (Academic)
.229
Peer Group Interactions (Social) .608
Academic & Intellectual Development (Academic) .356
Institutional & Goal Commitment (Overall) .758
Finally, subscale MANOVA results were calculated for the population of students who have not
yet graduated but who are in their last semester of study. Again, no statistically significant
difference was noted in levels of perceived integration between the group of students who
participated in the Urban Education Program and those who did not (Table 23).
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Table 23 MANOVA results – Has not yet graduated
Variable Subscale Significance
Participation in the Urban Education Program
Interactions With Faculty (Social) .701
Faculty Concern for Development & Teaching (Academic)
.536
Peer Group Interactions (Social) .541
Academic & Intellectual Development (Academic) .703
Institutional & Goal Commitment (Overall) .417
Because the respondents were divided over many years of graduation, it is likely that the
small sample size per year affected the validity of MANOVA scores, resulting in no statistically
significant differences between groups of students in any year of graduation. Therefore,
graduation years were grouped into early graduates (those who graduated in 2005, 2006 and
2007) and late graduates (those who graduated in 2008, 2009, 2010, and those who have not yet
graduated). Multivariate analysis of variance results for this grouping are displayed in Tables 24
and 25. Early graduates show no statistically significant difference between those who attended
the Urban Education Program and those who did not.
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Table 24 MANOVA results – early graduates
Variable Subscale Significance
Participation in the Urban Education Program
Interactions With Faculty (Social) .257
Faculty Concern for Development & Teaching (Academic)
.573
Peer Group Interactions (Social) .654
Academic & Intellectual Development (Academic) .589
Institutional & Goal Commitment (Overall) .614
The late graduates, those who graduated in 2008, 2009, 2010 or who have not yet graduated
again display a difference in the academic and intellectual development subscale (Table 25).
Table 25 MANOVA results – late graduates
Variable Subscale Significance
Participation in the Urban Education Program
Interactions With Faculty (Social) .177
Faculty Concern for Development & Teaching (Academic)
.782
Peer Group Interactions (Social) .398
Academic & Intellectual Development (Academic) .049
Institutional & Goal Commitment (Overall) .926
Additionally, the survey posed one open-ended question to respondents, and answers
were coded as recommended by Gall, Gall and Borg (2007). Each response was carefully
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reviewed for themes and was assigned one or more key words that emerged from the answer.
Within the group of respondents who participated in the Urban Education Program, eight general
themes emerged that contributed to the success of the individual students: academic
courses/preparation (specific to the Urban Education Program), welcoming/close community
(also specific to the Urban Education Program), Staff (University-wide but including Urban
Education Program staff), support in general, growth, Urban Education Program in general,
teachers (specific to the Urban Education Program), and resources. Most responses for this
group were between 40 and 50 words long, though some were only a few words, and others were
upwards of 120 words. A total of 27 Urban Education Program participants responded to this
optional question.
Similarly, responses from those who did not participate in the Urban Education Program
were coded for common themes, although different keywords were produced by this group of
students. Eight general themes regarding individual success also emerged for those who did not
participate in the Urban Education Program: activities/sports, teachers, staff, friends, personal
drive, support, academics, community/connections on campus. A total of 49 students who did
not participate in the Urban Education Program answered this question. Responses were
generally longer than the group who participated in the Urban Education Program and ranged
from 60 – 75 words, with some responses being one sentence and others containing more than
300 words.
Themes and keywords emerged easily within the responses of both groups. Many
students specifically used the words teacher or faculty, which was combined into one keyword
category (teacher), listed a specific sport or activity they participated in, and specifically
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mentioned their academic coursework, as an example. Therefore, the coding process did not
require specific definitions, but rather counted the frequency of keywords specifically used by
students. Similar terms were combined and specific activities and sports were grouped together
for simplicity.
The question asked respondents to address factors that made them successful at Westfield
State University. Answers from those who participated in the Urban Education Program were
compared to those who did not attend the program. While the most common answer among
students and alum who participated in the Urban Education Program was the preparation they
received in their academic courses, students and alum who did not participate in the Urban
Education Program most often cited on campus activities and sports as a factor in their success.
These results are consistent with the quantitative results also, which showed a statistically
significant difference between the two groups in an academic subscale but not in either of the
social subscales. It should be noted, however, that 39% of students who did not attend the Urban
Education Program and who provided an answer to the open ended question commented that a
teacher was instrumental to their success. Although the social factor seems to be more important
to this population than the population that attended the Urban Education Program, the academic
component was not absent from their responses. One student said: “I am ahead on credits and
having the experience to take college courses and see how they are helped me prepare myself for
the courses I took in the fall of my freshman year. I have grown immensely.” Factors listed by
more than one student are shown in Table 26.
