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Examining the relationship between Latinx community college STEM students’ self-efficacy, social capital, academic engagement and their academic success

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Examining the relationship between Latinx community college STEM students’ self-efficacy, social capital, academic engagement and their academic success

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Content Running Head: LATINX STEM STUDENTS AND ACADEMIC SUCCESS

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EXAMINING THE RELATIONSHIP BETWEEN
LATINX COMMUNITY COLLEGE STEM STUDENTS’
SELF-EFFICACY, SOCIAL CAPITAL, ACADEMIC ENGAGEMENT AND THEIR
ACADEMIC SUCCESS

by

Marina Daniela Rueda Juarez
__________________________________________________________________

A Dissertation Presented to the
FACULTY OF THE ROSSIER SCHOOL OF EDUCATION
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF EDUCATION

August 2019

© 2019 Marina Daniela Rueda Juarez
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Dedication
I dedicate this to all my students - past, present and future, and to my future
children… in the hardest of times, when I wanted to give up, you were my motivation to
keep on going. If I can do this, you can too!
¡Sí se puede!

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Acknowledgements
I would like to thank my committee - Dr. Lawrence Picus, Dr. Gisele Ragusa and
Dr. Armando Rivera-Figueroa. To my family, Moms in particular, thanks for your
unwavering love, there’s nothing like it! Pops, “sanks”. Sista, thanks for listening, and
being the only one who could truly understand my process. Bro, I’m finally done, and
now I’m waiting for that screenplay! Becca, thank you a million times over for the
motivation and the help! To my amazing in-laws - ¡Mil gracias por su amor y su apollo!
Enrique, my dear husband, I could not have done this without you. To all my friends,
who have been there with kind words, and motivational texts (Boo, special shout out to
you in particular), I thank you for your love and support every step of the way. To all the
amazing figures who paved the way for a Xicana like me to even have this opportunity;
may your spirit live on through my life’s work and commitment to education.

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Table of Contents
List of Tables ...................................................................................................................... 5
Abstract ............................................................................................................................... 7
Chapter One: Introduction .................................................................................................. 8
Statement of the Problem ................................................................................................ 8
Purpose of the Study ..................................................................................................... 12
Research Questions ....................................................................................................... 14
Significance of the Study .............................................................................................. 14
Limitations .................................................................................................................... 15
Definition of Key Terms ............................................................................................... 16
Chapter Two: Literature Review ...................................................................................... 18
Current State of Hispanic/Latinx, Chicanx population in STEM Education ................. 20
Conceptual Framework .................................................................................................. 22
Social Cognitive Approaches: Self Efficacy ................................................................. 23
Social Capital ................................................................................................................ 25
Institutional and Contextual Factors: Academic Engagement ...................................... 27
Academic Success ......................................................................................................... 30
Conclusion .................................................................................................................... 31
Chapter Three: Methodology ............................................................................................ 32
Context of the Study ..................................................................................................... 32
Sample........................................................................................................................... 35
Study Design ................................................................................................................. 35
Instrumentation ............................................................................................................. 35
Data Collection Procedures ........................................................................................... 39
Ethical Considerations .................................................................................................. 41
Chapter Four: Findings ..................................................................................................... 42
Background Characteristics of the Sample .................................................................. 42
Relationship of Background Variables to Academic Success ..................................... 54
Characteristics of the Independent Measures .............................................................. 56
Summary ...................................................................................................................... 58
Chapter Five: Discussion And Conclusions ..................................................................... 59
Summary ....................................................................................................................... 59
Discussion of Significant Background Variables ......................................................... 59
Discussion of Self-Efficacy and Academic Success ..................................................... 61
Discussion of Social Capital and Academic Success ................................................... 62
Discussion of Academic Engagement and Academic Success ..................................... 63
Limitations .................................................................................................................... 64
Delimitations ................................................................................................................. 65
Recommendations for Future Research ........................................................................ 66
Implications for Practice ............................................................................................... 67
Conclusion .................................................................................................................... 67
References ......................................................................................................................... 69
Footnotes ........................................................................................................................... 84

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List of Tables

Table 1: Number of Semesters/Years Participants Spent in College ................................ 43
Table 2: Number of Breaks Participants Took From College .......................................... 43
Table 3: Gender of Participants ........................................................................................ 44
Table 4: Age of Participants ............................................................................................. 44
Table 5: Marital Status of Participants .............................................................................. 45
Table 6: Whether Participants Have Children .................................................................. 45
Table 7: Whether Participants Have a Disability .............................................................. 46
Table 8: Generation and Citizenship of Participants ........................................................ 46
Table 9: Where Participants Grew Up .............................................................................. 47
Table 10: Location Participants Lived Most of Their Life ............................................... 47
Table 11: Type of High School Participants Attended ..................................................... 48
Table 12: Father/Male Guardian's Highest Level of Education ....................................... 49
Table 13: Mother/Female Guardian's Highest Level of Education .................................. 50
Table 14: High School or Junio High School Dropout in the Home ................................ 50
Table 15: Veteran of the U.S. Military ............................................................................. 51
Table 16: Participation of STEM Summer Academy ....................................................... 51
Table 17: Participation in Summer Research .................................................................... 52
Table 18: Whether Participants Were a Foster Child ....................................................... 52
Table 19: AR 540 Eligibility............................................................................................. 53
Table 20: Participants Work Status................................................................................... 53
Table 21: Analysis of Background Variables ................................................................... 55
Table 22: Mean and Standard Deviation for Measured Variables .................................... 56
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Table 23: Correlation for Measured Variables ................................................................. 57

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Abstract
As part of a larger longitudinal community college investigation involving evaluation of
programming and services designed to increase STEM achievement, particularly for
Latinx, socioeconomically disadvantaged students, this study examines the relationships
among Latinx community college STEM students’ background variables, as well as their
self-efficacy, social capital, academic engagement, and academic success. The analyses
indicated that there were significant relationships among several background variables
and academic success. In addition, the regression analysis indicated that all 3 independent
variables (self-efficacy, social capital, and academic engagement) were significant
predictors of the dependent variable, academic success. Overall, these findings indicate
that it will be important for administrators in higher education to address behavioral
patterns of these students with regard to participation in summer programming and
research opportunities, as well as working less. Additionally, it is imperative to continue
to target females, those who have the presence of a high school or junior high dropout in
the home, and AB540 students, to gear them towards success. In light of the findings,
institutions of higher education should focus on these salient factors in order to increase
the potential for academic success among Latinx community college STEM students.
Furthermore, it will be important not only for community colleges, but also any
institution of higher education, to work to improve student self-efficacy, social capital,
academic engagement, as a primary factors that have the potential to impact academic
success, particularly for Latinx STEM students.

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CHAPTER ONE: INTRODUCTION
Statement of the Problem
Currently, there are significant disparities in higher education attainment in the
U.S., with respect to race, ethnicity, and socioeconomic status, especially in the areas of
science, technology, engineering, and math (STEM). On average, for every 100
Hispanic
1
elementary students in the United States, only 46 graduate from high school. Of
these, only 26 enroll in college. Of these 26 students, 17 enroll into community college,
and of that, only one transfers to a university (Yosso & Solorzano, 2006). This is likely
due to the fact that less than 50 percent of Hispanic high school graduates will even
qualify to enroll at a four-year institution immediately following graduation (President’s
Advisory Commission, 2002). However, research does suggest that students of color and
those of low socioeconomic backgrounds continue to disproportionately attend
community college after high school. Unfortunately, they are much less likely to
complete a degree than others (Hagedorn, Moon, Cypers, Maxwell, & Lester, 2006; PEW
Research Center, 2018). Not surprisingly, the numbers are even more troubling for
students pursuing Science, Technology, Engineering, and Math (STEM) degrees, as
Hispanic students remain an underrepresented minority in STEM degree attainment (U.S.
Commission on Civil Rights, 2010).
According to The U.S. Department of Education (2008), among first-time
freshmen who declared their primary goal as “transfer to a four-year college”, 39% left
college without attaining any type of degree. Additionally, only 30% achieved their goal
to transfer. The numbers are even more daunting for Latinx students in California, where

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only 14% successfully transfer, and that is within a six-year timeframe (Moore &
Shulock, 2010). Additionally, according to literature which explores the role of diversity
in the STEM workforce, projections for the labor market are likely to grow faster in
STEM than any other area; thereby reinforcing the notion that minority participation in
STEM education should become a priority (Hrabowski, 2011).
Now, more than ever, STEM skills are necessary for the U.S. to compete in the
expanding global economy, as it is estimated that through 2020, STEM occupations will
increase by 17%. At present, there are two STEM positions for every qualified job
seeker, according to the U.S. Congress Joint Economic Committee (JEC) (2012).
Furthermore, approximately one million more college graduates in STEM disciplines are
needed just to sustain the current economic U.S. productivity, yet, nearly 60% change
their mind about STEM interest within the first year of high school (My College Options
and STEM Connector, 2013). Despite the need, it will be difficult for the U.S. to
compete with the ever expanding international market, given that children in this country
are scoring lower in math and science as compared to their counterparts in other
industrial countries (Organization for Economic Cooperation and Development, 2010).
As a likely impact of continued subpar math and science achievement at the secondary
level, insufficient numbers of students, especially Hispanics, are pursuing STEM degrees
to compete for these growing STEM positions. That is, although in 2010, Hispanics
accounted for 16% of the U.S. population, only 8 percent earned STEM certificates
and/or degrees between 2009 and 2010 (NCES data, 2010). Hispanic Serving
Institutions
2
(HSIs) in particular, have a great potential to increase STEM degree