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Table 26 Urban Education students & alum qualitative response frequencies Academic courses/preparation 11 Welcoming/close community 10 Staff 6 Support 4 Growth 3 Urban Ed was instrumental/crucial to success 3 Teachers 2 Resources 2
Similarly, open ended responses were also collected for students and alum who did not
participate in the Urban Education Program. A frequency table of keywords used by this group is
shown below in Table 27.
Table 27 Students & alum who did not attend Urban Education qualitative response frequencies Activities/Sports 22 Teachers 19 Staff 7 Friends 5 Personal drive 4 Support 3 Academics 3 Community/Connections 2
General Findings and Summary
Understanding the context of the Urban Education Program and this study is critical to
understanding the results and accompanying statistical analyses. By comprehending the
academic and social factors in the Urban Education Program curriculum, the staff, structure, and
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history of the program, and by further realizing the population of students the program serves, a
robust picture of successful students and alum emerges.
Additionally, through the use of descriptive statistics, demographic information on the
survey respondents was obtained and it was determined that there were sufficient respondents
from each group to move forward with data analysis. The validity of four of the five subscales
was reconfirmed using Cronbach’s Alpha and each subscale was linked to Tinto’s (1975)
Student Integration Model, the underlying framework of this study. Upon extensive analysis
using MANOVA to determine the differences between groups, it was determined that only the
academic and intellectual development subscale showed a significant difference in perception
between those who participated in the Urban Education Program and those who did not. Analysis
of qualitative data from one survey question confirmed the results of the quantitative analysis
and demonstrated that the social factor was more important to students and alum who did not
attend the Urban Education Program, whereas academic preparation was the most commonly
cited reason for success among students and alum who participated in the program. Further
discussion of the implications of and reasons for this difference in just one subscale will be
explored in the following chapter.
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Chapter 5: Conclusions
This chapter will present conclusions based on the contextual factors and data analysis
described in the previous chapter, and will discuss implications for the Urban Education Program
and Westfield State University. Possible reasons for the results are explored, and
recommendations for future studies will be articulated.
Overview
The purpose of this study was to compare the perceived levels of academic, social, and
institutional integration between successful students and alum who participated in a summer
bridge program and those that did not. Tinto’s (1975) Student Integration Model contends that
students who are integrated into the fabric of their institutions are more likely to persist to
graduation, thus improving the institutions retention rates. Using the Institutional Integration
Scale, modified by French and Oakes (2004), perceived levels of integration were quantified and
mean scores of the two groups were compared using a multivariate analysis of variance. The
validity of the Institutional Integration Scale, consisting of five subscales – two academic, two
social, and one institutional – was confirmed using Cronbach’s Alpha, and four of the subscales
were determined to be valid for this study population. Based on analysis of the data, it can be
concluded that those who participated in the Urban Education Program perceive their levels of
academic and intellectual development, one of the four aforementioned subscales, to be greater
than those who did not participate in the program. Because this subscale is linked to academic
integration as described by Tinto (1975), the Urban Education Program successfully helps
academically integrate students into the University. Given the context of the Urban Education
Program and its nature as an “academic boot camp” this result is not surprising. Allowing
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students to gain six credits prior to formal fall matriculation into the University provides them
with a foundational academic advantage over other students. Because of these six credits,
students may be able to take fewer classes in a particularly challenging semester, and may have
greater familiarity with academic tutoring, the environment of the collegiate classroom, and the
rigor required for academic coursework. Students who did not participate in the Urban
Education Program lack these advantages.
Because this study focused on successful students – those who have graduated or who are
planning to graduate in the current semester – an understanding of the reasons behind their
success can be reached. Although academic integration cannot conclusively be cited as a reason
for the success of Urban Education Program students and alum, Tinto’s (1975) Student
Integration Model suggests that students who are integrated both academically and socially into
an institution are more likely to graduate. It is, therefore, reasonable to infer that their perceived
level of academic integration is one reason that some Urban Education Program participants
have been successful.
Conversely, because the other four subscales did not demonstrate a significant difference
in the levels of integration between the two groups, it can be concluded that the reasons behind
student success cannot be attributed directly to overall integration, social integration, and one
subscale of academic integration for Urban Education Program participants. These results were
confirmed by qualitative data showing that Urban Education Program students and alum did not
list social activities and sports as a reason for their success while students and alum who did not
attend the Urban Education Program listed them more frequently than any other factor. It should
be carefully observed, however, that this does not mean that Urban Education Program
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participants do not feel integrated socially, only that they are no more integrated than similarly
at-risk students who did not participate in the program. Therefore, there may be yet undiscovered
reasons that Urban Education Program participants who successfully graduate do so.
This study did not conclusively determine the levels of integration caused by the Urban
Education Program, but there are implications for the program nonetheless. Since Urban
Education Program students and alum did show a significant difference (.04) from those who did
not participate in the academic and intellectual development subscale, the implication is that the
program is, indeed, making a significant difference for students in this area. This should be
considered a positive outcome for the Urban Education Program.
Furthermore, when broken down by gender, the implications of the Urban Education
Program became more dramatic. It can be concluded with 98.2% certainty that the Urban
Education Program has a positive impact on the academic and intellectual development of
female participants, while male participants indicated no difference in this subscale or any
subscale from males who did not participate in the program.
Similarly, early graduates of Westfield State University who graduated in 2005, 2006 and
2007 also showed no significant difference between those who participated in the Urban
Education Program and those who did not. Late graduates, however, who graduated in 2008,
2009, 2010 or who will graduate this year, once again demonstrated a statistically significant
difference in the academic and intellectual development subscale between those who participated
in the Urban Education Program and those who did not. The other four subscales do not appear
to demonstrate significant differences for any subgrouping of students who participated in the
Urban Education Program and those who did not.
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Interpretation
There are a multitude of possible reasons that successful Urban Education Program
participants demonstrate a higher level of perceived academic and intellectual development than
their counterparts who did not participate in the program. The academic components of the
Urban Education Program are extensive and include two academic classes which award a total of
six credits prior to formal fall matriculation. These academic classes are foundational, core
classes, which may provide students with both an understanding of culture on campus and in a
collegiate classroom, and foundational knowledge needed for success in future courses.
Additionally, the Urban Education Program supplements these credit-bearing classes with non-
credit workshops, including the First Year Experience which introduces students to tutoring,
library services, and study skills, and a writing workshop to increase writing skills. These
opportunities are unique and specific to the Urban Education Program and non-participants
would not be afforded the same opportunities. Therefore, it is no surprise that Urban Education
Program participants perceive a higher level of academic and intellectual development than do
their counterparts who did not participate.
In addition, there are several reasons that the Urban Education Program appears to have a
greater impact on female students than on male students. Although historical trends of gender
breakdowns are not available for the Urban Education Program, the staff are largely female,
which may result in a greater recruitment of female students. All three permanent staff members
are female, and the majority of seasonally employed residence assistants are also female. This
may also mean that female students feel more comfortable and connected to the female staff
members, thus impacting their levels of integration. A female dominated program may also
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increase confidence for female participants, leading to higher levels of academic integration in
the classroom as well. Confident students are generally more likely to ask questions and seek
faculty assistance and guidance outside of the classroom, which are components to academic
integration. To have a more robust understanding of the gender differences noted in this study
and the reasons behind them, additional research should further explore this dynamic and seek to
determine best practices for improving integration levels of both males and females, who appear
to have differing needs in terms of summer bridge programming and institutional integration.
Similarly, the reasons that the other four subscale scores were not significantly different
between the two groups are as numerous as they are varied. While the Urban Education summer
bridge program is only a five to six-week experience, for example, the collegiate experience of
developing friendships, living in dormitories, and engaging in social activities typically occurs
over a four-year period. It is possible, therefore, that both groups of students and alum feel
socially integrated into the University, though neither group’s perception is more intense.
Having established immediate friendships and social connections in the summer bridge program
may indeed assist some students in persisting from the first fall semester into the spring semester,
for example, but Westfield State University is known to be the most residential of all
Massachusetts state institutions and has a reputation for outstanding student affairs programming
for all students. It is, therefore, no surprise that all students in the sample felt a relatively similar
level of social integration.
Similarly, perceptions of the faculty concern for development and teaching subscale may
be difficult to ascertain in a five to six-week summer bridge experience. Understanding the
overall faculty sentiments on campus may take more than one summer, and it is thus conceivable
99
that both groups of students and alum ultimately perceive the same levels of faculty concern at
the end of their University experience. It is possible that completing the survey immediately
after the summer bridge experience may produce different results.