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attainment for Hispanic students, since approximately half currently attend an HSI
(Dowd, Malcolm, & Bensimon, 2009) and 40 percent of the undergraduate degrees which
are awarded to Hispanics, are granted by HSI’s (Dowd, Malcolm & Macias, 2010).
To further demonstrate the disparity in STEM representation, in the biological
sciences and mathematics/physical sciences, approximately 80% of those who hold four-
year degrees are White (Choy & Bradburn, 2008). Furthermore, according to researchers,
Hispanic students are less likely to earn undergraduate degrees in biological and life
sciences, computer and information sciences, engineering, and the health professions and
related sciences (Llagas & Snyder, 2003). Community colleges are of particular
importance for further inquiry because over 50% of freshman and sophomores in higher
education enroll in community colleges as a means to facilitate transfer to a four year
institution and ultimately, four year degree attainment (Berkner, He, Cataldi, & Knepper,
2002). The majority of Hispanic students (68%) attend a community college, (Pew
Hispanic Center, 2005) and comprise 58% of those currently enrolled at 2-year colleges,
as compared to White students, who comprise 42 percent (Snyder, Tan & Hoffman,
2006).
The disparities in STEM achievement are more troublesome in light of the
changing demographics in the country. Presently, it is estimated that nearly 30% of the
U.S. population will be Hispanic by the year 2050 (Aizenman, 2008). California in
particular is one of the most densely Latino/a Hispanic populated states in the U.S.
(Census, 2010); it is estimated that nearly 45 percent of California’s population will be
Latinx by 2060 (California Department of Finance, 2018) and is therefore of particular
interest to better understand disparities in educational outcomes for this population.
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The state of California (among other states) funds several support programs to
help increase Latinx student success and retention in STEM fields, and more specifically,
to pursue and successfully obtain 4-year STEM degrees. The state funded grant
programs, such as the Mathematics, Engineering and Science Achievement (MESA)
Program, (the MESA Community College Program (MCCP) branch of the MESA
program in particular), in partnership with the MESA Schools Program (MSP) and
MESA Engineering Program (MEP), serve to provide academic guidance and support
resources to facilitate four year STEM degree completion for underrepresented and
underserved populations in STEM education. The MESA program specifically targets
financially and educationally disadvantaged underrepresented minority students, with the
MCCP’s primary focus on community college students and their transfer to four-year
institutions in calculus-based science, technology, engineering and math related majors,
more commonly referred to as STEM majors.
STEM degree achievement for underrepresented minorities, and the Latinx
population in particular, is a complex issue; it is likely that a variety of institutional
factors are involved in explaining existing patterns, including resource allocation,
instructional quality, availability of support services, and institutional receptivity to
underrepresented students. However, other key factors related to individual students
include cognitive, motivational, and sociocultural factors as well (Pascarella & Terenzini,
2005; Hattie, 2009). Currently, the relative contributions of these factors to overall
STEM achievement is not well understood (Kruse, et. al, 2015)
With the vastly growing and changing global economy, and increasing population
density, it is imperative that the United States continue to grow its STEM educated
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population to compete on an international scale. Because California has an ever-
increasing Hispanic/ Latino/a population, and many of these students begin their higher
education journey at the community college, it is important to better understand the key
factors that affect minority student STEM degree attainment and to investigate the factors
which may contribute to the successful completion of STEM degrees.
Purpose of the Study
The influences on the academic success of STEM students, especially within the
community college sector, have not been thoroughly explored (Starobin, Laanan, &
Burger, 2010; Kruse, et al, 2015). There is a critical need to investigate the influences,
and relative contributions to academic success further, in order to gain a clear
understanding of how to improve and increase “success” which ultimately leads to STEM
degree attainment among these populations. Therefore, the goal of this study was to
investigate the relationships among these influences, and to assess their relative
contributions in predicting academic success.
This study was part of a larger longitudinal community college investigation,
involving evaluation of programming and services provided by three separate federally
funded grants designed to increase STEM achievement, particularly for Hispanic/
Latino/a and/or socioeconomically disadvantaged students. Two of the grants were
funded by the Department of Education, and the other grant, by the National Science
Foundation (NSF). The goal of these grants
3
was to increase 4-year STEM degree
attainment for Latinx students enrolled at a community college in the Western United
States. For this research, the community college of interest has been given the

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pseudonym Shaolin Community College (SCC) in order to aid in preserving the
confidentiality of participants, and anonymity of the institution. As an institutionalized
program at SCC, the Mathematics, Engineering and Science Achievement (MESA)
Program serves as the central hub for any incoming state or federally-funded grants
related to STEM student success and retention, especially those for underrepresented
groups, at the college. Through these supplemental grants, MESA program staff and
administration are able to disburse services, resources, and support programming to the
STEM students of the college, per grant guidelines.
As noted earlier, both institutional and individual factors are implicated in STEM
achievement. This study focused on individual factors which have been shown to be
related to achievement in general. The present study explored the relationships between
Latinx community college STEM students’ self-efficacy, social capital, and academic
engagement and their academic success. The literature has suggested that these are
particularly salient factors for Hispanic/ Latino/a students and will be further discussed in
the literature review. The purpose of this study was to understand the relationship
between students’ background and their academic success, as well as how these three key
variables (self-efficacy, social capital and academic engagement) relate to student
success, as measured by student’s STEM grade point average.
An important yet understudied variable included in this study, was academic
engagement. This variable was based on how much students took advantage of several
grant funded programming opportunities and resources provided conjointly by the
aforementioned grants. These resources were designed to serve as a means to
systematically decrease issues affecting underrepresented minority community college
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STEM student success, and address student needs. A research study such as this provides
great insight to how use of these resources relates with the ultimate goal, which is to
move students successfully through a rigorous STEM curriculum to complete a four year
degree in a STEM discipline. Naturally, in order to be able to transition successfully from
the community college to a university, these STEM students will need to acquire at
minimum, a satisfactory STEM G.P.A., thus underscoring the importance of the key
dependent variable in the study.
Research Questions
1) What is the relationship between STEM students’ background characteristics and
their academic success?
2) What are the relationships among community college STEM students’ self-
efficacy, social capital, academic engagement and their academic success?
3) What are the relative contributions of STEM students’ self-efficacy, social capital
and academic engagement in predicting their academic success?
Significance of the Study
Across the U.S., various colleges and universities are granted state and federal
funds to research and implement strategies that may potentially lead to increased student
retention and success rates in STEM, and many of these target underrepresented
minorities. In general, it is expected that at least some component of these grants become
institutionalized within the college or university. Therefore, it is critical to investigate the
outcomes, in order to better understand if and how they should be replicated, altered,
institutionalized, or even discontinued in future practice. This particular research project
is important because it adds to the foundation of knowledge about ways in which to better
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understand contributions to underrepresented minority STEM student success, and
ultimately, 4 year STEM degree attainment and completion. By understanding the
relationships and relative contributions of self-efficacy, social capital and academic
engagement, all of which are critical components of the higher education student
experience, this research project provides additional insight to the relationship of these
key factors to the success of Hispanic/ Latinx, and Chicanx STEM students.
Limitations
The primary data for this study consist of student self-reported information, thus,
there is a limitation in the ability to control for student honesty in their responses. It is not
possible to assure complete and thorough reflection on the students’ part. As a second
limitation, students from this study were not from a single cohort, but rather, come from
across various stages in their education
4
, and some may have even attended other colleges
throughout any given point in their educational path thus far. An additional factor
limiting the generalizability of the results is the context for this study; it was carried out
in a single large, urban, rather homogenous community college in the Southern California
region, and focused specifically on Latinx STEM students. Therefore, the findings may
not generalize to other schools or populations that are not similar to those in the present
study. These limitation items will be addressed further in the discussion section in a later
chapter.

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Definition of Key Terms
Academic engagement: a combined score that represents a student’s degree of
participation in a multitude of pedagogical practices and utilization of program resources
available to them at the college.
Community college student: a student who is attending a community college.
MESA Program: an acronym for the Mathematics, Engineering and Science
Achievement Program, a state grant funded program which provides programming and
services designed to increase retention of educationally disadvantaged students pursuing
4 year STEM degrees and to the extent possible by law, targets groups with low four-year
eligibility rates.
Self-efficacy: The belief in one’s ability to succeed in a particular situation;
determinants of how one thinks, behaves, and feels (Bandura, 1997).
Social capital: intangible resources such as social networks, or connections which
have potential value to one’s social mobility.
STEM: a commonly used acronym for Science, Technology, Engineering and
Mathematics, referring typically to, and in context of this study, those who are majoring
in science, technology, engineering or math disciplines.
Academic success: this study used self-reported student Grade Point Average
(G.P.A.), with at least a 2.0 indicated as passing, as a proxy to measure success. In
particular, the student’s STEM G.P.A. was used, which is a G.P.A. compiled purely of
STEM courses (that is, any science, technology, engineering or math course taken at the
college level); this excludes basic skills/ remedial STEM prerequisites. STEM G.P.A.
was used as it pertains specifically to STEM students. Three other types of G.P.A. were
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also requested in the survey data, including: overall G.P.A., community college G.P.A.
and transfer G.P.A. However, these were not used in this analysis, as they are not as
critical to the ability of a community college STEM student to transfer to a university, as
that of the STEM G.P.A. specifically.

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CHAPTER TWO: LITERATURE REVIEW
As early as 1957, with the Soviet Union’s successful launch of Sputnik, the Dawn
of the Space Age began. In this new era came heightened value for capable scientists,
engineers, and mathematicians within the United States, fueled by the goal of becoming a
top competing nation in the expanding global economy. Continuing to build on this goal,
in 2010 President Barack Obama emphasized the role that education plays in lowering
poverty, recommending investment in community college reform in particular, to make it
happen. A report from the President’s Council of Advisors on Science and Technology
(PCAST, 2012) urged colleges and universities to focus on producing more STEM
graduates; it was noted that if our nation is to remain competitive in STEM, as the
economy continues to change, it will need 1 million more STEM professionals through
the next decade. Naturally, this pertains to the role that community college transfer
institutions play in meeting STEM workforce needs, an argument also made in National
Academies reports (National Academies of Science, Engineering, and Medicine, 2016;
National Academy of Engineering, 2015).
At the third Annual White House Science Fair (April 2013), President Obama
noted the need to focus on creation of, “…an all-hands-on-deck approach to science,
technology, engineering, and math…” a response to the fact that the U.S. has one of the
lowest globally comparative rates of STEM degree production, with only 17% of STEM
degrees awarded in 2002, as compared to an international average of 26% (Kuenzi,
2008).
Community colleges are important because they enroll higher numbers of
Hispanic/ Latino/a and first generation students than do 4-year institutions (Pascarella &
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Terenzini, 2005, PEW Research Center, 2018). According to The National Science
Foundation (NSF, 2015) community colleges are identified as an important entry point
for advancement to doctoral degree attainment. For example, 14% of Latino Ph.Ds. in
STEM fields began their education at a 2-year college (Hill, 1992). Additionally, students
with at least one parent holding a bachelor's degree or higher earn more STEM-related
degrees than do first generation students. Among mathematics/ physical science
graduates, over 60% had parents who also possessed a bachelor's degree or higher; and in
the biological sciences, over 50% had parents with a bachelor's degree or higher (Choy &
Bradburn, 2008). In order to accomplish reform, and increase the number of
underrepresented minority graduates pursuing STEM degrees, especially Hispanic/
Latinx, Chicanx students who will soon make up a majority of our nation’s population, it
is imperative that the factors influencing the success of these STEM students be
identified and investigated further. This information can serve as the foundation to tailor
practices and policies and ultimately, institutionalize components that will serve in the
best interest of students where possible.
The focus of this study is STEM achievement with Hispanic/Latinx, Chicanx
students in a community college setting. The specific purpose was to investigate the
relationships and relative contributions between self-efficacy, social capital, academic
engagement, and academic success. Thus, this chapter provides a foundation for the
study, including an understanding of the current state of STEM education, especially as it
pertains to Hispanic/ Latinx, Chicanx students, an overall conceptual framework, and a
brief overview of existing work on self-efficacy, social capital, academic engagement,
and academic achievement.
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Current State of Hispanic/Latinx, Chicanx population in STEM Education
It is projected that by the year 2060, the Latinx population will represent 31% of
the total U.S. population (129 million) (U.S. Census Bureau, Population Division, 2012).
However, women and minorities continue to be underrepresented in STEM fields
(Huang, Taddese, & Walter, 2000). It has been noted that between 2004 and 2013, the
number of Latinos earning at least an associate’s degree has increased by 71% (from 3.8
million to 6.8 million). In 2012, Latinos represented 20% of students enrolled in
community colleges; overall, Latinas earned more bachelor degrees than did their male
counterparts, however, they earned less in STEM disciplines. However, despite the
increase, Latinos still remain the lowest attaining group among others, comparatively,
with only 22% earning at least an associates degree; compared to Asians (60%), Whites
(46%), and African Americans (31%) who have earned at least an associates degree or
higher (U.S. Census Bureau, Current Population Survey, 2013). More specifically, the
Latinx student population is the largest minority underrepresented in the STEM
disciplines (National Science Board, 2016).
The U.S. high school dropout rate has fallen to just 6% in 2016, with the Hispanic
population accounting for a substantial portion of that decrease. However, Hispanics still
remain as the highest dropout group among White, Black, Hispanic and Asian students
(PEW Research Center, 2017). With the decrease in high school dropouts, the nation has
seen an increase in college enrollment among Hispanic students. The number of Hispanic
high school graduates between the ages of 18-24 went up from 32% in 1999, to 47% in
2016. Almost 50% of Hispanic students who enroll in college, do so at the community
college, as opposed to a university; this is higher than any other ethnic group, wherein
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only 30% of white, 32% of Asian and 36% of black students, respectively, enroll into a
community college. However, despite the increased college enrollment, they are still less
likely to actually obtain a four year degree (PEW Research Center, 2018). As a result,
community colleges play a critical role in the attainment of STEM education, especially
for Hispanic students (Hagedorn, Purnamasari, & Eddy, 2012).
National educational statistics consistently show underrepresentation of Hispanics
in STEM degree attainment. A report from the National Action Council for Minorities in
Engineering (NACME, 2008) for example, notes that there has been a steady decline.
One study, supported by the National Science Foundation, shows that the percentage of
bachelor's degrees in engineering awarded to underrepresented minorities significantly
declined between 1995 and 2005. It was reported that 5.5% of Hispanics received
engineering degrees in 1995; however, only 4.2% received them just 10 years later in
2005 (Frehill, DiFabio, & Hill, 2008). In 2011-12, Latinas earned 60% of all bachelor’s
degrees awarded to Latinos, yet only 37% of these were in STEM fields. The National
Science Foundation (2010) reported that only 10% of Hispanic/ Latino/a graduates
earned a bachelor’s degree in a STEM field. Additionally, Latinas earned fewer
bachelor’s degrees in the fields of computer science, engineering, and mathematics than
did Latinos. Of all bachelor degrees earned by Latinos in 2011-12, Latinas earned 45% of
these in mathematics, 21% in engineering, and 19% in computer science (NCES, Digest
of Education Statistics, 2013). According to a 2014 workshop from the National
Academy of Engineering, statistics on the Science and Engineering workforce were
discussed, indicating that both Whites and Asians are disproportionately overrepresented,
whereby Hispanic men only accounted for 3% and women 2% of the STEM workforce.
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Conceptual Framework
Though there are several existing models and frameworks which seek to
understand college persistence and success, currently, there is no single comprehensive
theory to explain the factors specifically influencing Hispanic/ Latinx, Chicanx students
attending community college; this is even less so, for Hispanic/ Latinx, Chicanx students
pursuing STEM majors. In fact, it was recommended in the work of Crisp & Nora (2012)
that,
“Additional research is needed to extend what is known regarding the
factors that predict persistence for Latino/a students with an interest in
STEM (both before and after college matriculation). In particular,
research is recommended that explores additional socio-cultural variables
influencing Hispanic students decisions to major and persist in STEM.
There is also a need for the development of theoretical frameworks to
explain Hispanic students’ decisions to major in and persist in STEM. (p.
12)”

Furthermore, a comprehensive review of several studies dating as far back as
1980 indicates that there are studies that focus on Latinx student success in community
colleges, Latinx students transferring from 2- to 4-year institutions, or STEM, however,
rarely are all three elements examined together (Martin, et. al, 2018). Consequently, the
conceptual framework guiding this research study comes from a collection of existing
models and theories from three major sources. The first framework is based on social
cognitive theory, specifically, the Triadic Reciprocality model (Bandura, 1977). This
framework focuses on internal cognitive and motivational factors which impact student
outcomes, for example, self-efficacy and engagement.
The second framework informing this study focuses on social capital; in
particular, this framework is based on the work of Bourdieu (1973) and later extensions
by other scholars who have built upon this work. These theorists focus on the social
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23
resources available to individuals as important factors in various outcomes including
social class.
Finally, the third framework is based on empirical and conceptual models
regarding community college processes and outcomes compiled from the work of Crisp
& Nora (2010), which seeks to provide further insight to Hispanic/ Latinx, Chicanx
success in STEM. These models and frameworks tend to focus on institutional and
contextual factors affecting student outcomes.
The present research study draws on these theories in an effort to develop a
comprehensive framework that adds to the knowledge of better understanding the
relationship between self-efficacy, social capital, and academic engagement and
Hispanic/ Latinx STEM student success. Each of these frameworks and related research
will be described in the remainder of this chapter.
Social Cognitive Approaches: Self Efficacy
Self-efficacy is a commonly researched motivational construct, and has been
shown to predict academic achievement across various academic domains. In fact, a
meta-analysis examining university students’ academic performance indicated that self-
efficacy had the strongest correlation (r = 0.59) in a review of 50 antecedents of academic
performance (Richardson, Abraham, & Bond, 2012). Thus, if we are to better understand
students’ potential for success in STEM, it is important to look at self-efficacy as a
variable of interest. Self-efficacy refers to one’s own “judgment of their capabilities to
organize and execute courses of action required to attain designated types of
performances (Bandura, 1986, p. 391).” Grounded in Bandura’s social-cognitive theory,
the Triadic Reciprocality model, (Bandura, 1986; Bandura 1977), the author describes
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24
self-efficacy in relation to a number of constructs, including persistence and goals/goal
setting (e.g., Multon, Brown, & Lent, 1991; Schunk & Ertmer, 1999), use of strategies
such as self-regulated learning (e.g. Pintrich & DeGroot, 1990), and achievement.
Research suggests that self-efficacy is important to students’ academic and social
adjustment as well as overall wellness and personal adjustment (e.g., DeWitz & Walsh,
2002; Gore, 2006; Solberg & Villareal, 1998). Research has also shown that self-efficacy
plays a key role in influencing students’ motivation for learning (Pajares, 1996; Schunk
& Pajares 2009; Unrau, Rueda, Son, Polanin, Lundeen, & Muraszewski, 2018). More
specifically, self-efficacy has been useful in predicting performance and motivation in
mathematics for Hispanic students (Stevens, Olivarez, Lan, and Tallent-Runnels, 2004).
Research also shows links between self-efficacy and outcomes are stronger when the
specificity of the efficacy assessment and the criterion matches (Choi, 2005; Pajares &
Miller, 1995). It is critical to note, however, that self-efficacy is domain specific, and
therefore, judgments are specific to tasks in a given specific context (Bandura, 1977,
1986, 1997). In this research study for example, the context is academic, as we are
interested in STEM education, and with regard to academic achievement, individuals
with higher levels of self-efficacy tend to be more motivated, and therefore, use more
strategies, which can ultimately, potentially lead to higher achievement.
Unfortunately, Hispanic students show lower levels of self-efficacy when it
comes to science and mathematics as compared to their White counterparts (Leslie,
McClure & Oaxaca, 1998; Stevens, et al, 2004). Solberg, O.Brien, Villareal, Kennel, &
Davis (1993), in their work on self-efficacy and adjustment for Hispanic students, define
self-efficacy in the context of academics as, “the degree of confidence students have in
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25
their ability to successfully perform a variety of college-related tasks” (Solberg et al.,
1993, p. 82). This was significant in that it allowed the researchers to measure the broader
college experience, instead of a singular aspect.
In order to get these broader measures, the College Student Self-Efficacy
Instrument (CSEI) was developed (Solberg et al., 1993). Extracting duplicate and
incomplete cases, the researchers collected CSEI survey data from 3,187 freshmen. The
total sample was then split into two random, independent samples (Sample 1 and Sample
2) in order to replicate the work. The final sample sizes, bearing similar demographic
composition, for Sample 1 and 2 were N = 1,586 and N = 1,585, respectively. The study
found the measure to be reliable and valid. In review of its validity, this measure was
used to look at the sample and better understand students’ self-efficacy scores. This tool
was used in the present study, in order to assess students’ self-efficacy for the specified
sample, using an average CSEI subscale score based on survey responses.
Social Capital
Psychological studies of motivation, including self-efficacy and engagement, tend
to focus on internal cognitive beliefs. However, where the literature is lacking, is an
understanding of the larger social and/or cultural context, as it applies to academic
achievement. The applications of social capital theory have been widely studied, and its
relationship to education builds from the contributions and body of work from various
sources (Bourdieu, 1986; Coleman 1988; Goldin & Katz, 1999). Although there are
connections to social capital and education, research lacks a focus on social capital as it
applies in higher education (Pusztai, 2015). Therefore, social capital was included in this
study, and a brief overview of what is thus far understood is provided here.
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26
Bourdieu (1973) is considered to be one of the founding theorists behind the
theory of “social capital” as he was the first to introduce the concept systematically. As
defined by Bourdieu (1973), Social Capital is what is gained from ones access to
knowledge and certain social networks necessary to succeed. In the context of education,
these networks can include parents, teachers, advisors, and peers/ friends; the manner in
which the interactions within these groups influence students’ expectations of themselves
and even their sense of how they may fit within that particular academic environment
(Bourdieu, 1973); essentially, social capital refers to resources that are gained through
membership in a particular group.
Parental education, for example, is thought to play a role in students’ success, as it
ties directly to a student’s ability to navigate the college environment (Berger, 2000;
Logerbeam, Sedlacek, & Alatorre, 2004; Pascarella et al. 2003). Research has shown that
family support systems play an integral role for minority students in developing and
encouraging interest in STEM careers (Catsambis, 1994). In fact, it has been found that
Hispanic males exhibit a much greater likelihood of pursuing engineering or physical
science as a major/ occupation, in households where at least one parent already holds a
similar position (Leslie, McClure, & Oaxaca, 1998). Additionally, Rendon and Valdez
(1993) suggest that Hispanic community college students with immigrant parents, or
those who come from families with little understanding of the higher education system
are more likely to face barriers in the pursuit of 4-year transfer. Research suggests that
students who are well connected, and have access to elements of social capital, are more
likely to be successful. (Cole & Espinoza, 2008).
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Social Capital Theory provides context for a better understanding of how social
class may play a role in, and have a direct impact on Latinx student success, especially in
STEM disciplines. As a result, social capital was used as a primary independent variable,
as it plays an important role in better understanding student success for this particular
group of interest, Latinx community college STEM students.
Institutional and Contextual Factors: Academic Engagement
Crisp & Nora (2010) presented a comprehensive empirical and conceptual model
of community college outcomes, based on a compilation of research and prior
frameworks. These included Tinto’s (1993) Model of Student Integration, Nora’s (2003)
Student/Institution Engagement Model, and Bourdieu’s (1973) Cultural Capital Theory,
as well as conceptual models that are more specific to the Latinx population of students
(e.g., Nora and Garcia 2001; Torres 2006).
Federally defined as institutions of higher education that enroll at least 25% of
Latinx students, Hispanic Serving Institutions (HSIs) serve as a critical access point for
Latinx students; they currently enroll 60% of all Latinx students in college (Calderón
Galdeano, & Santiago, 2013). However, research also suggests, that despite demographic
changes indicating higher numbers of Hispanic student enrollment in higher education,
organizational structures in place are not growing and changing at the same rate, to
address the needs of the growing population (Contreras, Malcom, & Bensimon, 2008;
Malcom, 2010; Santiago, 2012). Therefore, the opportunities for academic engagement
that any given institution of higher education might provide to students becomes
increasingly critical, in the wake of minimal or at some institutions of higher education,
non-existent resources.
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However, even if these resources are available, not all students use them. Those
who do are presumed to be more engaged. Astin (1977; 1984) notes that a student’s
involvement in the educational process, or, their academic engagement has a direct
influence on academic achievement and graduation rates; that is, the more engaged and
involved throughout their education, the greater the likelihood of success. Academic
engagement, for the purposes of this study, is operationally defined as reference to an
individual’s use of compilation of specific pedagogical practices taken directly from the
College Pedagogical Practices Inventory (CPPI) (Ragusa & Juarez, 2018) administered to
the participants of this study. The goal was to gather a mean score indicating use of these
practices participants consistently access; the more often they do, the more academically
engaged, they are. These pedagogical practices included:
 “Met with a college counselor”
 “Used any college’s tutoring services”
 “Did academic program planning”
 “Participated in student clubs or organization”
 “Went a study skills workshop”
 “Went to the school’s learning center”
 “Participated in school extracurricular activities”
 “Went to the college library”
 “Met with an academic advisor”
 “Participated in a writing workshop”
 “Met with a financial aid officer”
 “Participated in a college-based support group”
 “Used the internet or web to find information at school”
 “Participated in a school-based study group”
 “Participated in a STEM competition”
 “Participated in supplementary instruction”
 “Attended the English lab”
 “Worked with an EOP tutor”
 “Worked with a math tutor”
 “Participated in STEM clubs”
 “Participated in mentoring program(s)”
 “Visited the math lab”
 “Studied with a group”
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Access to resources such as those listed are important to facilitate academic engagement
for students on campus.
It is through the work of Tinto (1993) that the concept of “Student Integration” is
introduced in the higher education context. This framework places emphasis on
socialization factors. These socialization factors are essentially the pedagogical practices
also commonly referred to, especially in the context of this particular research project, as
“academic engagement”. It is through increased academic engagement, or, involvement
on and connection to the campus, that a student is more likely to complete their degree.
Tinto’s (1993) body of work provides a foundation upon which to better understand
academic engagement, and student success. However, this work has also been criticized
for its focus on traditional college aged White males, and does not really look at those
students who do not fit this mold (i.e. – women and students of color) (Rendon, Jalomo,
& Nora, 2001; Tierney 1992). Research as it relates to Latinx students especially tends to
lack the connections between social integration and persistence for these populations
(e.g., Nora 1987; Nora and Cabrera 1996; Nora, Cabrera, Hagedorn, & Pascarella, 1996).
It was not until the work of Torres (2006) that the Latinx population was looked at
through a model identifying the relationship between academic engagement and ones
commitment to their institution. It was found that the greater the “commitment” a student
exhibited to their institution, the greater chances for success.
With regard to STEM in particular, Gasiewski, Eagan, Hurtado, Chang & Garcia
(2012) used a mixed method approach to gain a better understanding of the relationship
between student engagement, and STEM instruction. Quantitative surveys were
administered to 2,873 students from 73 introductory STEM courses across 15 college
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30
and university campuses. Additionally, qualitative data were collected from students
through 41 focus groups across eight of the participating campuses. Findings showed
student tendency for higher engagement, where the instructor expressed consistent
openness to questions. Participants who reported feeling comfortable engaging in class
(i.e. – asking questions in class), seeking tutoring services and/ or supplemental
instruction, and collaborating with others were also more likely to be engaged.
The present study sought to better understand the broader impacts of this concept,
specifically at the community college level, and with Latinx STEM students, and its
relationship to the ultimate goal, student success.
Academic Success
A longitudinal study conducted by Chang, Sharkness, Hurtado & Newman
(2014), focused on the factors contributing to persistence of underrepresented minorities
in STEM disciplines. With a sample size of 3,670 students from across 217 institutions,
data came from two surveys: the Cooperative Institutional Research Program's 2004 "The
Freshman Survey" (TFS) and 2008 "College Senior Survey" (CSS). It was discovered
that among participants, Latinx participants were significantly less likely to persist in
their STEM majors than White and Asian students. Studies such as this show that it is
imperative to better understand the correlation to persistence and academic success for
these students, in order to aid in increasing their persistence.
Congruently, research suggests that one of the most influential factors in Hispanic
students’ decisions to persist in higher education attainment is their academic
performance (Nora and Cabrera 1996; Nora et al. 1996; Hu and St. John 2001); that is, as
Hispanic student G.P.A.s increase, they are more likely to persist. Because college grade
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31
point average (G.P.A.) serves as the most immediate, quantifiable measure of success, it
was used as the dependent variable as a proxy indicator for success in this study; more
specifically, the STEM G.P.A. was used, since it is students pursuing STEM degrees who
are the primary group of interest, and it is their STEM GPA which is the best indicator
for their potential to succeed in STEM degree attainment.
Conclusion
Based on the review of literature, it is clear that the variables of this study,
including self-efficacy, social capital and academic engagement are important in better
understanding academic success. Gaps in the research however, indicate that more work
is needed which focuses on Hispanic/ Latinx, Chicanx students, and STEM students in
particular, especially those at the community college level; what is known for this
population, is that the statistics for degree attainment (especially in STEM fields) are
troublesome, and consequently, there is a great need to better understand how to increase
the numbers of Hispanic/ Latinx, Chicanx students obtaining a higher education in STEM
disciplines, so that we may continue to compete in the global economy, with a highly
educated population that will match the population growth. This study contributes to the
existing body of knowledge on STEM Hispanic/ Latinx, Chicanx students and their
academic success in higher education.
The following chapter provides an overview of the study, including the design,
participants, measures, and data analysis.