Finally, although the overall integration subscale of institutional and goal commitment
did not prove to be a valid measure of integration for this sample, the results of the MANOVA
were also not different between the Urban Education Program participants and those who did not
participate in the program. Without a valid measure of overall integration, it is difficult to
speculate regarding whether there may have been a significant difference between the two
groups. Regardless, if the results were valid they would only indicate that Urban Education
Program participants do not feel a different level of overall integration than at-risk students who
did not participate, they would not indicate whether students perceived that they were integrated
or not. Thus, no direct conclusion regarding the Urban Education Program’s success at
integrating students into the University environment can be drawn from this data.
Implications
Implications for Practice. Based on the data collected and analyzed in this study, it is
recommended that Westfield State University and the Urban Education Program continue to
emphasize academic achievement as part of the programming. A strong focus on academic and
intellectual development may assist more students in persisting to graduation. As Tinto’s (1975)
Student Integration Model suggests, students who feel integrated into the University community
are more likely to persist to graduation. Given that Urban Education Program participants
demonstrated a higher perceived level of academic and intellectual development than did their
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at-risk counterparts who did not participate, an even greater focus on this component is
warranted.
Similarly, Westfield State University should consider specific recruitment initiatives to
attract female students to the Urban Education Program. Since the program seems to have the
greatest impact on females, attention should be paid to this group and to empowering more
females through the summer bridge program. It is also recommended that Westfield State
University consider shifting the focus of the Urban Education Program to an all-female program.
This may also help to improve social subscale scores because women may find deeper
connections and friendships when participating only with students of the same gender.
Furthermore, based on the qualitative data gathered in this study, Westfield State
University and the Urban Education Program should consider modifying the summer bridge
program to include more emphasis on confidence building for participants. Four students or alum
who did not attend the Urban Education Program specifically mentioned personal drive as a
factor that made them successful and noted that they would have been successful anywhere, not
just as Westfield State University. One student who did not participate in the Urban Education
Program commented: “I am a dedicated and focused individual who would have succeeded at
any institution of higher learning.” Although the number who responded with this factor is
small, particularly given the initial sample population, it is nonetheless indicative of varying
attitudes and confidence levels between those who attended the Urban Education Program and
those who did not. While respondents who attended the Urban Education Program cited factors
like support and growth as necessary to their success, those who did not attend the program cited
personal drive, social activities, and teachers. In fact, only 3 respondents who did not attend the
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Urban Education Program listed support as a factor to their success. The Urban Education
Program, therefore, should work to bridge the gap in attitudes between the two groups by
concentrating on confidence building activities and an enhanced program of social activities.
This study has implications for other institutions as well. Based on both quantitative and
qualitative data, the Urban Education Program has a positive effect on students’ academic and
intellectual development. Institutions with demographics similar to Westfield State University’s
should consider implementing a summer bridge program to improve levels of integration and
thus, retention, at their universities as well. For example, Westfield State University has eight
sister institutions, all former Massachusetts State Colleges, who collaborate on programming,
regularly share resources and information, and who serve similar populations of students. It is
strongly recommended that sister institutions who do not currently provide summer bridge
programming construct such a program with the recommendations and findings of this study in
mind. This group of institutions should also consider collaborating on their programming by
sharing in-demand or stellar faculty members, data, and best practices for summer bridge
programming.
Implications for Theory Advancement. Finally, this study has implications for the
existing body of knowledge and research in the field of retention, campus integration, and
student withdrawal. Although Tinto (1975), Bean (1982), and Cabrera et al. (1993) contend that
academic, social, and overall campus integration positively impacts student retention, this study
only partially confirms this concept. Since only one subscale showed a difference between
students who participated in the Urban Education Program and those who did not, this study is
102
not completely congruous with the Student Integration Model and other similar models put forth
by myriad researchers.
On the other hand, Breihan (2007) argued that retention has three prongs: teaching,
relationships outside of the classroom, and support structures. This study largely confirms
Breihan’s (2007) results as well and demonstrates that the most important factors for successful
students who attended the Urban Education Program were academic factors, which including
teaching, support structures, albeit academic structures in this case, and relationships with faculty
outside of the classroom. Similarly, Garcia and Paz (2009) and McCurrie (2009) discuss the
need for summer bridge programming to help prepare students academically, which is also
highlighted by this research study since one academic subscale was shown to have differing
perceptions between the group who attended the Urban Education Program and the group that
did not. This is in line with Strayhorn (2011) whose study showed that summer bridge
participants showed improved academic skills, and increased self-esteem. Therefore, this study
adds to the body of research on retention, student withdrawal, and integration by confirming the
findings in some studies, and contradicting the findings in others.