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CHAPTER THREE: METHODOLOGY
This study was part of a larger longitudinal study, which investigated specific
components of a multi-dimensional questionnaire with several measurements within
(Ragusa, & Juarez, 2019). This study used a secondary analysis of an existing data set to
investigate the interrelationships among select independent variables (self-efficacy, social
capital, and academic engagement) and the dependent variable (success) each represented
as an averaged score gathered from responses within each set of Likert type scale
responses. The purpose of this chapter is to describe the methodology used in the present
study. The chapter introduces the context of the project, then presents the sample,
measures, and data analysis plan. As noted earlier, this study examined the following
research questions:
1) What is the relationship between STEM students’ background characteristics
and their academic success?
2) What are the relationships among community college STEM students’ self-
efficacy, social capital, academic engagement and their academic success?
3) What are the relative contributions of STEM students’ self-efficacy, social
capital and academic engagement in predicting their academic success?
Context of the Study
The study was carried out in a community college setting, located in an urban
region of Southern California. Shaolin is an urban community college, also a Hispanic
Serving Institution (HSI), located in an economically challenged, diverse region of the
Western United States. First time students come primarily from local feeder high schools,
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33
with historically subpar API (Academic Performance Index) scores
5
. The campus is fairly
homogenous in terms of ethnicity, student age, and economic background. Based on the
most recent information available, demographically, the student population of SCC is
comprised of 80.4% Hispanic, 12.4% Asian, 1.9% Caucasian, 1.6% African American
and 3.7% other and non-respondent. Of those, 58.1% are female, and the remaining
41.9% are male; just over 75% of the population is under the age of 30. Although the
primary language for the majority of the population is English (77.2%), there is also
Spanish (13.6%), Chinese (6.3%) and an additional 2.9% who note “other” as their
primary language. For the 2015-16 academic year, SCC enrolled 39,063 (head-count)

students, primarily from feeder schools ranked in the bottom 10% of the state;
approximately 73.3% attend on a part-time basis
6
. SCC’s service area includes more than
50,000 households below the poverty line (based on the 2010 Census). Additionally, of
the 39,063 students enrolled, just under 70% receive at least the California Board of
Governors Fee Waiver (BOGFW)
7
(Shaolin Community College, Fall 2015 Credit
Student Profile).
One of Shaolin’s institutionalized academic support programs includes the state
grant funded Mathematics, Engineering and Science Achievement (MESA) Program. The
MESA program serves as a central location for disbursement and implementation of all
STEM (Science, Technology, Engineering and Math) supplemental grants and resources
received by the college. The MESA program seeks to serve financially and educationally

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34
disadvantaged minority students
8
pursuing four year STEM degrees, and in so doing,
provides a wealth of programming and services to meet the needs of this population,
shown to have an effective impact on student success. These resources include (but are
not limited to): a designated STEM counselor who provides specialized educational
planning and course selection tailored to meet the needs of the STEM specific population
and prepare students for transfer; an orientation/ personal development course
9
; tutors
and Supplemental Instruction (SI) opportunities; assistance and guidance through the
transfer process; assistance and guidance navigating financial aid options, including help
and guidance securing scholarships; a textbook and calculator loan program
10
; university
and industry field site visits; STEM peer mentors
11
; a STEM study center space to create
a collaborative working environment and develop a STEM culture among students;
summer research/ internship opportunities for those who qualify.
Access to the MESA program/ field site, and to its program participants for this
research project was granted as a result of the involvement of key personnel. These key
personnel serve an interest in gaining access to information which helps to better
understand how the population noted in this research study is affected by support and
programming provided by the grant projects.

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35
Sample
The group from which the questionnaire responses were received wass a fairly
homogenous group of self-identified "Hispanic, Latino/ Chicano" students primarily from
within the same basic age range (18-25) from within the MESA program at Shaolin
Community College. Data was originally collected from 1,312 students, of which 946
identified themselves as "Hispanic, Latino/ Chicano". Because this study focused on the
Hispanic/Latinx population, the sample was reduced to 946. However of these 946
participants, only 572 responded to the survey question specifically pertaining to STEM
G.P.A., which is the variable representing success. Therefore n=1,312 of the returned
questionnaires, however, n=572 for the final analysis. More specific data on background
characteristics is provided in the following chapter.
Study Design
This study used a descriptive correlational design, employing multiple regression
and correlation analysis, as well as a Chi square analysis.
Instrumentation
The instrumentation used to compile the data set for this research study was
derived from a multi-dimensional questionnaire with several measurements within
(Ragusa & Juarez, 2019). Incorporated into the instrument are a combined measure of 5
scales and background characteristics designed to measure cultural factors that lead to
persistence in STEM majors (Ragusa & Juarez, 2019). These sections, include:
“Background and Socio-Demographic Information”, “College Self-Efficacy Instrument”,
“College Independence and Social Capital Index”, “College Pedagogical Practices
Inventory”, “Engineering Creativity and Propensity for Innovation Index” and finally, the
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36
“Engineering Global Preparedness Index”. The construct validity evidence of the
questionnaire items has been examined through assessment of the generalizability of the
dimensionality. External validity was also gathered through examination of the
relationships between its subscale scores and theoretically related criteria, which
supported most hypothesized relationships.
The “Background and Socio-Demographic Information” section of the
questionnaire asked participants to provide basic personal and demographic information
using both fill in as well as check box format questions. This section began with key
information used as the identifiers for each student; this information was compiled to
preserve participant confidentiality, yet simultaneously allowed researchers to have a
means through which to identify participants anonymously. These identifiers, compiled
through fill in from participants included: “First Name”, “Middle Initial” and “Mother’s
Month and Day of Birth.” Questions 1-25 go on to ask additional demographic
information such as gender, age, marital status, etc.
The “College Self-Efficacy Instrument”, based on the work of Solberg, et. al
(1993), asked about views on specific aspects of college life and subsequent confidence
engaging in college related tasks and activities. It contains 14 items and used both a
Likert type scale with possible scores ranging from 1) Strongly Disagree to 6) Strongly
Agree. In addition, this section included a check box question, “What is the biggest
hurdle that you have faced while in college?” adapted from the College Pedagogical
Practices Inventory (CPPI), based on the work of Ragusa & Juarez
(2018). For this question, students were asked to select only “ONE” of several options
which they recognize as the single “biggest” hurdle. These included 14 options with
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37
elements relating to: finances, time management, understanding content, family, work,
and personal hurdles.
The “College Independence and Social Capital Index” portion, based on the work
of Lopez & Lent (1991), asked for a rating of oneself, given specific social capital
variables, including, but not limited to “communication skills”, “ability to work well with
others”, etc. It contains 23 items and also uses a Likert type scale ranging from 1)
Strongly Disagree, to 6) Strongly Agree for each variable.
The “College Pedagogical Practices Inventory” section, based on the work of
Ragusa & Juarez (2018) which is referred to as the Academic Engagement variable in
this study, asked for estimated average amount of time engaged in particular activities
from within the last month. It contains 23 items and also uses a Likert type scale ranging
from 1) None to 6) More than 30 hours (per month). In addition to the Likert scale
questions, there are also check box questions, such as “Have you attended a summer
research experience”, and “Were you a foster child?”
Finally, there were two additional components that were not areas of focus for this
particular study, yet are described here, as they remain a part of the overall questionnaire.
The first area is the “Engineering Creativity and Propensity for Innovation Index”
(Ragusa & Slaughter, 2017), where participants are asked to indicate the extent to which
a given example of a perception about “aspects related to science and engineering
creativity and innovation” would most closely match the participants own experience or
perception. The second component of the index not included as part of this study is the
“Engineering Global Preparedness Index” (Ragusa, 2014) which focuses on “aspects
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38
related to science and engineering global preparedness” rather than “creativity and
innovation.”
For this study, the mean, standard deviation, and inter-correlations were
calculated for all variables, including demographic variables, social capital scale, self-
efficacy scale, and academic engagement score. The distributions of all variables were
also examined for non-normality. These are reported in the following chapter.
A set of questions were used to create a quantifiable score for both Social Capital
and Self-Efficacy. The questions used to define Self-efficacy in this study are provided
through an averaged score from question item numbers 26-39 of the aforementioned
measure with a total of 6 being the highest possible rating “Strongly Agree”, and 1 being
the lowest “Strongly Disagree”. Social capital was quantified through an averaged score
from question item numbers 41-64, also a total of 6 being the highest possible score
“Strongly Agree”, and 1 being the lowest “Strongly Disagree”. Finally, Academic
Engagement was quantified through an averaged score from question item numbers 65-
87, under College Pedagogical Practices. In the range of scores for the academic
engagement subscale, any given question may have had a score ranging from 1) None to
6) More than 30 hours (per month). The reliability of each of these subscales was also
calculated for the sample with self-efficacy (.847), Social capital (.833), and academic
engagement (.924).
This study used student STEM grade point average (G.P.A.), as provided by
participant responses to question 24 of the survey; this variable is an average of each
student’s reported G.P.A. in all Science, Technology, Engineering and/ or Math
coursework completed, on a 4.0 scale. For this study, a 2.0 G.P.A. was used as a proxy to
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39
measure success. This 2.0 value is used by the college as the minimum passing grade to
advance to the next level of study. It is also commonly used as a national norm to indicate
minimum competency in a course at the collegiate level, and used as a proxy for success
on a federal level, with regard to student financial aid eligibility.
Data Collection Procedures
The consent and questionnaires were administered and collected at the beginning
of the Spring 2013, Fall 2013, Spring 2014, Fall 2014, Spring 2015, Fall 2015, Spring
2016, Fall 2016 and Spring 2018 semesters. The questionnaire was administered to
students who, at the time of survey completion, were active members of the MESA
program at SCC. All active MESA members
12
at that time were asked to participate in
completing the questionnaire, in the event they provided consent without coercion to
participate. Additionally, participants were given adequate debriefing upon completion of
questionnaire administration. The total number of questionnaires initially distributed and
administered was N=1,312. However, the primary focus of this study is centered on those
who identified as “Hispanic/Latino/Chicano”, and of those, only 572 responded to the
survey item requesting a reported STEM G.P.A. As a result, the sample was n=572
useable surveys.
All data was compiled into an Excel spreadsheet. From the Excel spreadsheet,
data was then transferred into SPSS version 25 Statistical Analysis software. Once
transferred into the software, data were cleaned, accounting for and removing any
outliers. An initial step, was to identify the specific group of interest, the self-identified
“Hispanic, Latino/Chicano” participants (as noted in question item number10 of the

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40
survey). Therefore, all who identified themselves as anything aside from Hispanic (i.e.
that “of African descent”, “of Asian descent”, “of Pacific Island descent”, “Indigenous
People”, “of Arab or Middle Eastern descent” or “of Caucasian European descent, not
Hispanic”) were excluded from the sample in the data set, as they are not part of the
group of interest for this study. Of those who self-identified as “Hispanic,
Latino/Chicano”, only those who also responded to question 24, asking for a reported
STEM G.P.A. were included, as that was the primary dependent variable of interest for
this study.
The next step was to run the descriptive statistics, which included calculating the
mean, standard deviation and distribution of all relevant demographics from the data
provided from the questionnaire administered to participants. Because this research
sought to predict a single continuous dependent (criterion) variable (G.P.A.) using more
than one independent (predictor) variable (Self-efficacy score, Social Capital score and
Academic Engagement score), a multiple regression analysis was used to examine
questions 2 and 3 so that the relationship among the criterion and predictor variables
could be examined. Furthermore, the research assessed the relative contribution of each
independent variable on the criterion variable. The goal was to investigate if the three
independent variables (self-efficacy, social capital, and academic engagement) had a
statistically significant relationship with the dependent variable, (success), and therefore
could be used as an indicator to predict achievement.
For research question number one, however, a Chi-square test was performed.
STEM G.P.A., which is continuous, was split into 2 categories, thereby making it a
categorical variable. The median score was used to see where the even split would be, to
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41
separate the variable into a “high” range category and a “low” range category. In so
doing, the researcher was able to categorize the stem G.P.A., in order to perform the Chi-
square analysis with various background variables.
The data and findings that resulted from performing these statistical analyses are
presented in chapter four.
Ethical Considerations
This study involved a secondary analysis of an existing data set. The data do not
include identifying information, merely first name, middle initial, and mother’s month
and day of birth as participant identifiers. An Institutional Review Board process for this
research study was completed before data analysis commenced. Additionally, the
investigator underwent a required CITI Research Ethics and Compliance training in order
to meet all university and district procedures for ethical conduct, prior to the start of the
study. All data was purposely stored in locations only accessible to those who had
completed the IRB, and never e-mailed, shared electronically, or stored in any shared
drive or location otherwise potentially accessible by anyone who had not completed the
IRB process for this study. Therefore the risk of breaching confidentiality was minimized
to the extent possible.

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42
CHAPTER FOUR: FINDINGS
The goal of this study was to examine the relationships among Latinx community
college STEM students’ background variables, as well as their self-efficacy, social
capital, academic engagement, and their academic success. In this chapter, the results of
the research conducted, as well as the answers to the research questions presented in
Chapter one will be shared. The first section of the chapter presents information on the
background variables of the sample. The second section presents the results of the
analysis of the relationship of key background variables and the main dependent variable
through the use of Chi-square analyses. The final section, addressing research question
two and three, presents the results of the multiple regression analysis which examines the
relationship of the independent variables of the study and the main dependent variable.
Background Characteristics of the Sample
The sample in this study represented Latinx community college STEM students.
This section provides descriptive data on specific characteristics of those students. The
data reported in this section is based on the number of students who self-identified as
Hispanic, Latino/Chicano and who also reported a STEM G.P.A. (n = 572). In total,
there were 20 background variables. Each background variable described in this section
corresponds to a questionnaire item. Each background variable is presented in numerical
order, yet there are some survey question items that have been omitted; as determined by
the researcher, these omitted survey questions did not represent background information
of interest for this particular study.
The first background variable, presented as question one of the survey, asked
about the number of semesters completed at the time of the study. As shown in Table 1,
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43
where 547 responded, nearly 75 % of participants had been in college for at least 2 years,
of which, 54.4% had been in college for 3 years or more.
Table 1
Number of Semesters/Years Participants Spent in College

Frequency Percent Cumulative
Percent
1 semester 49 8.6 9.0
1 year 70 12.2 21.8
2 years 117 20.5 43.1
3 or more years 311 54.4 100.0
Total n in analysis 547 95.6
Total missing 25 4.4
Total 572 100.0

The second background variable, question two of the survey, asked if participants
had ever taken a break from college. Data from Table 2 shows that 567 respondents
provided useable information for this question. Of these participants, only 170, or 29.7%,
had taken a break at some point in their college education.
Table 2
Number of Breaks Participants Took From College

Frequency Percent Cumulative Percent
No 397 69.4 70.0
Yes 170 29.7 100.0
Total n in analysis 567 99.1
Total missing 5 9
Total 572 100.0

Question four of the survey asked about participants’ gender as the next
background variable. As shown in Table 3, of the 570 that answered the question, a
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44
majority of them self-identify
13
as male (62.6%), whereas 37.1% self-identify as
female.
Table 3
Gender of Participants

Frequency Percent Cumulative Percent
Male 358 62.6 62.8
Female 212 37.1 100.0
Total n in analysis 570 99.7
Total missing 2 .3
Total 572 100.0

The background variable represented in question five references age, asking
participants to indicate what age bracket they fall into. From the data shown in Table 4,
with 571 responses to this question, a majority of participants (48.3%) are between the
ages of 20-22. However, spanning across the first three age range brackets, nearly 90%
are between the ages of 18-25.
Table 4
Age of Participants

Frequency Percent Cumulative
Percent
18-19 140 24.5 24.5
20-22 276 48.3 72.9
23-25 98 17.1 90.0
26-30 37 6.5 96.5
31-35 14 2.4 98.9
36+ 6 1.0 100.0
Total n in
analysis
571 99.8
Total 572 100.0

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In the following background variable, derived from survey question six,
participants were asked about their marital status. Data reveals that with 570 who
answered this question, a majority of the group (96.2%) are single, having never been
married.
Table 5
Marital Status of Participants

Frequency Percent Cumulative
Percent
Single, never married 550 96.2 96.5
Married 9 1.6 98.1
Separated 6 1.0 99.1
Divorced 5 .9 100.0
Total n in analysis 570 99.7
Total missing 2 3
Total 572 100.0

The next background variable, taken from question seven, asks whether
participants have any children. As seen in Table 6 with 570 respondents, only 7.2
percent of the sample have children, whereas, the majority (92.5%) do not.