Suggestions for Future Research. Additional analysis of specific program details
should also be conducted to better understand how the program has morphed over time.
Although early graduates are more likely to exhibit recall bias than later graduates, it is possible
that small, seemingly insignificant changes to the program over time have resulted in a greater
focus on academic and intellectual development. Westfield State University must understand
and acknowledge these changes in order to enhance programming in future years as well. They
must also have a better understanding of student demographics within the Urban Education
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Program. Participation in other activities, athletics, student government, etc. may have a greater
impact on integration, particularly when coupled with participation in the Urban Education
Program. Future research should, therefore, also explore whether at-risk students participate in
athletics and other activities, and whether the Urban Education Program increases the likelihood
that at-risk students will participate.
Additionally, because this study compared successful students and alum who participated
in the Urban Education Program and those who did not, it is not possible to conclude that the
Urban Education Program either instills a sense of integration or that it does not. Only
conclusions between the two groups can be made. Therefore, Westfield State University should
consider conducting additional research to determine the specific impact of the Urban Education
Program. Similarly, additional research targeting students who did not successfully complete
their studies at Westfield State University may provide insight into other factors that affect the
student experience with the Urban Education Program that were not studied here. With the
complexities of the program, it is not possible to highlight every component in one study, so
additional research is needed to have a more robust view of the Urban Education Program.
Additionally, because this study surveyed only Westfield State University students and alum, it
is not possible to compare these results to those of similar programs at other institutions. Future
studies should compare the Urban Education Program at Westfield State University with similar
summer bridge programs across the country to better determine if the Urban Education Program
is having a similar effect to other programs.
Additionally, in the course of the research for this study, the qualitative nature of the
Urban Education Program became immediately apparent. While this quantitative study reduced
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student and alum perceptions to Likert-scale scores, medians, and significance values, the true
meaning, complexity, and purpose of the Urban Education Program may be better understood
with a qualitative study which allows respondents to share individual thoughts and experiences.
This type of study may provide a more robust view on the importance some students and alum
place on the Urban Education Program and may better articulate their experiences.
Conclusion
Tinto’s (1975) Student Integration Model serves as an excellent lens through which to
view the increasingly problematic issue of retention on university campuses. Students who feel
academically and socially integrated into an institution are more likely to persist to graduation,
according to Tinto (1975). Summer bridge programs, which are typically offered the summer
prior to freshman year, aim to provide certain populations of students with the social and
academic skills necessary for collegiate success, and are thus considered models for increased
retention. With this in mind, this study looked at one summer bridge program specifically, and
via a previously validated survey instrument, determined the level of academic and social
integration felt by students who participated in a summer bridge program and those who did not,
all of whom have successfully graduated, or will graduate at the end of the current semester.
Students with one or more risk factors for withdrawal, first-generation student, financial aid
recipient, students who speak English as a second language, and students were documented
learning disabilities, were studied.
Four of the five subscales linked to Tinto’s (1975) Student Integration Model were shown
to be valid for the sample population in this study. However, only one subscale, the academic
and intellectual development subscale, was shown to have statistically significant differences in
105
perception between those who participated in the summer bridge program and those who did not.
The reasons for this are varied and demonstrate only that a difference exists in one category,
without directly discussing if and how students are integrated at Westfield State University. The
reasons behind the success of students who participate in the Urban Education Program cannot,
therefore, be conclusively stated, but it should be noted that their summer coursework does seem
to play a role in their overall perceptions of academic integration. Furthermore, the Urban
Education Program also seems to provide a greater impact for female students and for students
who have graduated in the most recent graduation years or who will graduate this year. Further
study into seemingly insignificant curricular differences and changes in social activities should
be undertaken to better determine what recent changes have impacted the academic and
intellectual development subscale scores for recent graduates and current students.
Recommendations for Westfield State University and future research were also discussed.
Overall, the Urban Education Program at Westfield State University produces successful
students and alum who have a stronger sense of academic integration in one subscale than do
other at-risk students who do not participate in the program. This may be one reason for the
success of these students, but there are undoubtedly countless more not researched in this study.
106
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Appendix A – Pre-contact Letter – Via email
Hello Westfield State University Alum:
You are invited to complete an upcoming survey regarding your sense of integration into the Westfield State University community during your time as a student. As a doctoral candidate at Northeastern University, I am studying levels of institutional integration felt by WSU alum. The goal of this study is to compare the perceived levels of institutional integration felt by alum who participated in the Urban Education Program and alum who did not participate. In one week you will be asked to complete a short, electronic survey regarding your experience at WSU. The survey will be sent to you electronically. Even if you receive the survey more than once, we ask that you complete the survey only one time. The survey should take approximately 15-20 minutes to complete. Your participation in this study will be anonymous. Any reports or publications based upon this research will only use group data. Your participation in this research is very important and is very much appreciated. Upon completion of the survey you will be asked to provide your email address so you can be entered to win one of two $25 gift certificates to Amazon. The only reason your email address is requested is to inform you if you’ve won the raffle. Your email address will not be used for any other reason, nor will it be shared or sold. The survey responses will not be tied to your email address and you will remain completely anonymous. Please feel free to contact me with any questions. Also, please feel free to contact me if you do not wish to be included in this study. Please reply to this email with the subject line “Remove” to opt out from future emails about this research project. Sincerely,
Meaghan L. Arena Director of Program Development & Outreach Westfield State University Northeastern Doctoral Candidate [email protected] 413-572-8355
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Appendix B – First Reminder Letter – Via email
Hello Westfield State University Alum:
This is a friendly reminder to please complete the survey on “Institutional Integration at Westfield State University.” For your convenience, the following link will take you to the survey: www.linkhere.com The survey should take approximately 15-20 minutes to complete. Your participation in this study will be anonymous. Any reports or publications based upon this research will only use group data. The survey is scheduled to conclude on (DATE HERE). Please reply to this email with the subject line “Remove” to opt out from future emails about this research project. Your participation in this research is very important and is very much appreciated. Upon completion of the survey you will be asked for your email address so that we may contact you if you are the winner of one of two $25 gift cards to Amazon. Your email address will not be tied to your survey responses, sold to a third party, or used for any purpose aside from informing the raffle winners of their gift. Please feel free to contact me with any questions. Sincerely,
Meaghan L. Arena Director of Program Development and Outreach Westfield State University Northeastern Doctoral Candidate [email protected] 413-572-8355
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Appendix C – Second Reminder Letter – Via email
Hello Westfield State University Alum:
This is a second reminder to please complete the survey on “Institutional Integration at Westfield State University.” For your convenience, the following link will take you to the survey: www.linkhere.com The survey should take approximately 15-20 minutes to complete. Your participation in this study will be anonymous. Any reports or publications based upon this research will only use group data. The survey is scheduled to conclude on (DATE HERE). Please reply to this email with the subject line “Remove” to opt out from future emails about this research project. Your participation in this research is very important and is very much appreciated. Upon completion of the survey you will be asked for your email address so that we may contact you if you are the winner of one of two $25 gift cards to Amazon. Your email address will not be tied to your survey responses, sold to a third party, or used for any purpose aside from informing the raffle winners of their gift. Please feel free to contact me with any questions. Sincerely,
Meaghan L. Arena Director of Program Development and Outreach Westfield State University Northeastern Doctoral Candidate [email protected] 413-572-8355
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Appendix D – Final Reminder Letter – Via email
Hello Westfield State University Alum:
This is a final reminder to please complete the survey on “Institutional Integration at Westfield State University.” For your convenience, the following link will take you to the survey: www.linkhere.com The survey should take approximately 15-20 minutes to complete. Your participation in this study will be anonymous. Any reports or publications based upon this research will only use group data. The survey is scheduled to conclude on (DATE HERE). Please reply to this email with the subject line “Remove” to opt out from future emails about this research project. Your participation in this research is very important and is very much appreciated. Upon completion of the survey you will be asked for your email address so that we may contact you if you are the winner of one of two $25 gift cards to Amazon. Your email address will not be tied to your survey responses, sold to a third party, or used for any purpose aside from informing the raffle winners of their gift. Please feel free to contact me with any questions. Sincerely,
Meaghan L. Arena Director of Program Development and Outreach Westfield State University Northeastern Doctoral Candidate [email protected] 413-572-8355
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Appendix E – Informed Consent Form – To appear as the first survey question
Northeastern University, Department of: College of Professional Studies
Name of Investigator(s): Dr. Margaret Kirchoff, Meaghan L. Arena
Title of Project: Summer Bridge Programs: A Quantitative Study of the Relationship between
Participation and Institutional Integration using Tinto’s Student Integration Model at a Mid-
Sized, Public University in Massachusetts
Request to Participate in Research
We would like to invite you to participate in a web-based online survey. The survey is
part of a research study whose purpose is to compare levels of institutional integration between
alum who participated in the Urban Education Program and similar alum who did not participate.
This survey should take about 15-20 minutes to complete.