Table 6
Whether Participants Have Children

Frequency Percent Cumulative
Percent
No 529 92.5 92.8
Yes 41 7.2 100.0
Total n in analysis 570 99.7
Total missing 2 3
Total 572 100.0

The next background variable, represented in question nine, asks if the participant
has any disability whether learning, physical, or other. From the data shown in Table 7,
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46
among the 505 who answered this question, most participants (83.4%) do not have a
disability.
Table 7
Whether Participants Have a Disability

Frequency Percent Cumulative
Percent
None 477 83.4 94.5
Learning/dyslexia 7 1.2 95.8
Physical/sensory/health related 13 2.3 98.4
Other 8 1.4 100.0
Total n in analysis 505 88.3
Total missing 67 11.7
Total 572 100.0

The next background variable, as represented in survey question 11, asks
participants which item most accurately describes their generation and citizenship
status here in the United States. With 571 respondents for this question, the majority
of participants are first generation (56.3%) with neither parent having been born in
this country.
Table 8
Generation and Citizenship Status of Participants

Frequency Percent Cumulative
Percent
At least 1 grandparent, parents & self, born in U.S. 24 4.2 4.2
At least 1 parents & self, born in U.S. 78 13.6 17.9
Self, born in U.S. but not parents 322 56.3 74.3
Foreign born, but now a U.S. citizen 23 4.0 78.3
Foreign born, not yet a U.S. citizen 122 21.3 99.6
Student/visitor visa 2 .3 100.0
Total n in analysis 571 99.8
Total missing 1 .2
Total 572 100.0

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In the next background variable, taken from survey question 12, participants are
asked which option best describes where they grew up. Data from Table 9, with 562
respondents, indicates that most of the participants (67%) grew up in an urban area.
Table 9
Where Participants Grew Up

Frequency Percent Cumulative
Percent
Urban area 383 67.0 68.1
Small town 47 8.2 76.5
Suburban area 110 19.2 96.1
Rural area 22 3.8 100.0
Total n in analysis 562 98.3
Total Missing 10 1.7
Total 572 100.0

Question 13 of the survey asks about where the participant has lived for the
majority of their life before college. In Table 10, with 561 who answered this question, it
is revealed that the majority indicated “Urban Area”, with 67.3%.
Table 10
Location Participants Lived Most of their Life

Frequency Percent Cumulative
Percent
Urban area 385 67.3 68.6
Small town 36 6.3 75.0
Suburban area 120 21.0 96.4
Rural area 20 3.5 100.0
Total n in analysis 561 98.1
Total missing 11 1.9
Total 572 100.0

Survey question 14, the next background variable, explored what type of
secondary or high school the participant last attended. As seen in Table 11, with 563
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48
respondents, data reveals that most of the participants (87.8%) attended a public or state
high school with no religious affiliation.
Table 11
Type of High School Participants Attended

Frequency Percent Cumulative
Percent
Did not finish 6 1.0 1.1
Public or state school, non-religious 502 87.8 90.2
Home school 9 1.6 91.8
Religious-affiliated, public or private 21 3.7 95.6
Finished by exam (e.g., GED) 10 1.7 97.3
Private, non-religious 7 1.2 98.6
Adult school 8 1.4 100.0
Total n in analysis 563 98.4
Total missing 9 1.6
Total 572 100.0

The next background variable, gathered from survey question 16, asks about
participants the highest level of education obtained by their father or male guardian.
Based on the data presented in Table 12, with 568 who responded to this question, most
participants’ father or male guardian had some high school or above as their highest level
of education obtained (18.5%). However, as a close second level of education obtained
by participants’ father or male guardian, graduation from high school was at 18.2%. Only
14.3% of the group had some college, and just above five percent graduated college,
while just over two percent obtained a professional degree.

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Table 12
Father/ Male Guardian’s Highest Level of Education

Frequency Percent Cumulative
Percent
Don’t know 64 11.2 11.3
Elementary 100 17.5 28.9
Junior high school 70 12.2 41.2
Some high school 106 18.5 59.9
High school graduate 104 18.2 78.2
Some college 82 14.3 92.6
College graduate 30 5.2 97.9
Professional degree 12 2.1 100.0
Total n in analysis 568 99.3
Total missing 4 .7
Total 572 100.0

Survey question 17 asked participants the highest level of education obtained by
their mother or female guardian. Based on the data presented in Table 13, with 570 who
responded to this question, most participants’ mother or female guardian achieved high
school graduation as their highest level of education (18.2%). However, as a close second
level of education obtained by participants’ mother or female guardian, graduation from
junior high school was at 16.8%. Only 14.9% of the group had some college, and just
above seven percent graduated college, while just over two percent obtained a
professional degree.

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Table 13
Mother/Female Guardian’s Highest Level of Education
Frequency Percent Cumulative
Percent
Don’t know 42 7.3 7.4
Elementary 125 21.9 29.3
Junior high school 96 16.8 46.1
Some high school 60 10.5 56.7
High school graduate 104 18.2 74.9
Some college 85 14.9 89.8
College graduate 45 7.9 97.7
Professional degree 13 2.3 100.0
Total n in analysis 570 99.7
Total missing 2 .3
Total 572 100.0

In the next survey question, item 18, participants were asked if anyone living
in their home (other than a parent) had dropped out of junior high or high school. This
background variable, as shown in Table 14, with 570 respondents, indicates that while
a majority of the group does not have someone living at home who has dropped out of
either junior high or high school (79.4%), there are still 20.3% who do live with
someone who dropped out.
Table 14
High school or Junior High Dropout in the Home

Frequency Percent Cumulative
Percent
No 454 79.4 79.6
Yes 116 20.3 100.0
Total n in analysis 570 99.7
Total missing 2 .3
Total 572 100.0

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For the following background variable, information was taken from survey
question 19, asking if the participant is a U.S. military veteran. From information
gathered in Table 15, where 569 answered this question, most of the respondents
indicated that they are not a veteran (99%).
Table 15
Veteran of the U.S. Military

Frequency Percent Cumulative Percent
No 566 99.0 99.5
Yes 3 .5 100.0
Total n in analysis 569 99.5
Total missing 3 .5
Total 572 100.0

Moving on to survey question 88, participants were asked if they participated
in the STEM Summer Academy
14
offered by SCC. As shown in Table 16, with 553
who responded to this question, a majority of participants have not taken part in the
STEM Summer Academy (72.7%).
Table 16
Participant of STEM Summer Academy

Frequency Percent Cumulative
Percent
No 416 72.7 75.2
Yes 137 24.0 100.0
Total n in analysis 553 96.7
Total missing 19 3.3
Total 572 100.0

Derived from survey question 89, the background variable representing
participation in summer research is conveyed. From the data shown in Table 17, with 570

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52
responses, just over 15% of participants have taken part in a summer research
opportunity.
Table 17
Participation of Participants in Summer Research

Frequency Percent Cumulative Percent
No 483 84.4 84.7
Yes 87 15.2 100.0
Total n in analysis 570 99.7
Total missing 2 3
Total 572 100.0

As seen in question 90 of the survey, participants were asked if they have ever
been a foster child. Table 18, with 571 who responded to this question, shows that only
1.2 percent have.
Table 18
Whether Participants Were a Foster Child

Frequency Percent Cumulative Percent
No 564 98.6 98.8
Yes 7 1.2 100.0
Total n in analysis 571 99.8
Total missing 1 .2
Total 572 100.0

On question 91 of the survey, participants were asked if they are eligible for
AB540
15
. With regard to the background variable indicating AB 540 eligibility, as shown
in Table 19, with 551 who responded to this question, just under 20% (19.8%) are
eligible.

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Table 19
Participants Eligibility for AB 540

Frequency Percent Cumulative Percent
No 438 76.6 79.5
Yes 113 19.8 100.0
Total n in analysis 551 96.3
Total missing 21 3.7
Total 572 100.0

Finally, in survey question 145, participants were asked if they are currently
employed. As Table 20 indicates, with 353 who responded to this question, 30% are
currently working while in school, and a majority, 70%, are not.
Table 20
Participants Work Status

Frequency Percent Cumulative Percent
No 181 31.6 51.3
Yes 172 30.1 100.0
Total n in analysis 353 61.7
Total Missing 219 38.3
Total 572 100.0

In summary, the data indicated that a majority of the sample are first generation,
male, between the ages of 18-25, who have been in college for at least 2 years with no
breaks in their education. Most are single, never married, with no children, possess no
disability, and primarily grew up and are currently still living in an urban area. A
majority of the sample attended public school with no religious affiliation, and had over
80% of both their father/ male role model and/ or mother/female role model earn less
than a high school education. Additionally, only 15% have conducted summer research,
only 1.2% are currently, or have ever been foster youth and just under 20% are AB540
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54
eligible. Finally, a majority of respondents (70%) are not currently working while in
school.
Relationship of Background Variables to Academic Success
Research question one focused on the relationship between various background
variables and academic success. For purposes of analysis, academic success was defined
as STEM G.P.A. Since the data related to this question were nominal, in order to answer
this question, non-parametric Chi-square analyses were carried out. For each background
variable, Chi-square was calculated with STEM G.P.A. as the second variable.
In order to carry out a Chi-square analysis, a cell count of more than five is
required. However, in the course of this analyses, it was found that a number of the
background variables were not evenly distributed. Specifically, in some cases with
categorical variables, a majority of the group fell into one category, resulting in an
expected frequency count less than 5 in one or more of the other cells. Consequently,
because of the statistical limitations related to small cell size, it was not possible to
calculate a valid Chi-square coefficient for these seven variables: age, marital status,
presence of a disability, citizenship status, high school attended, veteran status, and foster
youth status.
The results of the analyses for the variables on which a valid Chi-square analysis
was possible, are presented in the following table.

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Table 21
Analysis of Background Variables

Background
variable
n Chi-
Square
Df Sig Pearson
Phi
Sig Craemer’s
V
Sig
Semesters/yrs. in
college

547 2.082 3 ns .062 ns .062 ns
Have taken a break

567 .273 1 ns .022 ns .022 ns
Gender

570 7.447 1 .006 -.114 .006 .114 .006
Have children

570 .26 1 ns -.021 ns .021 ns
Location grew up

562 1.833 3 ns .057 ns .057 ns
Location now
living

561 3.704 3 ns .081 ns .081 ns
Father/male
guardian ed.

568 5.264 7 ns .906 ns .096 ns
Mother/female
guardian ed.

570 9.538 7 ns .129 ns .129 ns
High school
dropout at hm.

570 3.831 1 .05 -.082 .05 .082 .05
Attended STEM
Academy

553 7.748 1 .005 -.118 .005 .118 .005
Attended summer
research

580 9.447 1 .002 .129 .002 .129 .002
AB 540

551 8.97 1 .003 .128 .003 .128 .003
Work 353 5.274 1 .022 .122 .022 .122 .022

The Chi-square analyses indicated that the following six variables were found to
be significantly related to the dependent variable, academic success: gender, presence of
a high school or junior high dropout at home, participation in the STEM summer
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56
academy, participation in summer research, AB540 status and work status. These
variables and their relationship to academic success will be discussed in Chapter 5.
Characteristics of the Independent Measures
Research question two focused on the relationship among key independent
variables (self-efficacy, social capital, and academic engagement) with academic
success as the dependent variable. In order to explore this question further, analyses
of the characteristics of the measures were carried out, including reliability analyses
of the measures. Descriptive statistics, including means and standard deviations of the
variables derived from scales (which can be found in the “Instrumentation” section of
chapter 3), are presented below.
Table 22
Means and Standard Deviation for Measured Variables

Variables N Missing
cases
M SD Number of
items on scale
Reliability
coefficient
1. Self-efficacy 568 4 4.5 .68 14 .847
2. Social Capital 568 4 4.4 .60 24 .833
3. Academic Engagement 568 4 2.8 .93 23 .924

In order to determine reliability, an analysis was done to calculate an alpha
coefficient for each variable. As Table 22 indicates, the variables had acceptable
reliability and thus were suitable for further analysis. The dependent variable, STEM
GPA, was not derived from a scale, but was an ordinal variable based on an n of 575
(missing cases = 371), with a mean of 3.13 and a standard deviation of .48. The
remaining analyses, based on these variables, is described in the next section.
Relationship of the Independent Variables and Academic Success
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57
Questions two and three focused on the relationship of the independent variables
and the dependent variable, academic success. In order to answer these questions, a
multiple regression analysis was carried out. The independent variables in the analysis
were self-efficacy, social capital, and academic engagement, and the dependent variable
was academic success. The intercorrelations of the variables are presented in Table 23
below.
Table 23
Correlations for Measured Variables

Variables STEM GPA Self-Efficacy Social Capital Academic
Engagement
STEM GPA

--
Self-Efficacy

.24** --
Social Capital

.15** .72** --
Academic
Engagement
.05** .27** .250** --
Note. Correlation is significant at <.001.. Total n =568

In the next step of the analysis, a multiple linear regression was calculated to
predict STEM GPA based on each of the independent variables: self-efficacy, social
capital and academic engagement. The regression analysis yielded an R
2
of .06, which
was significant (F(3, 564) = 11.45, p <.001). The regression equation indicated that
participants’ predicted STEM GPA is equal to 2.461+ .270 (self-efficacy) -.04 (social
capital) -.02 (academic engagement), where (as noted in the “Instrumentation” section of
Chapter 3) self-efficacy was measured as the mean score on a 14 item scale ranging from
0-6, social capital was measured as the mean score on a 23 item scale ranging from 0-6
and academic engagement was measured as the mean score on a 22 item scale ranging
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58
from 0-6. What these results show, is that participants’ STEM GPA increased .270 for
each 1 unit increase in self-efficacy score. Additionally, participants’ STEM GPA
decreased .04 unit for each 1 unit decrease in social capital score. Finally, participants’
STEM GPA decreased .02 unit for each 1 unit decrease in academic engagement score.
What these results indicate, is that the more self-efficacy (greater self-efficacy score) a
student possesses, the higher the potential GPA of the student; whereas the lower the
social capital (per social capital score) and the lower the academic engagement (per
academic engagement score), the lower the potential GPA of the student. Implications of
these findings will be further discussed in Chapter 5.
Summary
In sum, the analyses indicated that there were significant relationships among six
background variables and academic success. These six variables included students’:
gender, presence of someone in the home who was a high school or junior high dropout,
participation in the STEM Summer Academy, participation in summer research, AB540
status, and whether the student works. In addition, the regression analysis indicated that
all three independent variables (self-efficacy, social capital, and academic engagement)
were a significant predictor of the dependent variable, academic success. Further
discussion of these findings are presented in the following chapter.

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CHAPTER FIVE: DISCUSSION AND CONCLUSIONS
Summary
The goal of this study was to examine the relationship between community
college Latinx STEM students’ background and their academic success, as well as the
relationship and relative contributions of their self-efficacy, social capital, academic
engagement and their academic success. The findings of this research indicated that of
the twenty background variables, only 6 (gender, presence of a high school or junior high
dropout at home, participation in the STEM summer academy, participation in summer
research, AB540 status and work status) were found to have a statistically significant
relationship with the dependent variable, academic success. Additionally, all 3
independent variables, self-efficacy, social capital, and academic engagement, were
shown to be a significant predictor of the independent variable, academic success.
Participants who had higher self-efficacy scores, were more likely to have a higher
STEM G.P.A., a proxy for academic success, and those who had lower social capital and
lower academic engagement scores were more likely to have a lower STEM G.P.A. The
remainder of this chapter will expand upon the findings of this study, as well as
implications, and suggestions for future research.
Discussion of Significant Background Variables
As noted, only 6 of the twenty background variables were found to have a
statistically significant relationship with academic success. One likely explanation for
these results is the skewed nature of many of the key variables which made it difficult to
analyze. At any rate, these variables included: gender, presence of a high school or junior
high dropout at home, participation in the STEM summer academy, participation in
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60
summer research, AB540 status and work status. Elements such as gender, presence of a
high school or junior high dropout at home and AB540 status are elements relating to
one’s own personal, or family characteristics. As such, these are not elements that can be
changed, nor is that the intention or focus of this work. However, as this body of work
indicates, there is a correlation with these specific characteristics, and these students’
potential for success. Therefore, instead, those exhibiting these characteristics from
within the Latinx student population can be targeted for additional support and resources
to mitigate potential barriers to academic success. The other three variables, which
included participation in the STEM summer academy, participation in summer research,
and work status are behavioral factors found to have a statistically significant relationship
with academic success. That is, these behavioral factors can potentially be influenced to
some extent. With these findings, practitioners can implore Latinx STEM students to
consider participation in STEM related summer programming, as well as research
opportunities where appropriate; furthermore, institutions of higher education should
consider offering these opportunities with particular outreach tactics. Also, while work
status is often not something that is usually a choice, but rather, out of necessity, helping
students to find other means to fund their education becomes increasingly important. That
is, helping them search for, and apply to scholarships, as well as applying to and
understanding their financial aid options; this is especially important for those who are
AB540, and consequently, may have limited access to federal funding opportunities or
financial resources.
Overall, these findings indicate that it will be important for administrators in
higher education to focus on potential ways in which to address behavioral changes of
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61
students with regard to their participation in summer programming and research
opportunities, as well as working less. Additionally, where possible, it is imperative to
continue to target females, those who have the presence of a high school or junior high
dropout in the home, and AB540 students, to gear them towards success. This
information is not always easy to gather, however, with the growing expansion of
technological advancements in college application screening, and other such ways to
gather student information, it is certainly worthwhile to attempt to look at this
information where possible, as another way in which to increase success rates,
particularly for Latinx STEM students.
It is important to note that because so little research has been conducted on Latinx
community college STEM students in particular, these findings are not generalizable.
Discussion of Self-Efficacy and Academic Success
Self-Efficacy is one of the most important and well researched motivational
variables. It is defined as the belief in one’s ability to succeed in a particular situation;
determinants of how one thinks, behaves, and feels (Bandura, 1997). Bandura’s work has
been applied to a number of domains. However, not specifically to understanding Latinx
community college STEM students’ academic success.
The findings of this study are parallel to previous work, in that the research
revealed that self-efficacy has a positive correlation with academic success. Results of
this study imply that a students’ self-efficacy score has a positive impact on STEM GPA,
which was used as a proxy for academic success. That is, the higher the self-efficacy
score, the higher the potential STEM GPA.
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62
In previous research, self-efficacy, has been shown to have a positive relationship
with academic achievement (Richardson, Abraham, & Bond, 2012). Various studies have
provided evidence that self-efficacy is useful in understanding higher education
attainment (Pajares, 1996; Schunk & Pajares 2009; Unrau, et al., 2018). However, in
general, most existing work focuses on university students, rather than community
college students, and furthermore, is not specific to the Latinx population, nor is it
specific to those pursuing STEM majors. The findings of this work add to the pool of
research relating specifically to community college Latinx STEM students, and further
imply that students’ self-efficacy is an important variable to academic success. As such,
this work validates the importance of the need for institutions of higher education,
community colleges in this context, to provide an environment that is encouraging, and
supportive in nature. When students are encouraged and supported, they are more likely
to have increased sense of self-efficacy (Stevens, et al., 2004; Pajares, 1996; Schunk &
Pajares 2009; Unrau, et al., 2018).
Discussion of Social Capital and Academic Success
Social capital refers to the intangible resources including, but not limited to
elements such as social networks, or connections which have potential value to one’s
social mobility. In this study, social capital was shown to have a positive correlation, and
to be a predictor of academic success. This study revealed that the lower the social capital
score, thereby implying less social capital, the lower the GPA. These findings were
consistent with existing literature, referencing the impact of social capital on student
success, wherein, it has been shown to be a predictor of academic success (Bourdieu,
1986; Coleman 1988; Goldin & Katz, 1999). This is not to imply that the lack of access
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63
to these social networks and connections means inevitable low G.P.A. Yet because
students may already come into the college setting lacking such capital, practitioners
need to assure equitable access to campus resources. For example, faculty office hours
and accessibility should be reasonable, and flexible in nature. Furthermore, student
services which seek to provide vital institutional information such as financial aid,
counseling, career and transfer centers, etc., should be accessible during morning, mid-
day, evening, as well as weekend hours where possible, to accommodate student needs
and improve accessibility to social networks and key information relevant to
understanding and navigating the higher education system. However, again, because
research on the Latinx community college population, especially STEM students, is still
fairly novel (Crisp & Nora, 2010), additional studies may help to better understand this
relationship.
Discussion of Academic Engagement and Academic Success
Previous literature has looked at academic engagement as a key factor
contributing to academic success (Tinto, 1993). The results of this study prove consistent
with these notions. The findings of this research showed that the lower the academic
engagement score (implying less academic engagement) the lower the Latinx community
college STEM students’ potential GPA.
This population, often still first generation college students, may not yet have a
clear understanding of the importance of utilization of these institutional resources, or
even how to access them in the first place; furthermore, because of the lack of prior
exposure to higher education, they may be intimidated by or even uncertain how to
navigate such resources. With the lack of use of key resources which may otherwise help
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64
students be more successful (increase their G.P.A), it is clear that this can impact their
academic success. These findings further echo the need to expand and widely publicize
accessibility to and uses of key resources that each college campus has to offer. When
students understand what these various resources can potentially provide, they may be
more likely to seek out and utilize such resources, thereby increasing overall academic
engagement. To that end, increased academic engagement leads to a correlation with a
higher potential for academic success. Campus-wide campaigns to share knowledge of
resources and their uses should be embedded throughout the campus, so as to increase
visibility and accessibility of such resources.
Limitations
It is important to note that the primary data for this study consisted of student self-
reports, including self-reported STEM G.P.A.. As a result, it was not always possible to
control for student honesty, and through reflection in their responses; some students may
not have been as thorough as they would in an in-person interview or other qualitative
data collection process. However, while some research suggests self-reported grade
information should be used with caution in research (Kuncel, et. al, 2005), it has also
been found that self-reported grade information is positively correlated with actual grade
information (Sticca, et. al, 2017; Rosen et. al, 2017). Also, given the nature and length of
the questionnaire, as well as the amount of time that it may take a student to provide
honest and thoughtful feedback, some students may not have been thorough.
A second limitation is that students from this study are not from a single cohort,
but rather, come from across various cohorts over the span of the past 5.5 years. Some
students may even have attended other institutions throughout any given point in their
Running Head: LATINX STEM STUDENTS AND ACADEMIC SUCCESS

65
educational path, as that is common community college behavior. Consequently,
students may have been exposed to several other elements, and/or programmatic
initiatives which may have otherwise impacted their academic success.
An additional factor limiting the generalizability of the results is the context for
this study, as it was carried out in a single community college, in an urban environment,
with a fairly homogenous population (primarily Hispanic/Latinx, between the ages of 18-
25). Therefore, these findings may not generalize to other schools or populations that are
not similar in size, location, or population/ demographics.
Delimitations
STEM grade point average was used as the dependent variable, a proxy indicator
for academic success. However, other measures for success which were not specifically
assessed in this questionnaire (i.e. – participation in research, transfer to a four year
institution within prescribed time limits, etc.) may provide other means through which to
measure and compare “success”. Even though STEM grade point average was used as the
measure for success, it is important to note that at the community college level, a G.P.A.
of 2.0 is considered “successful completion.” However, to be competitive for transfer,
specifically among competitive research institutions, (within the University of California
system, for example) a much higher, more competitive G.P.A., such as a 3.5 minimum,
would be more likely considered “success” than would a comparative 2.0 being used in
this community college context.
This research focused primarily on those who identified as “Hispanic, Latino,
Chicano”. In addition, there was some missing data from those who did not report a
Running Head: LATINX STEM STUDENTS AND ACADEMIC SUCCESS