We are asking you to participate in this study because you entered Westfield State
University as a first time freshmen between 2001 and 2006 and subsequently graduated, and
exhibit at least one of the following characteristics: first generation college student, financial aid
recipient, student with a learning disability, or student who speaks English as a second language.
You will be asked to confirm your eligibility criteria during the survey.
The decision to participate in this research project is voluntary. You do not have to
participate and you can refuse to answer any question except the demographic questions, which
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determine your eligibility to continue the survey. Even if you begin the web-based online survey,
you can stop at any time.
There are no foreseeable risks or discomforts to you for taking part in this study.
As a token of our appreciation for completing the survey, you will be entered to win one
of two $25 gift cards to Amazon. To enter, you must provide your email address at the end of the
survey. Please note that your email address will not be linked to your survey responses or used
for any purpose other than informing raffle winners of their gift.
Your part in this study is anonymous to the researcher(s). However, because of the nature
of web based surveys, it is possible that respondents could be identified by the IP address or
other electronic record associated with the response. Neither the researcher nor anyone involved
with this survey will be capturing those data. Any reports or publications based on this research
will use only group data and will not identify you or any individual as being affiliated with this
project.
If you have any questions regarding electronic privacy, please feel free to contact Mark
Nardone, NU’s Director of Information Security via phone at 617-373-7901, or via email at
If you have any questions about this study, please feel free to contact Meaghan L. Arena
([email protected], 413-572-8355), the person mainly responsible for the research. You
can also contact Dr. Margaret Kirchoff ([email protected]), the Principal Investigator.
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If you have any questions regarding your rights as a research participant, please contact
Kate Skophammer, Human Subject Research Protection, 960 Renaissance Park, Northeastern
University, Boston, MA 02115. Tel: 617.373.4588, Email: [email protected]. You may call
anonymously if you wish.
By choosing the “yes” radio button below, you are indicating that you consent to
participate in this study. Please print out a copy of this consent form for your records.
Thank you for your time.
Meaghan L. Arena
Dr. Margaret Kirchoff
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Appendix F – Pilot Survey Letter – Via email. Dear Colleague: I would like to invite you to complete a pilot survey regarding Institutional Integration at Westfield State University. You were chosen for this pilot survey since you have attended Westfield State University in the past or are currently attending classes. Many of you may know that I am the Director of Program Development and Outreach, but I am also currently a doctoral candidate at Northeastern University’s Doctor of Education Program studying institutional integration at WSU. The goal of my graduate research study is to compare perceived levels of integration between alum who participated in the Urban Education Program and similar alum who did not participate. The pilot survey should take approximately 15-20 minutes to complete. This pilot is being conducted as a validity test of the survey instrument. There is an open-ended comment box at the end of each survey section. Please feel free to provide comments on your thoughts regarding the survey. Your responses and comments responses will be valuable to ensure the efficacy of the survey instrument and, as such, are greatly appreciated. For your convenience, the following link will take you to the consent form and survey: www.linkhere.com Please respond to this email with a subject line of “Remove” in order to opt out from future emails regarding this research project. Your participation in this study will be handled in a confidential manner. Any reports or publications based upon this research will only use group data and will not identify you. If you do not participate or if you decide to quit, there will be no penalty. Your participation in this research is very much appreciated. Upon completion of the survey you will receive a separate thank you email as a token of appreciation for your participation. My research study was reviewed and approved by the Northeastern University Institutional Review Board (IRB# TBD). Please feel free to contact me with any questions. Sincerely,
Meaghan L. Arena Northeastern Doctoral Candidate College of Professional Studies – Doctor of Education Program [email protected] 413-572-8355
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Appendix G – Pilot Survey Thank You – Via email.
Dear Colleague:
Thank you very much for participating in my research study. Your participation has helped to refine the survey questions for WSU alum who will also take this survey. Again, thank you very much. Your participation is greatly appreciated. Sincerely,
Meaghan L. Arena Northeastern Doctoral Candidate College of Professional Studies – Doctor of Education Program [email protected] 413-572-8355
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Appendix H – Survey Instrument
Please respond to the survey only once.
5: Strongly Agree, 4: Somewhat Agree, 3: Not sure, 2: Somewhat Disagree, 1: Strongly Disagree
1. Most of my courses at Westfield State University were intellectually stimulating.
5 4 3 2 1
2. I am satisfied with my academic experience at Westfield State University.
5 4 3 2 1
3. I am more likely to attend a cultural event (e.g., a concert, lecture, or art show) now as compared to before college.
5 4 3 2 1
4. I am satisfied with the extent of my intellectual development while at WSU.
5 4 3 2 1
5. In addition to required reading assignments, I read many of the recommended books for my courses at WSU.
5 4 3 2 1
6. My interest in ideas and intellectual matters increased during my time at WSU.
5 4 3 2 1
7. I had an idea about what I wanted to major in during my Freshmen year.
5 4 3 2 1
8. My academic experience at WSU has positively influenced my intellectual growth and interest in ideas.
5 4 3 2 1
9. Getting good grades was important to me during my time at WSU.
5 4 3 2 1
10. While at WSU, I performed academically as well as I anticipated.
5 4 3 2 1
11. My interpersonal relationships with other students while at WSU has positively influenced my intellectual growth and interest in ideas.
5 4 3 2 1
12. I developed close personal relationships with other students while at WSU.
5 4 3 2 1
13. The student friendships I developed at WSU were personally satisfying.
5 4 3 2 1
14. My personal relationships with other students while at WSU positively influenced my personal growth, values, and attitudes.
5 4 3 2 1
15. It was easy for me to meet and make friends with other students during my time at WSU.
5 4 3 2 1
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16. During my time at WSU, I was satisfied with my dating relationships.
5 4 3 2 1
17. During my time at WSU, many students I knew would be willing to listen and help me if I had a personal problem.
5 4 3 2 1
18. Most students at WSU had values and attitudes similar to mine.
5 4 3 2 1
19. I was satisfied with the opportunities to participate in organized extra-curricular activities while at WSU.
5 4 3 2 1
20. I was happy with my living/residence arrangement at WSU. 5 4 3 2 1
21. I was satisfied with opportunities to meet and interact informally with faculty members while at WSU.
5 4 3 2 1
22. Many faculty members I had contact with at WSU were willing to spend time outside of class to discuss issues of interest and importance to students.
5 4 3 2 1
23. I developed a close, personal relationship with at least one faculty member while at WSU.
5 4 3 2 1
24. My non-classroom interactions with faculty members while at WSU positively influenced my intellectual growth and interest in ideas.
5 4 3 2 1
25. My non-classroom interactions with faculty members while at WSU positively influenced my personal growth, values, and attitudes.
5 4 3 2 1
26. My non-classroom interactions with faculty members while at WSU positively influenced my career goals and aspirations.
5 4 3 2 1
27. Many faculty members I had contact with while at WSU were genuinely outstanding or superior teachers.
5 4 3 2 1
28. Many faculty members I had contact with while at WSU were genuinely interested in students.
5 4 3 2 1
29. Many faculty members I had contact with while at WSU were genuinely interested in teaching.
5 4 3 2 1
30. Many faculty members I had contact with while at WSU were interested in helping students grow in more than just academic areas.
5 4 3 2 1
31. During my time at WSU, it was important for me to graduate from college.
5 4 3 2 1
32. It was important for me to graduate from Westfield State University specifically.
5 4 3 2 1
33. I am confident that I made the right decision in choosing to attend WSU.
5 4 3 2 1
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34. Are you male or female?Male Female
35. What year did you graduate from WSU?
2005 2006 2007 2008 2009 2010 2011 2012I did not graduate
36. How many years were you enrolled at WSU before you graduated?
Less than 4 years 4 yearsMore than 4 years
but less than 6 years
6 yearsMore than 6 years
I did not graduate
37. Did either your mother or father earn a college degree?
Yes, my mother earned a degree
Yes, my father earned a degree
Yes, both my mother and father earned a degree
No, neither my mother or father earned a degree
I am not sure
38. Did you receive need-based financial aid (loans, Pell grants, work study, etc) at any point in your time at Westfield State University?
Yes No I am not sure
39. Do you speak English as a second language?
Yes No
40. While attending Westfield State University, did you have a documented learning disability?
Yes No I am not sure
41. Did you participate in the Urban Education Program while at WSU?
Yes No
41b. If yes, please use the scale to the right of the statement and indicate the extent of your agreement or disagreement with this statement:The Urban Education program was instrumental in my graduation from WSU.
5 4 3 2 1
42. Reflecting on your time at WSU and/or your participation in campus offerings such as the Urban Education Program, please provide any thoughts you may have on what seemed instrumental to your successful graduation: 43. Please provide your email address. Your email address will not be connected to your survey answers in any way and will only be used to inform you if you have won the gift certificate raffle:
Thank you for participating in this survey. If you’d like a copy of the final report, please email
this request to [email protected]. Winners of the gift certificates will be informed via
email in approximately 4 weeks.