66
STEM GPA, which was the primary dependent variable of interest on the questionnaire.
As a result, the sample was reduced significantly from its original size, 1,312, to 572.
Finally, the initial sample was N=1,312. However, in order to answer the research
questions, the sample was reduced by excluding anyone who did not self-identify as
“Hispanic, Latino, Chicano”, as this group was the primary focus of the study, thus
reducing the sample to n = 946. For some of the analyses which focused on STEM
achievement, only those cases who reported a STEM G.P.A. were included, resulting in a
total of 572 respondents.
Recommendations for Future Research
This study included only quantitative data analysis. Therefore, in replication, a
qualitative component – perhaps via interview, or some other qualitative investigation,
should take place in order to more thoroughly understand the relationships between the
independent and dependent variables. Qualitative methodologies can give greater insight
to understanding the interrelationships between the variables of study, and would provide
a deeper insight to student perspective on how individual success may be affected by the
noted resources provided by the grants and services in STEM at the community college
level.
Additionally, STEM G.P.A. was used as the dependent variable to indicate
academic success, as STEM students were the primary focus of this study. However,
future research might investigate other potential variables as indicators of success. For
example, transfer G.P.A., which, for community college students, helps them to be able
to transfer to a university. This study did not use that G.P.A., as it is the STEM G.P.A. in
Running Head: LATINX STEM STUDENTS AND ACADEMIC SUCCESS

67
particular, for this population, which makes them more competitive for transfer to a
university in a STEM major.
Implications for Practice
This study provides insight to the relationship between Latinx community college
STEM students’ self-efficacy, social capital, academic engagement, and their academic
success, as well as the relationships between their background characteristics and
academic success. In light of the findings, it appears that institutions of higher education
should focus on these salient factors in order to increase the potential for academic
success among Latinx community college STEM students. In order to gain the greatest
outcomes of success for Latinx community college STEM students, it will be important
not only for community colleges, but also any institution of higher education, to work to
improve student self-efficacy, social capital, academic engagement, as a primary factors
that has the potential to impact academic success. Colleges need to recognize the
influence of background variables as well as motivational and behavioral variables. It
will be important to look into ways in which to increase self-efficacy, as well as provide
access to and encourage usage of vital information and resources to support students from
these groups. Implementing programming and other facets from within the student life
and students services division tailored to background characteristics for these
underrepresented groups has the potential to make an impact on academic success.
Conclusion
Based on the findings from this work, there were 6 specific background variables
found to have a positive relationship to Latinx community college STEM students’
academic success. Additionally, there was found to be a positive relationship between
Running Head: LATINX STEM STUDENTS AND ACADEMIC SUCCESS

68
students’ self-efficacy, social capital, academic engagement, and their academic success,
thereby indicating that these remain to be salient factors related to academic achievement
in higher education. As the Latinx population continues to grow, naturally, so too will
their pursuit and attainment of higher education. In particular, as trends show, enrollment
into community colleges in particular will be a primary option for many Latinx students
(PEW Research Center, 2018). With the community college system serving as a viable,
and relatively affordable option for the higher education pathway, it becomes imperative
to assure that community colleges understand the key predictors for optimal academic
success. Therefore, additional qualitative insights can help to better understand these
variables, and direction in which practitioners of higher education should move forward
in serving the Latinx STEM population, by helping them to further develop their sense of
self-efficacy, gain access to vital resources and information, and engage in campus
activities and utilize the many resources and services campuses have to offer. More
important, however, is that further research continue to focus on this rather under-studied
population, in order to continue to seek out additional ways in which to continue to
improve their academic success in the pursuit of higher education in STEM. As the
Latinx population continues to grow, there is great potential to empower them to expand
as a highly educated, highly skilled workforce, vital to the very fabric of our nation.

Running Head: LATINX STEM STUDENTS AND ACADEMIC SUCCESS

69
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Footnotes
1
The distinction between the labels Latino/a, Latinx, Hispanic, Chicano/a,
Chicanx remains a highly controversial topic of debate, and there is no universally agreed
upon label that adequately distinguishes the groups, and is not the focal point of this
research project. Participants of this study are self-identified as “Hispanic, Latino/
Chicano” as noted on the questionnaire that was used for this research, and this
terminology will be interchangeably referred to as “Latino/a”, “Latinx”, “Hispanic”,
“Chicano/a”, “Chicanx” depending on the point of reference. The terms “Latinx” and
“Chicanx” have been largely adopted in academia more recently as a non-binary, gender
neutral way for one to describe their identity without the need to select a particular
gender attached to the label.
2
A Hispanic Serving Institution (HSI) is defined in federal law as an accredited
and degree-granting public or private nonprofit institution of higher education with “an
enrollment of undergraduate full-time equivalent [FTE] students that is at least 25 percent
Hispanic students at the end of the award year immediately preceding the date of
application (Department of Education, 2011).” In this context “date of application” is
referring to the date of application for Title V HSI status and funding.
3
Two of the grants have ended since the beginning of this study (one funded by
the U.S. Department of Education, and the other, by the National Science Foundation).
Currently the third and separate grant, funded by the U.S. Department of Education, is in
its third year.
4
Participants were comprised of students from within approximately a 5.5 year, 9
semester span including the Spring 2013, Fall 2013, Spring 2014, Fall 2014, Spring 2015,
Running Head: LATINX STEM STUDENTS AND ACADEMIC SUCCESS

85
Fall 2015, Spring 16, Fall 16, and Spring 18 terms; neither Spring or Fall 2017 data was
collected due to grant/ funding interruptions. The data is based on the semesters in which
the survey was administered through three separate federal grants funded by either the
U.S. Department of Education, or the National Science Foundation. The names of these
grants shall not be disclosed, so at to preserve the anonymity of Shoalin Community
College.
5
“State legislation, the Public Schools Accountability Act (PSAA) of 1999
(Chapter 3, Statutes of 1999), established the API, which summarizes a school’s or a
local educational agency’s (LEA’s) academic performance and progress on statewide
assessments… Assembly Bill (AB) 484 revised California Education Code (EC) Section
60640 which established a new assessment system known as the California Assessment
of Student of Student Performance and Progress (CAASPP). The CAASPP became
effective January 1, 2014” (California department of Education website,
http://www.cde.ca.gov/ta/ac/ap/glossary14b.asp, retrieved July 12, 2016).
6
Part time status refers to a student being enrolled in 11 units or less for that term;
that is, because full time status refers to a student being enrolled in 12 units or more.
7
The Board of Governors Fee Waiver (BOGFW) was offered by the Board of
Governors of the California Community College system, for low income residents of
California to have their tuition fees waived at any of the 114 California community
college campuses. This waiver is provided to students who meet the financial need
criteria – that is, those who may not otherwise be able to afford the tuition. However, in
2017, it was introduced that this would now be rebranded as the “California College
Promise Grant”, and beginning in Fall 2018, BOGFW was phased out.
Running Head: LATINX STEM STUDENTS AND ACADEMIC SUCCESS

86
8
MESA students apply in order to participate in the program, and are provided
access to program resources to the extent possible by law, given that they meet the grant
eligibility requirements; these requirements include: election to major in a STEM field,
need-based financial aid eligibility, full time enrollment (fall/spring) with at least 2
STEM courses, minimum 2.8 G.P.A. Emphasis is placed on participation by students
from groups with low rates of eligibility for four-year colleges.
9
The personal development course is taught by the STEM counselor, and targets
first-year college STEM students, who successfully complete a STEM summer bridge
program in order to transition them into their first year of college, and accelerate their
math sequence, with a goal to have all participants be calculus ready by the end of their
first academic year.
10
Active students of the MESA program are able to check out textbooks and
calculators on a loan basis for the entirety of the semester; textbooks are provided
specifically in STEM disciplines.
11
Through one of the current STEM grants, the campus has a STEM peer mentor
program which systematically pairs former Shaolin MESA students who have since
either already transferred or even graduated and are now working in industry with a
current lower division Shaolin MESA student. The mentors are trained by the peer
mentor coordinator and STEM counselor to work with assigned mentees in their
discipline, who elect to participate via application and selection process. This is distinct
in that the STEM peer mentor program involves a formal training and check-in process, a
reporting mechanism for both mentors and mentees to provide updates and feedback, and
regular check in.
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87
12
To remain active in the MESA program, students must maintain a minimum 2.8
overall G.P.A., as well as full time enrollment (12 units), with at least 2 STEM courses
per semester; this is in addition to a number of other requirements necessary to maintain
active status (i.e. - participate in at least 1 STEM club; meet with the STEM counselor
each semester; complete a 6 week and 12 week progress report to be signed by all
professors for each STEM course in which the student is enrolled, verifying students’
academic status in each course; attend at least 2 MESA sponsored events per semester).
13
This study does not focus on gender identity, therefore, the response options for
this survey item were dichotomous. However, given that there were 2 missing cases for
this question, there may have been participants who elected not to respond given the
limited construct of the question.
14
The STEM summer academy is a programmatic aspect of the college that has
been in place at SCC since 2008, when it was first funded under an initial federal grant.
In the years since then, this component has continued at the college, but changes annually
to some degree, based on additional STEM related grants accrued by the college (and
corresponding grant goals and objectives). The primary goal of this academy each year,
regardless of funding source, is to expose incoming recent high school graduates who
plan to attend SCC the following fall, to STEM, through enriched hands-on activities,
field trips to local universities and other enrichment experiences and activities.
15
Assembly Bill 540 (AB 540) is a state law, pertaining to the California
Education Code, wherein certain non-residents (those who have attended high school in
California for at least 3 years, and received a high school diploma or its equivalent,
among other requirements) are granted exemption from payment of non-resident tuition
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88
from publicly funded institutions of higher education. At the college level, students are
very much aware of their eligibility for this status, as it is presented to them at
orientation, and in the college application, because it impacts the cost of their attendance
– that is, those who qualify for this status, are able to pay in-state tuition which is
significantly cheaper than were they to be classified as an “international” student.
Because of the salience of financial constraints for this population, the likelihood of
students’ awareness is very high.

Abstract (if available)

Abstract As part of a larger longitudinal community college investigation involving evaluation of programming and services designed to increase STEM achievement, particularly for Latinx, socioeconomically disadvantaged students, this study examines the relationships among Latinx community college STEM students’ background variables, as well as their self-efficacy, social capital, academic engagement, and academic success. The analyses indicated that there were significant relationships among several background variables and academic success. In addition, the regression analysis indicated that all 3 independent variables (self-efficacy, social capital, and academic engagement) were significant predictors of the dependent variable, academic success. Overall, these findings indicate that it will be important for administrators in higher education to address behavioral patterns of these students with regard to participation in summer programming and research opportunities, as well as working less. Additionally, it is imperative to continue to target females, those who have the presence of a high school or junior high dropout in the home, and AB540 students, to gear them towards success. In light of the findings, institutions of higher education should focus on these salient factors in order to increase the potential for academic success among Latinx community college STEM students. Furthermore, it will be important not only for community colleges, but also any institution of higher education, to work to improve student self-efficacy, social capital, academic engagement, as a primary factors that have the potential to impact academic success, particularly for Latinx STEM students.

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Asset Metadata

Creator Juarez, Marina Daniela Rueda (author)

Core Title Examining the relationship between Latinx community college STEM students’ self-efficacy, social capital, academic engagement and their academic success

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 07/24/2019

Defense Date 05/08/2019

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag academic engagement,academic success,community college,Latinx,OAI-PMH Harvest,self-efficacy,social capital,STEM

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Picus, Lawrence (committee chair), Ragusa, Gisele (committee member), Rivera-Figueroa, Armando (committee member)

Creator Email ruedamd@elac.edu,uscxicana@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-186941

Unique identifier UC11663153

Identifier etd-JuarezMari-7607.pdf (filename),usctheses-c89-186941 (legacy record id)

Legacy Identifier etd-JuarezMari-7607.pdf

Dmrecord 186941

Document Type Dissertation

Format application/pdf (imt)

Rights Juarez, Marina Daniela Rueda

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA