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Factors that contribute to community college career and technical education student success
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Content
Factors That Contribute to Community College Career and Technical Education Student
Success
by
Juan Pedro Flores-Zamora
Rossier School of Education
University of Southern California
A dissertation submitted to the faculty
in partial fulfillment of the requirements for the degree of
Doctor of Education
December 2020
© Copyright by Juan Pedro Flores-Zamora 2020
All Rights Reserved
The Committee for Juan Pedro Flores-Zamora certifies the approval of this Dissertation
Cynthia Olivo
Mary Andres
Ruth Chung, Committee Chair
Rossier School of Education
University of Southern California
2020
Abstract
Although the demand is high for a Career and Technical Education trained workforce, people of
color and women remain underrepresented in the industry and have lower community college
completion rates; moreover, students of color make up a large percentage of the CTE student
population. Thus, without meeting the needs of students of color, CTE programs will have a
difficult time meeting the needs of industry. This study examines the non-cognitive,
environmental and campus ethos factors that influence student success outcomes for CTE
students. Using the Community College Success Measure survey instrument, a simultaneous
regression analyses found multiple variables that significantly predicted success outcomes for
CTE students.
Keywords: Career and Technical Education (CTE), Community College, Student
Success, Socio-Ecological Outcomes (SEO) Model.
Dedication
To my mother, Amelia Zamora who is a strong, beautiful and resilient woman, this dissertation
showed me how much she provided for me and gave me the ability to appreciate her ever more
deeply. My daughter Raven Bayou-Flores who is smart, funny and always has a smile on her
face. To her mother Jasmine Bayou-Young who brought her into this world and is the reason
why Raven is amazing. To Ann & Robbie who I love dearly, thank you for all that you have
given me. To my brother Damian, and my nieces Mia and Alexa.
vi
Acknowledgements
I want to thank the following faculty who helped me along the way in the process of
writing this dissertation. Dr. Ruth Chung, my committee chair. Dr. Cynthia Olivo, who I admire
greatly and was instrumental in this study. Dr. Mary Andres, who assisted me and provided
feedback, thank you. Lastly to Dr. Maria Malagon, who helped me along the way. I cannot
express how deeply grateful I am to all of you.
vii
Table of Contents
Abstract .......................................................................................................................................... iv
Dedication ....................................................................................................................................... v
Acknowledgements ........................................................................................................................ vi
List of Tables ................................................................................................................................. ix
List of Figures ................................................................................................................................. x
Chapter One: Introduction .............................................................................................................. 1
Statement of the Problem .................................................................................................... 4
Background of the Problem ................................................................................................ 5
Conceptual Framework ....................................................................................................... 7
Purpose of the Study ........................................................................................................... 9
Key Terms and Definitions ............................................................................................... 11
Chapter Two: Literature Review .................................................................................................. 13
Community College CTE History and Purpose ................................................................ 13
SEO Conceptual Framework ............................................................................................ 18
Summary of Literature Review ......................................................................................... 23
Purpose of the Study ......................................................................................................... 24
Chapter Three: Methodology ........................................................................................................ 27
Participants ........................................................................................................................ 27
Instrumentation ................................................................................................................. 29
Procedure ......................................................................................................................... 33
Chapter Four: Results ................................................................................................................... 35
Preliminary Correlational Analysis ................................................................................... 35
viii
Research Question One: Are there racial and gender group differences in Anticipated
Persistence, Current Credits Enrolled, Credit Earned, and GPA of CTE
Community College students? .............................................................................. 37
Research Question Two: Non-cognitive, Environmental, and Campus Ethos Domains and
CTE Community College Students Persistence .................................................... 40
Research Question Three: Non-cognitive, Environmental, and Campus Ethos Domains
and CTE Community College Students Credits Enrollment ................................ 41
Research Question Four: Non-cognitive, Environmental, and Campus Ethos Domains and
CTE Community College Students Earned Credits .............................................. 42
Research Question Five: Non-cognitive, Environmental, and Campus Ethos Domains and
CTE Community College Students GPA .............................................................. 42
Chapter Five: Discussion .............................................................................................................. 44
The Relationship Between Students Background and Success Measures for Community
College CTE Students ........................................................................................... 44
The Relationship between Non-Cognitive to Student Success Measures ........................ 48
The Relationship between Environmental to Student Success Measures ......................... 50
The Relationship Between Campus Ethos to Student Success Measures ......................... 51
Implications for Practice ................................................................................................... 52
Recommendations ............................................................................................................. 53
Limitations of the Study .................................................................................................... 55
Implications for Research ................................................................................................. 56
Conclusion ........................................................................................................................ 57
References ..................................................................................................................................... 59
ix
List of Tables
Table 1: Frequency Distribution of Demographic Characteristics of
Participants……………………………………………………………………………………….28
Table 2: Zero-order Pearson Product Correlations of Measured Variables for CTE
Students………………………………………………………………………………………......35
Table 3: Means and Standard Deviations of Student Success Outcomes by Race and
Gender……………………………………………………………………………………………38
Table 4: Factorial Univariate Analysis of Variance for Student Success
Outcomes………………………………………………………………………………………...39
Table 5: Summary of Simultaneous Regression Analysis for Student Success
Outcomes………………………………………………………………………………………...41
x
List of Figures
Figure 1: Socio-Ecological Outcomes Model ................................................................................20
1
Chapter One: Introduction
It has been nearly a decade when the President’s Council for Science and Technology
announced that for the United States to keep its "historical preeminence in science and
technology," the educational system will have to produce one million more science technology
engineering and math (STEM) professionals over the next decade (Olson, 2012). Over the past
decade, the narrative surrounding the “skills-gap” has captured the attention of many educational
researchers, practitioners, and policymakers (Briggs, 2016; Giffi et al., 2018; Jackson & Rudin,
2019; Jones, 2018; Monis, 2018; Olson, 2012; Xue, 2015). Sounding the “skills-gap” alarm,
researchers have reported that sixty-five percent of all jobs, referred to as middle-skills jobs, will
require a post-secondary degree and training beyond high school (Achieve, 2012; Carnevale,
2013; Giffi et al., 2018; Rios-Augilar, 2018). The skills-gap narrative addresses the need to
alleviate the shortage in middle-skilled positions, which accounts for some of the fastest-growing
occupations. These high demand positions have been noted to be STEM literate-skilled jobs
(Carnevale et al., 2013; Stevens et al., 2019). According to a study by Deloitte and the
Manufacturing Institute, the skills-gap will leave approximately 2.4 million positions vacant in
an industry requiring 4.6 million jobs to be filled between 2018 and 2028 (Giffi et al., 2018).
Training for high demand, middle-skilled jobs takes place primarily at community
college Career and Technical Education (CTE) programs. Community colleges enroll over 5.1
million undergraduates in the United States, representing 29% of post-secondary students
(National Student Clearinghouse Research Center, 2019). With its open-admission system, low
tuition, and high numbers of first-generation and low-income students, community colleges play
a critical role in economic prosperity for many students in the U.S. (American Association of
Community Colleges, 2019). This chapter introduces and reveals the saliency of Career and
2
Technical Education-STEM (CTE-STEM) literate community college programs, the narrative
surrounding the need for CTE-STEM trained professionals, the current structures within the
California Community College system which produces these professionals, the statement of the
problem, it’s background, the conceptual framework used, the purpose of the study and finally
key terms and definitions used throughout this study.
In the state of California, community college students comprise 80% of the post-
secondary student population (Los Angeles Economic Development Corporation, 2019).
California community colleges provide more than 2.1 million students with the ability to earn
certificates and degrees in workforce training, basic skills, and preparation to transfer to four-
year universities (California Community College Chancellor's Office, 2019a). Despite the
number of students enrolled, employers face challenges in finding trained technical workers who
have the skills to complete their work, which comprises part of the national "skills gap" narrative
(Briggs, 2016; Monis, 2018; Jackson & Rudin; 2019) In California, thirty percent of all job
openings, representing a total of 1.9 million jobs will require some form of post-secondary
education by 2025 (Academic Senate for California Community Colleges 2015; Academic
Senate of California Community Colleges, 2019; California Community College Chancellor's
Office, 2015; Snyder & Cudney, 2017). Community colleges thus, plays a critical role in the
development of a skilled workforce through its CTE programs.
Community college CTE programs train a variety of skilled workers through its 13
clusters of disciplines ranging from business, transportation, construction to manufacturing and
STEM-based disciplines (ACTE, 2020). CTE programs assist in developing the high-tech
STEM-based workforce who are needed to be able to "learn, adapt, install, debug, train, and
maintain new processes or technologies" (National Science Board, 2015). Furthermore, with the
3
costs of automation declining, the advancement of 3D-printing and artificial intelligence,
traditional modes of economic production are being disrupted. The technological skills that
workers of the future will need will have to adapt to these continuous changes, and educators
play a critical role in meeting those needs today and well into the future (Los Angeles County
Economic Development Corporation, 2019).
As the needs of a trained workforce deepen and evolve, the California Community
College system is not producing enough capable CTE-STEM students with the necessary
knowledge to fill the "skills gap" (California Community College Chancellor's Office, 2015;
Synder & Cudney; 2017). Further, more than 60% of students left CTE-STEM programs
altogether, and less than 40 percent completed an associate degree (Bailey et al., 2005; Chen,
2013; Olson, 2012; Snyder & Cudney, 2017). In response to the widening skills-gap in industry,
the National Science Foundation continues to fund its Advanced Technological Education
initiative aimed at awarding grants that focus on the education of science and engineering
technicians at two-year institutions (National Science Foundation, 2020). The Federal
Government, in addition to sounding the alarm, has launched funding initiatives throughout the
decade to alleviate the skills gap. One such initiative is the reauthorization of the Carl D. Perkins
Career and Technical Education Act of 2006, titled Strengthening Career and Technical
Education for the 21st Century Act, which was passed by Congress in 2018 (Thompson, 2018).
In California, the governor and legislature launched the Strong Workforce program,
which funds CTE programs through an annual $248 million recurring state investment
(California Community College Chancellor's Office, 2019e). While investments in education are
being made within the community college system, the outcomes of CTE programs have yet to
fully fill the ‘skills-gap’ and make a return on investment (Jones et al., 2018).
4
Statement of the Problem
Although the demand is high for a CTE-STEM based workforce, people of color and
women remain underrepresented in the industry and have lower community college completion
rates; moreover students of color make up a large percentage of the CTE student population
(Chang et al., 2011; Committee on Underrepresented et al., 2011; Estrada, 2016; Harper, 2010;
Hoffman & Starobin, 2010; Snyder & Cudney, 2017). Therefore, this study will examine the
experiences of CTE students and the factors that influence their anticipated persistence and
success at two-year institutions.
A socio-ecological outcomes (SEO) conceptual model will allow for an examination of
the relationship between various factors that influence student success outcomes, such as,
anticipated persistence, current credits/units enrolled, credits/units earned, and GPA. The factors
will be hereafter described as domains per the SEO conceptual model developed by Harris III
and Wood (2016). The domains of chief concern in this study will be the non-cognitive,
environmental and campus ethos domains, which were derived from Harris III and Wood’s SEO
model (2016). Group differences will then be disaggregated by race/ethnicity, and gender.
Elaborating on the issues that affect students of color, specifically within community
college CTE-STEM programs, are critical for educators to understand in order to meet the ever-
changing and expanding occupational needs of the STEM industry. Thus, without meeting the
needs of students of color, educators will not be able to adequately meet the needs of industry.
Furthermore, workforce training and education through CTE can be a strategic move to address
employment, income, and overall wealth disparities that often plague disenfranchised and
racially minoritized communities (Johnson et al., 2019).
5
Background of the Problem
The United States Census Bureau reports that by 2044, the majority of Americans will be
people of color (Colby, 2014). Latinos currently represent 7 percent of the STEM workforce yet
make up 15 percent of the total workforce, African Americans account for 6 percent of the
workforce and represent 11 percent of the entire workforce (Landivar, 2013). Nationally, Latino
students currently make up half of all school-aged youth and will account for 30 percent of the
total population by 2040 (Malcolm, 2010). Meanwhile, African Americans will grow from 40
million to 60 million by 2060, making up a total of 14 percent of the population (Colby 2014).
Community colleges, therefore, should address the "skills gap" in the industry by
addressing the needs of community college students, and specifically, students of color. Since a
significant proportion of students of color enter post-secondary education via the community
college system, these institutions must focus on improving the factors that lead to success for this
population (Bailey, 2005; Fry, 2010; Moore, 2010). Furthermore, the majority of community
colleges will be made up of students of color, accounting for a total of 61 percent, which will be
34 percent Latino,18 percent Asian-Pacific Islander, and 9 percent African-American. Whites
will account for less than 39 percent (Moore, 2010). While African Americans students have an
equal proportion of entering 4-year as 2-year schools, twice as many as Latino students are going
to a community college over 4-year institutions (Moore, 2010).
Occupations that require less than a bachelor's degree will account for the largest
percentage of future openings and currently represent a large share of the workforce (Offstein,
2016; Olson, 2012;). These "middle-skilled jobs" are represented by workers who are primarily
trained at community colleges in CTE programs. These 'middle-skilled' positions now offer
higher wages than in previous decades, which is not what most assume (Achieve, 2012). Thus,
6
community colleges play a pivotal role in producing these 'middle-skilled' workers that will be in
short supply in the future, representing a highly automated economy with many potential
opportunities for economic gain.
An open admissions policy of community colleges provides a go-to resource of higher
education for students of color and thus, has been a resource for potential social mobility.
However, due to low completion and transfer rates, many educational aspirations of students of
color have been historically stifled (Clark, 1960; Brint & Karabel, 2006; Long, 2016;
Mamiseishvili & Deggs, 2013;). The necessity for an educated STEM workforce has been noted
by many researchers; however, minimal scholarship focuses on the educational success of CTE-
STEM students (Bensimon, et al., 2019).
What is more, the majority of California CTE students are students of color, and their
experiences and needs are mostly absent in the research (California Community College
Chancellors' Office, 2015; Harris III & Wood 2016; Kosloski & Ritz, 2016; Martin & Ritz,
2012). Thus, without meeting the needs of students of color, two-year institutions cannot meet
the workforce needs of industry (Bensimon, et al., 2019; Jackson & Rudin, 2019).
Half of all first-generation students go to community college (Bailey, 2005; Goldrick-
Rab, 2006; Levesque, 2008; Smith 2017). Additionally, over half of the lowest socioeconomic
status (SES) students go to a community college, whereas 70% of the highest SES students go to
4-year institutions. The higher percentage of low-income students who attend community college
illustrates a need for career upward mobility and more significant opportunities by increasing
skill-sets, improving job opportunities, and or integrating career skills with current employment
(Hirschy 2011; Horn 2006; Goldrick-Rab, 2006). The majority of these students are financially
independent, are low income, married or single parents, and received financial aid. Eighty
7
percent worked an average of 32 hours per week, while 41 percent worked full-time. (Goldrick-
Rab, 2006; Horn, 2006; Levesque, 2008; Smith, 2017). Although the age range in CTE-STEM
programs varies wildly, the average age is 26. The lowest age is high school-age students who
are taking dual enrollment courses while in high school, while the highest are students nearing
retirement (Horn, 2006; Goldrick-Rab, 2006; Levesque, 2008; Smith, 2017). Thus, the profile of
a typical community college CTE-STEM student is a 26-year-old male, first-generation, Black or
Latino, works at least 32 hours a week, is financially independent while not making enough, and
needs financial aid. Therefore, it is imperative that a conceptual framework that addresses this
highly minoritized working class community college population is necessary to use.
Conceptual Framework
The conceptual framework for this research study will be the socio-ecological outcomes
(SEO) model developed by Harris III, and Wood (2016). The SEO model demonstrates the
factors that affect the success of students of color at two-year institutions, showing the interplay
between individual, societal, environmental, and campus factors that influence student outcomes
(Harris III & Wood, 2016).
The SEO model is similar to Astin's Input-Environment-Output (IEO) model, which
formulates that student outcomes are influenced by students' background characteristics (inputs)
and the people, curriculum, programs, and policies found in the campus environment (Astin,
1993). The difference is that the SEO model describes the factors as domains that influence
student development and success within the community college system (Harris III & Wood,
2016).
The SEO model is made up of seven constructs. The first two constructs are inputs that
are made up of background (such as age, primary language, generation status, and citizenship)
8
and societal factors (such as stereotypes, prejudice, economic conditions, and identity) (Harris III
& Wood 2016). At the center of the model are four socio-ecological domains: (1) non-cognitive,
(2) academic, (3) environmental, and (4) campus ethos. The non-cognitive domain is made up of
factors contained within the individual student such as self-efficacy (how much a student
believes that they are capable of being successful in college), locus of control, degree utility,
action control (a student’s perception to overcome educational obstacles, focus, and endure
academically) and intrinsic interest (how students enjoy learning and are interested in subject
matter). The academic domain includes faculty-student interactions, academic service use, and
commitment to course study. The environmental domain consists of mediators (finances,
transportation, and external validating interests), commitments (family responsibility,
employment), and stressful life events. Campus ethos consists of sense of belonging (student-
student, student-faculty, student to student service), connectedness, campus resources (access,
efficacy), and internal validating agents (faculty and staff) (Harris III & Wood, 2016). Outcomes
in the SEO model are focused on student success measures such as persistence, achievement,
attainment, transfer, goal accomplishment, and the labor market (Harris III & Wood, 2016).
Understanding the factors that contribute to student success is especially salient within
the community college system. The SEO model provides a conceptual framework that
comprehensively examines the multi-layered experiences that may provide us with the
information necessary to better serve the needs of students. The new funding formula put
forward by both the California Community College Chancellor's office and the state of
California puts outcomes at the center of how community colleges are funded. Outcomes include
student completion, serving low-income students, and closing equity gaps (California
Community College Chancellors' Office, 2019d).
9
Purpose of the Study
Although the demand for a CTE-STEM-based workforce is high, people of color remain
underrepresented in the industry. Latinos represent 7% of the STEM workforce yet account for
15% of the total workforce, and African-Americans are 6% and 11%, respectively (Landivar,
2013). The US Census Bureau reports that by 2044, the majority of Americans will be people of
color (Colby, 2015). Latinos, for example, make-up one-half of all school-aged youth and are the
single fastest-growing demographic who will represent 30% of the population by 2040
(Malcolm, 2010). African Americans will grow from 42 million to 60 million by 2060, which
will make up 14% of the total US population (Colby, 2015). With these population projections, it
is clear to see that people of color will be increasingly relied on to address the "skills gap" in the
workforce.
Community colleges will play a critical role in addressing the "skills gap" (Fry, 2010;
Jackson & Rudin, 2019; Jones et al., 2018). By most accounts, the majority of community
college students are students of color, which, compared to four-year institutions, illustrates the
fact that community colleges are a critical entry point of higher education for most students of
color (Gaxiola-Serrano, 2017; Lasota, 2016; Moore, 2010;).
Community college degree completion rates include 48% for white students, 22% for
Asian Pacific Islander's, 23% for Latinos, and 7% for Blacks (Moore, 2010). Students pursuing
associate’s degrees in community college within STEM-based programs have high dropout rates,
where seven out of ten students left STEM programs entirely (Chen, 2013). These statistics show
the importance of a study that focuses on students of color due to lower completion rates
compared to white students.
10
Thus, the national and California "skills-gap" could be addressed by better serving all
students; however, equity-focused efforts specifically will better address the needs of Black and
Latino students who represent a significant share of the total student and workforce population
now and in the future. These efforts are essential for the state of California, where issues that
arise for equitable student success in CTE programs are barely discussed. These factors need to
be considered in discussions that include funding equity initiatives and the changing funding
formula (Association for Career and Technical Education, 2018).
This study will contribute to a body of scholarly literature that has traditionally ignored
students of color in CTE-STEM programs. Specifically, a scholarly discussion that includes
equity-minded frameworks, and practices is vital to understand factors that contribute to success
for CTE students of color (Johnson et al., 2019).
The purpose of this study is to explore the achievement gap of students of color in CTE-
STEM programs at the community college level. People of color will be a more significant share
of the total student and workforce population in the future, and addressing their needs as students
could aid in addressing the national "skills-gap." Thus, shedding light on the achievement gap of
students of color in CTE programs can help administrators, faculty, and staff recognize the
particular issues that help or impede student success. An SEO conceptual model is vital to
understand how CTE students view themselves and how they view the institution. Previous
research shows that examining and addressing socio-ecological domains is essential to
understanding student perceptions in order to address and alleviate the inequitable outcomes at
two-year institutions (Harris III & Wood, 2016; Fong 2017). Therefore, it is necessary to
examine the following research questions: (1) Are there racial and gender group differences in
Anticipated Persistence, Current Credits/Units Enrolled, Credit/Units Earned, and GPA of CTE
11
Community College students? (2) Do the Non-cognitive, Environmental, and Campus Ethos
domains predict current credits/units enrolled for CTE community college students? (3) Do the
Non-cognitive, Environmental, and Campus Ethos domains predict anticipated persistence for
CTE community college students? (4) Do the Non-cognitive, Environmental, and Campus Ethos
domains predict community college GPA for CTE community college students? (5) Do the Non-
cognitive, Environmental, and Campus Ethos domains predict credits/units earned for CTE
community college students?
Key Terms and Definitions
• Action control: Refers to a student's perception of focus and effort placed on academic
matters (De La Garza et al., 2015).
• Anticipated Persistence/Intent to Persist: Anticipated Persistence is defined as the
likelihood that students will enroll and continue their studies at the community college
(Guaracha, 2018).
• Campus Ethos Domain: Campus ethos consists of a sense of belonging (student-student,
student-faculty, student to student service), connectedness, campus resources (access,
efficacy), and internal validating agents (faculty and staff) (Wood et al., 2015).
• Career and Technical Education (CTE): Career and Technical Education can broadly be
described as career preparation within 16 career clusters that focus on academics and
technical skills, knowledge, and training for the workplace (Advance Career and
Technical Education, 2019).
• Career and Technical Education-Science Technology Engineering and Math (CTE-
STEM) is defined as an educational program that focuses on the career preparation of the
12
STEM field short of a four-year degree, which includes scientific and engineering
technicians (Smith & Starobin, 2017).
• Degree Utility: the value a student places on their academic endeavors, degree or
certificate (De La Garza et al., 2015).
• Environmental Domain: is comprised of hours worked per week, food insecurities,
housing insecurities, transportation, and stressful life events (Wood et al., 2015).
• Intrinsic Interest: measures how students enjoy learning and are interested in the subject
matter (De La Garza et al., 2015).
• Locus of Control: Locus of control refers to the students' perception of the amount of
control they have over their own educational future (De La Garza et al., 2015).
• Non-cognitive Domain: The non-cognitive domain captures students' perceptions and
responses to their educational experiences and includes the following subscales: intrinsic
interest, academic self-efficacy, degree utility, locus of control, action control. Masculine
identities and racial/ethnic affinity are also part of the domain but will not be used in this
study (Wood et al., 2015).
• Self-efficacy: how much a student believes that they are capable of completing academic
coursework successfully (De La Garza et al., 2015).
• Sub-baccalaureate: a degree or certificate obtained at two-year institutions such as an
associate's degree, sometimes referred to a degree or certificate below a bachelor's degree
(Rios‐Aguilar et al., 2018).
13
Chapter Two: Literature Review
Community college Career and Technical Education (CTE) students face numerous
obstacles to persistence and success; therefore, it is necessary to explore the literature regarding
community college CTE students. The purpose of this literature review is to explore the factors
that help or hinder the success of students in CTE programs at the community college broadly
and students of color in particular. This chapter will present 1) a review of the literature of the
community college system and purpose of Career and Technical Education programs 2) review
of the literature of the factors that influence CTE student success and 3) a review of the Socio-
Ecological Outcomes (SEO) conceptual framework that helps describe the factors that influence
student success within the community college system. This structure will help address the
following research questions: (1) Are there racial and gender group differences in Anticipated
Persistence, Current Credits/Units Enrolled, Credits/Units Earned, and GPA of CTE Community
College students? (2) Do the Non-cognitive, Environmental, and Campus Ethos domains predict
current credits/units enrolled for CTE community college students? (3) Do the Non-cognitive,
Environmental, and Campus Ethos domains predict anticipated persistence for CTE community
college students? (4) Do the Non-cognitive, Environmental, and Campus Ethos domains predict
community college GPA for CTE community college students? And finally (5) Do the Non-
cognitive, Environmental, and Campus Ethos domains predict credits earned for CTE
community college students?
Community College CTE History and Purpose
Community colleges are distinctly a U.S. invention, born in the early 20th century as
local and national leaders realized that a more skilled and educated workforce was necessary to
compete globally (American Association of Community Colleges, 2019b). The history of the
14
California community college system can be traced back to 1907 when the California State
Legislature passed the Caminetti Act, which was the first in the nation that authorized local
school districts to offer postgraduate lower-division courses offered by universities (Tollefson,
2009; Wattenbarger 1995). In 1917, the Ballard Act included funding for junior colleges and
regulations on how to establish a junior college (Tollefson, 2009). By 1920, community colleges
enrolled no more than 10,000 students nationally (Brint & Karabel, 2006). Community colleges
were often first initiated by local school boards and were expanded from local high schools
(Beach, 2011; Tollefson, 2009; Wattenburger, 1995). Initially, the mission of community
colleges was to train teachers, skilled labor, and provide a pathway towards the university
(American Association of Community Colleges, 2019b; Beach, 2011; Long, 2016; Nevarez &
Wood, 2010). Two wings emerged in the early formation of the community college system, one
engaged in workforce development and another towards transfer to four-year universities (Dowd,
2007; Gilbert & Heller, 2013; Vasquez & Wood, 2014; Nevarez & Wood 2010).
Workforce training and development has been part of the mission of the community
college system since its inception (Beach, 2011; Brint & Karabel, 2006; Tollefson, 2009). In
fact, William Harper, whom some consider to be the father of the Junior Colleges, called for the
inclusion of vocational education at these two-year institutions (Beach, 2011). Subsequently
California junior colleges created many technical programs in agriculture, manual and domestic
arts that were often terminal (Beach, 2011). The graduates from these occupational focused
programs would fit in a middle-skill position between low skilled manual laborers and the
university graduated professional workforce. These Vocational programs grew and diversified
with the advent of technology and the subsequent stratification of labor from the 40’s onward to
15
the present, new programs focused on health, nursing, electronics and automation have now
become popular programs that fill a unique niche in the American labor market (Beach, 2011).
Notably since the inception of junior colleges is that the majority of students had always
aspired to transfer yet had low transfer rates. Beach (2011) states that the community college
system “created an often-competing focus between students and administrators: Students sought
out the academic transfer curriculum, yet university and junior college leaders promoted the
vocational curriculum.”
Today, community colleges comprise over 5.8 million students (Community College
Research Center FAQs, 2019). While the community college system is generally beholden to
three agencies that include government, business, and 4-year institutions, graduation and transfer
rates remain low (Baldwin, 2017; Crosta, 2014; O'Gara et al., 2009). In response to historically
low completion and transfer rates, the California Community Chancellor's Office, at the behest
of the Governor Jerry Brown, has reformulated the funding formula from enrollment to now
including student outcomes such as degrees, certificates, and transfers over just enrollment by
census date (California Community College Chancellor’s Office, 2019). Moreover to increase
student completion rates, the state of California has also adopted Assembly Bill 705, which has
eliminated remedial coursework while requiring all students to start at college-level English or
math while providing the necessary support to ensure success in the course (California
Community College Chancellor’s Office, 2017).
Factors That Influence CTE Student Success
Workforce development is a critical need for industry and economic development. As
such it is critical that the relevant literature regarding CTE student success be examined. This
section will be a review of the literature of the factors that influence CTE student success.
16
Hirschy’s (2011) seminal article on CTE student success is by far the most relevant and
foundational research paper in the area of CTE student success. She cites the relevant literature
in the field of CTE and discusses why these students are in need of a focus as many CTE
students drop out of their selected CTE programs, which other research has subsequently
confirmed (Chen, 2013). Moreover, Hirschy’s contribution is not so much that its a novel
approach as the model is put forward is an amalgam of different models, what's novel is the
focus on CTE students. Hirschy (2011) describes a typical student model for success such as
student characteristics, the college environment and student success, however one thing Hirschy
does point out which is special to this model is the inclusion of career integration, such as
networking, socialization of professional norms, and work experience.
CTE and Race
For the past two decades, researchers have focused on the success of students of color in
higher education (Harper, 2006; Harris III & Bensimon 2007; Nogurea 2003). In Confronting the
Racial-Colonial Foundations of Higher Education (2018), Stein remarks that the significant
foundational hallmarks of the U.S. education system were subsidized by violence, slavery,
colonization, and exclusion of non-white people. Very little research has explored the history of
racism, segregation, and educational inequality in the community college system partly because
of the lack of data collection that disaggregated student demographic data by race and ethnicity
(Beach, 2011). In general, before 1963, American educational institutions did not collect racial
demographic data (Beach, 2011). Moreover, as Pascarella and Terenzini (2005) note, there has
been a lack of research regarding community colleges but has been growing steadily since the
1990s.
17
Some of the research does place a small lens on demographic details of students of color
in CTE programs, researchers, in general, do not take into account the varied experiences of
students of color in CTE programs. Hirschy (2010) is notable because she is one of the few
researchers who developed a conceptual model of student success centered on CTE students at
the community college level. Moreover, Hirschy does state that CTE is demographically
minoritized; however, she does not connect this fact with the racist nature of the educational
system and how it disproportionately affects students of color and their success (Harper &
Hurtado 2007; Harper, 2009; Bensimon 2013; Bensimon 2017). Giani in Does Vocational Still
Imply Tracking? Examining the Evolution of Career and Technical Education Curricular Policy
in Texas (2019) states that CTE has been historically a mechanism to divert students of color and
low-income students away from four-year pathways. Most and or all research does not examine
how students of color are either persisting or exiting CTE programs. The demand is high for a
CTE-STEM based workforce, yet people of color and women remain underrepresented in the
industry. Additionally, the number of students who complete certificates and or degrees in CTE-
STEM community college programs remains low (Chen, 2013). Community colleges will play a
critical role in closing the skills gap and the gap in equitable educational outcomes. However,
without addressing the needs of students of color and women, the community college education
system will not be able to address the skills gap adequately.
Furthermore, as many researchers have found, vocational education has historically been
seen as a substandard form of education meant to divert students of color away from post-
secondary pathways (Gonzalez, 2013; Oakes, 1985; Oakes & Guiton, 1995; Rosenbaum, 1976).
As Gonzlez (2013) notes in his chapter on the efficiency of vocational education, segregated
Mexican schools had always had a vocational focus, and Anglos were the only ones who were on
18
the college preparatory track. Gonzalez (2013) reports that tracking was standard for students of
color throughout the southwest because educational and political leaders saw students of color as
incapable of a college education and could only work with their hands, what is more students of
color needed to be Americanized. In the 1960s, there was a sharp backlash against vocational
tracking as the civil rights movement grew, and people of color started demanding a college
education (Beach, 2011; Gonzalez, 2013)
CTE and Gender
Community College CTE students are composed of a higher percentage of women.
However, their numbers in CTE-STEM programs are dramatically low (Smith, 2017; Levesque,
2008). In industry, women are marginalized to the lower end, lower-paid, and highly repetitive
work of manufacturing operations, making up a total of 21 % of that classification and comprise
less than 5 percent of welders, 4 %of skilled machinists, 3 % of electricians, of which represent
the higher end, higher pay of the CTE-STEM industry (Eggerth, 2012; Smith, 2017; US Dept of
Labor, 2011). What this data shows is that there are women within technical professions but not
in the higher-skilled technical positions. Moreover, this data shows that these women are
primarily women of color (Eggerth, 2012). What is more, the scholars who do focus on issues of
gender within CTE, have not explicitly examined the minoritized fashion of specific sectors of
the manufacturing industry (Domina, 2017; Lester, 2017; Toglia, 2013). Examining why women
of color who make up 21 percent of the lower-skilled manufacturing workforce are not
encouraged to move into higher-skilled technical positions is noteworthy.
SEO Conceptual Framework
According to Harris III and Wood, the SEO conceptual model was developed from a
model that focused on Black male success in the community college system. This model
19
originated from an interdisciplinary approach using literature and research on the experiences of
Black men in higher education, community college student success, Black identity development,
and in particular Black masculinity (Harris III & Wood, 2016).
Harris III and Wood initially focused on the needs of Black male students within the
community college system, citing that most scholarly works focused on students of color at four-
year institutions, where conceptual and theoretical models did not take into account the
development and success of Black male students at two-year institutions (Harris III & Wood
2016). After reviewing and synthesizing the literature on Black male student success Harris III
and Wood (2016) were able to identify five factors that explained the experiences and outcomes
of Black men in community colleges: social factors, non-cognitive factors, academic factors,
environmental factors, and institutional factors. These five factors became the basis for an
expanded socio-ecological outcomes model, which then included students of color (Black,
Native Americans, Latinos, and South East Asian). Following the expansion, the SEO model was
also field-tested through the Community College Success Measure (CCSM). The CCSM thus,
became a tool that established student benchmarks and identified areas in need for improvement
(Wood & Harris III, 2013). The CCSM is an assessment instrument that was completed by
nearly 4,000 male community college students at 27 colleges (Harris III & Wood, 2016).
20
Figure 1
Socio-Ecological Outcomes Model
Note: Harris III, F., & Luke Wood, J. (2016). Applying the Socio‐Ecological Outcomes Model to
the student experiences of men of color. New Directions for Community Colleges, 2016(174),
35-46.
Inputs
The inputs refer to the circumstances that occur in students' lives prior to college that
influence their experience and interpretations of the college life. Inputs include: age, time status
(part-time versus full-time), veteran status, primary language, citizenship status, generation
status, and (dis)ability status (Wood & Harris III, 2015). Societal factors include stereotypes,
prejudice, economic conditions, and capital identity projection (i.e., glory-seeking materialism
21
and excessive consumerism) (Wood & Eisen, 2012). These two input factors help educators
understand the perceptions that students bring with them, which in turn are influenced by the
four socio-ecological domains that students encounter while in college; the non-cognitive,
academic, environmental, and campus ethos (Harris III & Wood, 2016).
Non-Cognitive Domain
The non-cognitive variables explore students’ experiences, backgrounds, and how these
factors relate to student success. The non-cognitive domain is based on factors relevant to
students' intrapersonal lives and identities. Researchers have concluded that non-cognitive
factors have a greater potential in identifying the capabilities of non-traditional students than
intelligence tests (Hyatt, 2003).
The intrapersonal includes affective and emotional responses to personal life pressures
and the collegiate environment. Five constructs were identified to being strong contributors to
student success for students of color (Harris III & Wood, 2014). These five intrapersonal factors
include students’: academic self-efficacy (students confidence in their academic ability), locus of
control (students feelings of control over their academics), degree utility (students beliefs in the
value of their academic endeavors), action control (student's perception to overcome educational
obstacles, focus, and endure academically), and intrinsic interest (how students enjoy learning
and are interested in the subject matter). Identities were excluded from this study however, they
include gender (masculine/feminine), racial/ethnic affinity, breadwinner orientation, and help-
seeking orientation (Community College Success Measure, 2019). However, for this study,
identities will be excluded and only the five intrapersonal factors will be used for this study.
Consideration of non-cognitive factors has greater potential than traditional intelligence tests
when it comes to identifying capabilities and traits of nontraditional students (Hyatt, 2003;
22
Sedlacek, 2004; Sternberg, 1986). Tracey and Sedlacek (1984) argued that non-cognitive
variables are more predictive of academic success in Black students.
Environmental Domain
The environmental domain refers to factors external to the institution that has an impact
on students' success in college. The environmental domain includes the following variables:
mediators, commitments and stressful life events. Mediators include outside encouragement,
finances, and transportation. Commitments include family responsibilities and employment.
Stressful life events could be a myriad of outside factors such as housing insecurity or food
insecurity up to and including legal problems. The environmental factors can challenge students'
ability to be successful in community college. According to Harris III and Wood (2014),
elements within the environmental domain influence a student’s academic and noncognitive
domain. More specifically, stressful life events such as students who are not able to provide the
basic needs of food and shelter. Their research provides us with valuable knowledge regarding
food and housing insecurities by demonstration the influences and impact it has on the student’s
academic performance, interpersonal relationships, and social and personal identities.
Campus Ethos
The nine campus ethos variables in this study were: (a) caring staff, (b) faculty belonging,
(c) faculty personnel, (d) faculty preference, (e) faculty welcomeness inside of class, (f) faculty
welcomeness inside of class, (g) service accessibility, (h) service efficacy, and (i) staff
validation. These are significant variables in that student success can be influenced by the feeling
of inclusivity on college campuses (Tinto, 1993). Early college experiences along with a caring
culture can support a positive welcoming climate that overall contributes to students’ sense of
belonging to the campus community (Hurtado & Carter, 1997).
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Student Success Measures
Student Success as defined by the SEO model includes, anticipated persistence, current
credits/units enrolled, credits/units earned and GPA. Anticipated persistence is defined as the
likelihood that students will enroll and continue their studies at the community college. Current
Credits/Units enrolled includes all courses the student is enrolled in during that current semester.
Credits earned include how many credits/units a student has earned. GPA is the students grade
point average.
Summary of Literature Review
The literature regarding CTE within the community college system is limited. It is not
surprising that the literature is limited since most educational research is focused on the
development of students at 4-year institutions who are primarily homogenous, academically
prepared, and represent a wealthier type of student (Chen, 2013). This limited scope reveals the
nexus of race, gender, class, and first-generation status of CTE-STEM community college
students and the importance they have in the United States. Furthermore, the research on CTE
regarding students of color, campus racial climate beyond demographics is also scant. The above
literature review contributes to the research of community colleges, and more specifically,
Career Technical Education and campus racial climate and its impact on the success of students
of color in CTE programs. Moreover, it brings to light the history of racist tracking and puts at
the center an equity framework and mindset within CTE that is sorely missing in practice and
research. Most research is mostly centered on 4-year institutions, PWIs, and residential
campuses.
The literature on CTE students and programs was absent, with several keyword searches
such as Campus Climate and CTE finding no articles. Many articles talk about the student
24
population is primarily first-generation, immigrant, and overwhelmingly students of color. No
articles specifically address the issues of students of color in CTE. It is as if students of color
who have been tracked into CTE since the '60s have been abandoned there. Further studies are
needed to examine this critical population. Therefore, it is imperative to research the following
questions as it pertains to the experiences of CTE community college students. The following
questions will help guide the methodology within the next chapter.
Purpose of the Study
The goal of this study is to first explore the racial and gender group differences in the
SEO outcomes of CTE community college students. Secondly, the predictive relationship
between each independent variable domain that is, the non-cognitive, environmental, and campus
ethos domain, to the dependent variables of anticipated persistence, current enrollment, credits
earned and GPA for CTE community college students.
Research Question 1:
Are there racial and gender group differences in Anticipated Persistence, Current Credits
Enrolled, Credit Earned, and GPA of CTE Community College students?
Hypothesis 1: There will be racial and gender group differences in the outcomes of Anticipated
Persistence, Current Credits Enrolled, Credit Earned, and GPA of CTE Community College
students.
Research Question 2:
Do the Non-cognitive, Environmental, and Campus Ethos domains predict anticipated
persistence for CTE community college students?
25
Hypothesis 1: Higher scores in the Noncognitive domain will predict anticipated persistence.
Hypothesis 2: Higher scores in the Environmental domain will predict anticipated persistence.
Hypothesis 3: Higher scores in the Campus Ethos domain will predict anticipated persistence.
Research Question 3:
Do the Non-cognitive, Environmental, and Campus Ethos domains predict current credits
enrolled for CTE community college students?
Hypothesis 1: Higher scores in the Non-Cognitive domain will predict current credits/units
enrolled.
Hypothesis 2: Higher scores in the Environmental domain will predict current credits/units
enrolled.
Hypothesis 3: Higher scores in the Campus Ethos domain will predict current credits/units
enrolled.
Research Question 4:
Do the Non-cognitive, Environmental, and Campus Ethos domains predict credits/units
earned for CTE community college students?
Hypothesis 1: Higher scores in the Non-Cognitive domain will predict credits/units earned.
Hypothesis 2: Higher scores in the Environmental domain will predict credits/units earned.
Hypothesis 3: Higher scores in the Campus Ethos domain will predict credits/units earned.
Research Question 5:
Do the Non-cognitive, Environmental, and Campus Ethos domains predict community
college GPA for CTE community college students?
26
Hypothesis 1: Higher scores in the Non-Cognitive domain will predict community college GPA.
Hypothesis 2: Higher scores in the Environmental domain will predict community college GPA.
Hypothesis 3: Higher scores in the Campus Ethos domain will predict community college GPA.
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Chapter Three: Methodology
This study investigated factors that contribute to community college CTE students’
anticipated persistence, current credits/units enrolled, the number of earned credits/units, and
GPA. This chapter reviews the study’s methodology, including the relevant participant
demographic characteristics, instrumentation, and recruitment procedures.
Participants
Participants of this study were recruited from a large urban community college in
California. The college has a diverse student body of approximately 30,242 students enrolled in
the Fall of 2016 (California Community College Chancellor's Office Management Information
System Data Mart 2019). This college was selected because of its robust offering of CTE
programs. For the Fall of 2016, 35.4% of the student body was enrolled in over 12 units, 54.2%
were enrolled below 12 units, and a total of 10.4% were enrolled in NonCredit. The cohort of
2011-2012, with reported outcomes in 2016, had a persistence rate of 84 percent, whereas CTE
success rates were 61.7% (California Community College Chancellor's Office Management
Information System Data Mart, 2019b). According to the Chancellor's Office CTE student
success is measured by the percentage of students who attempted a CTE course for the first-time
and completed more than 8 units in the subsequent three years in a single discipline vocational or
occupational program and who achieved any of the following outcomes within six years of entry:
a) Earned any AA/AS or credit Certificate (Chancellor’s Office approved) b) Transfer to four-
year institution (students shown to have enrolled at any four-year institution of higher education
after enrolling at a CCC) c) Achieved “Transfer Prepared” (student successfully completed 60
UC/CSU transferable units with a GPA >= 2.0) (California Community College Chancellor's
Office Methodology For College Profile Metrics, 2019c).
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Participants in the current study included 354 credit-seeking students enrolled in the CTE
program for the Fall of 2016. They included 155 female (46.4%), 177 male (53%), and two
gender non-conforming (.6%) CTE college students. 20 students did not report their gender. The
majority of the students identify as Asian (n = 141, 39.8%) and Latinx (n = 103, 29.1%),
followed by Black (n = 39, 11%), and White (n = 24, 7.8%). Other race/ethnicities reported by
participants included Middle Eastern (n = 8, 2.3%), multiethnic (n = 26, 7.4%), and “other” (n =
7, 2.0%). Most of the participants are in the 18-24 age group (n = 284, 80.2%) and the 25 - 31
age group (n = 45, 12.7%). See Table for a summary of participants’ demographic
characteristics.
Table 1
Frequency Distribution of Demographic Characteristics of Participants.
n %
Sex
Male 177 53
Female 155 46.4
Non-Conforming 2 .6
Race
Asian 141 39.8
Black 39 11.0
Latinx 103 29.1
White 24 7.8
Middle East 8 2.3
Multiethnic 26 7.4
Other 7 2.0
Age Group
Under 18 4 1.1
18 – 24 284 80.2
25 – 31 45 12.7
32 – 38 12 3.4
39 – 45 3 .8
46 – 52 6 1.7
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Instrumentation
This study used the Community College Success Measure (CCSM), which is a student
assessment tool used to help identify factors influencing the experiences and outcomes of
underserved community college students (Community College Success Measure, 2019). The
survey was administered by the Community College Equity Assessment Lab (CCEAL) at San
Diego State University (SDSU). CCSM was validated over a three-year process at 60 community
colleges and has been implemented at over 90 community colleges throughout the United States
(Community College Success Measure, 2019). The deliverables include a report that identifies
the disproportionate impact by race/ethnicity, gender as well as predictive modeling of factors
influencing student engagement, use of services and focus in college (Community College
Success Measure, 2019).
The CCSM is a 20-30-minute paper survey that measures factors influencing student
success in seven domains and 32 topical areas. These areas include the following seven domains
1) Background/defining domain: Race/ethnic affiliation, gender affiliation, sexual identity,
respondent age, income, time status, veteran status, generation status, athletic participation, high
school GPA, degree goals, education goals, basic remedial development education, total
credits/units, major, parents education and parents birth. 2) Non-cognitive domain: self-efficacy,
degree utility, and locus of control. 3) Identity domain: racial identity, help-seeking, and
breadwinner orientation. 4) Academic domain: use of student services, and engagement with
faculty. 5) Environmental domain: hours worked per week, food insecurities, housing
insecurities, and commute. 6) Campus ethos domain: a sense of belonging, welcomeness to
engage, and validation. 7) Success outcomes: anticipated persistence, current credits enrolled,
credits earned and grade point average (GPA) (Community College Success Measure, 2019a).
30
Each construct and their subscales will be elaborated below, including sample questions,
responses, scales, and Chronbach alpha. The following domains were not included in this study
consist of the Identity Domain, and the Academic Domain.
Background Domain
The background domain covers student demographic information. Background
information includes race/ethnicity, such as Latinx, African-American, Asian, White,
Multiethnic, other, and gender. Race and Ethnic Background was grouped together for this study
due to the number of sampled students. For example, the instrument included nine different
categories of Asian students, but in this study, they were all grouped into one category. African
American and African students were also grouped together. Mexican American, Central
American and South American were also grouped to comprise the LatinX population. Middle
Eastern, Native American and multi-ethnic students were excluded due to low sample size.
Background information survey included questions regarding age, parental education, high
school GPA, and student income. A sample question of income as an ordinal measurement
includes, "What is your annual income? Please report your annual income and other family
members' income who support you. Include income from all sources (e.g., work, government aid,
stocks)." The CCSM then gives survey respondents the following options: $20,000 or less;
$20,001- $40,000; 40,001-60,000; $60,001-80,000; $80,001or more (Guaracha, 2018).
Student Success Outcomes
Utilizing the SEO model, this study defined student success as their anticipated
persistence, current credits enrolled, credits earned prior to the current semester, and their current
GPA. Each student success outcome will be defined and how each is measured.
31
Anticipated Persistence
Anticipated persistence is defined as students’ self-perceived likelihood to enroll and
continue their study the next semester. It was measured with the following question. “Please
indicate what is most likely to occur after this semester? The responses for this question utilized
the following scale: 1: Not coming back because I completed my goals 2: Probably not coming
back 3: Taking a break but will be back 4: Coming back 5: Absolutely coming back”
Credits Enrolled
Current Credits Enrolled is defined as students self-reported range of current credits
enrolled, during the semester when this survey was taken. It was measured with the following
question. “Please indicate the total number of credits/units you are enrolled in this academic
term (semester, quarter).” The responses for this question utilized the following scale: 1) 1-5
credits 2) 6-11 credits 3) 12-15 credits 4) 16 or more credits
Credits Earned
Credits Earned show the range of current credits enrolled the semester when this survey
was taken as reported by the student. It was measured using the following question. How many
total credits/units have you earned (not counting courses you are currently taking)? The
responses for this question utilized the following scale: 1) None yet 2) 1 to 14 credits 3) 15 to 29
credits, 4) 30 to 44 credits, 5) 45 to 60 credits, 6) 61 credits or more.
Grade Point Average (GPA)
Grade Point Average shows the students self-reported grade point average. It was
measured using the following question. GPA which used the following Scale 1: No GPA 2: 0.5
to .09 (F to D-) 3: 1.0 to 1.4 (D to C-) 4: 1.50 to 1.93 (C- to C) 5: 1.97 to 2.44 (C to B-) 6: 2.45
32
to 2.9 (B- to B) 7: 2.91 to 3.4 (B to A-) 8: 3.41 to 4.0 (A- to A).
Non-Cognitive Domain (Intrapersonal Factors)
The non-cognitive domain for this study included only the intrapersonal factors which
captures students' perceptions and responses to their educational experiences and includes the
following subscales: intrinsic interest, academic self-efficacy, degree utility, locus of control,
action control. The domain included identity questions; however, they were excluded from this
study. The non-cognitive domain had combined the intrapersonal factors into a combined
composite score. Questions were based on a six-point Likert scale from “Strongly Disagree,
Disagree, Somewhat Disagree, Somewhat Agree, Agree, and Strongly Agree." Academic self-
efficacy measures how confident a student feels in their ability to complete their assignments
(e.g., "I have the ability to excel in my coursework"; α = .93). Intrinsic interest measures how
students enjoy learning and are interested in the subject matter (e.g., "What I learn in class is
interesting" α = .75). Locus of control refers to the students' perception of the amount of control
they have over their own educational destiny (e.g., “My academic success is in my own hands”;
α = .73). Degree-utility can be defined by how the student perceived how useful their time in
school will help with their career goals. "The time I spend in school will help me achieve my
personal goals"; (α = .71). Action control subscale includes items that measure a student's
perception to overcome educational obstacles, focus, and endure academically (e.g., "I am
completely focused on school"; α = .68). (Wood & Harris III, 2013; Guaracha, 2018).
Environmental Domain
The environmental domain refers to factors external to the institution that has an impact
on students' success in college (Urias et al., 2016; Harris III et al., 2017). The environmental
domain was especially salient for men of color who experienced external life circumstances in
33
ways that differ from their peers (Harris III et al., 2017). These may direct their time, resources,
and attention which may affect their college life (Harris III & Wood, 2016). Collected data
include: off-campus hours worked per week, number of dependents supported, stressful life
events, employment status, and the amount of time spent caring for others. The environmental
domain variables were combined into a composite score. A sample question includes: "During
this past week, how many hours did you spend time working for pay off-campus?" Options
include: None; 1-5; 6-10; 11-15; 16-20; 21-25; 26-30; 31- 35; 36-40; 41 or more (Guaracha,
2019).
Campus Ethos Domain
The campus ethos variables in this study include: (a) caring staff, (b) faculty belonging,
(c) faculty personnel, (d) faculty preference, (e) faculty welcomeness inside and outside of class,
(f) service accessibility, (g) service efficacy, and (h) staff validation. The Cronbach alpha for the
campus ethos variables include: caring staff (α=.51), faculty belonging (α =.61), faculty
personnel (α=.51), faculty preference (α=.57), faculty welcomeness inside of class (α=.66),
service accessibility (α = .58), service efficacy (α =.60), staff validation (α =.35). The campus
ethos domain variables were combined into a composite score. A sample question using a six-
point Likert scale of Strongly Disagree, to Strongly Agrees includes the following: the
"Instructor (1) cares about my perspective in class; (2) values interacting with me during class;
and (3) values my presence in class; (4) cares about my success in class; and (5) believes I
belong here." (Guaracha, 2019).
Procedure
This study used an existing data set carried out by the CCEAL team at a large urban
community college in the Fall of 2016. The administration had requested the survey to see how
34
and in what ways the institution could improve student success and, more specifically, for
students of color and marginalized groups suffering from disproportionate impact.
The instrument was distributed via a scantron and was confidential. The survey was
voluntary and was distributed randomly to various course sections and included 1,101 students.
Students were able to opt-out of the survey before finishing it. From this data set, CTE students
were grouped and used exclusively for this study.
35
Chapter Four: Results
The purpose of the study was to first investigate group differences in the success
outcomes of (Anticipated Persistence, Current Credits Enrolled, Credits Earned, and GPA) of
Career and Technical Education (CTE) community college students. The following questions
explored the predictive relationship between the domains of the non-cognitive, environmental
and campus ethos to student success outcomes for CTE students. This chapter will review the
findings of the study, including the preliminary correlational analysis and results of the five
research questions.
Preliminary Correlational Analysis
To examine the overall relationships between the major measured variables, a Pearson-
product correlation analysis was conducted. Table 2 provides the summary.
Table 2
Zero-order Pearson Product Correlations of Measured Variables for CTE Students
Variables Persist Enrolled Credits GPA Non-Cog Env Campus
1. Gender .04 -.21*** .04 .04 .12* .06 -.08
2. Persist -- .11* -.20*** .10 .07 -.02 -.01
3. Credits Enrolled -- -.10 .19*** .04 -.20*** .15**
4. Credits Earned -- .33*** .05 .13* .01
5. GPA -- .20*** .02 -.01
6. Non-Cog -- .08 .46***
7. Env -- .13*
8. Campus --
Note. All scores are scaled scores. 1: Gender (1=male, 2=female); 2: Persist: likelihood to
continue; 3: Enrolled: the number of credits/units currently enrolled; 4: Credits: total credits/units
students have earned prior to current semester; 5. GPA; 6. Non-Cog: Non-Cognitive Domain; 7
Env: Environmental Domain; 8 Campus: Campus Ethos Domain.
* p < .05; ** p < .01; *** p < .001
36
Gender was associated with the likelihood to return the next semester (r = -.21, p < .001)
and non-cognitive domain (r = .12, p = .031). More specifically, male CTE students reported a
higher likelihood to be enrolled in more credits/units the current semester but reported lower
scores in non-cognitive domain, suggesting male students reported lower perceptions of their
educational experiences (e.g., lower intrinsic interests, lower academic self-efficacy, less sense
of control of their educational destiny, etc.). Overall, students’ anticipated persistence was
associated with the number of credits/unit they enrolled in the semester (r = .11, p = .048) and
the number of credits they have earned so far (r = -.20, p < .001), suggesting those students who
were currently taking more credits/units or those who have earned less credits/units so far were
more likely to see themselves returning the next semester. GPA was associated with both the
number of credits/units enrolled currently (r = .19, p < .001) and the number of credits/units
earned (r = .33, p < .001). In other words, students with higher GPA enrolled in more
credits/units in the current semester and they also have earned more credit/units so far. In
addition, GPA was also associated with students’ non-cognitive domain, (r = .20, p < .001),
suggesting that those students with higher cognitive-domain scores also reported higher GPA.
Lastly, there were positive associations among students’ non-cognitive, environmental, and
campus ethos domain scores, suggesting that CTE students with higher non-cognitive
intrapersonal factors regarding their educational experiences (e.g., intrinsic interests, academic
self-efficacy, degree utility, locus of control, and action control) also reported higher
environmental external factors (e.g., more off-campus work, more dependents supported, more
stressful life events, spending more time supporting others), and higher campus ethos factors
(i.e., more validation from faculty, more validation from staff, and feeling higher sense of
belonging from faculty).
37
The purpose of the study was to first investigate group differences in the success
outcomes of (Anticipated Persistence, Current Credits Enrolled, Credits Earned, and GPA) of
Career and Technical Education (CTE) community college students. The following questions
explored the predictive relationship between the domains of the non-cognitive, environmental
and campus ethos to student success outcomes for CTE students.
Research Question One: Are there racial and gender group differences in Anticipated
Persistence, Current Credits Enrolled, Credit Earned, and GPA of CTE Community
College students?
Research question one explored if there were differences in student success outcomes
based on students’ race and gender. Four 4 (racial groups) X 2 (gender groups) factorial
univariate analyses of variances were conducted with anticipated persistence, current credits
enrolled, credits earned, and GPA as the criterion variables and race and gender as independent
variables. Due to the small size of some racial and gender groups, this research question only
included four racial groups (Asian, Black, Latinx, and White) and two gender groups (male and
female) in the analyses.
Anticipated Persistence
Results of the 4X2 factorial univariate analyses of variance indicated that there were
significant interaction effects between gender and race in CTE students’ anticipated persistence,
F (3, 279) = 3.27, p = .022. There were no significant group differences by race or gender itself,
indicating when examining race alone, there were no differences in CTE students’ anticipated
persistence (i.e., the likelihood to return the next semester) between Asian, Black, Latinx, and
White students. Similarly, when examining gender alone, there were no differences between
male and female CTE students’ anticipated persistence. However, follow-up pos thoc analyses
38
revealed several differences when gender and race were examined together. First, among male
CTE students, there were racial group differences, F (3, 152) = 3.33, p = .021. Games-Howell
post hoc analyses indicated that Latino male CTE students reported significantly higher
likelihood to return the next semester (anticipated persistence), p = .047 than Asian male CTE
students. There were no racial differences among the female CTE students. Second, within Asian
American students, female Asian American students reported significantly higher likelihood to
return the next semester (anticipated persistence), t (130) = -2.17, p = .032. See Table 3 for a
summary of the student success outcome descriptive statistics by race and gender. Table 4
outlines the results of the univariate analyses and post hoc analyses.
Table 3
Means and Standard Deviations of Student Success Outcomes by Race and Gender
1 2
Male Female
Mean SD n Mean SD n
Persistence
Asian 4.17 1.06 81 4.55 .81 51
Black 4.47 .52 15 4.27 1.03 22
Latinx 4.60 .79 48 4.26 1.03 47
White 3.75 1.54 12 4.36 1.21 11
Credits Enrolled
Asian 3.10 64 81 3.00 .69 51
Black 2.93 .70 15 2.45 .74 22
Latinx 2.88 .79 48 2.30 .86 47
White 2.75 .87 12 .26 .92 11
Credits Earned
Asian 3.10 1.55 81 3.29 1.54 51
Black 2.60 1.30 15 2.64 1.76 22
Latinx 3.06 1.62 48 3.28 1.85 47
White 3.00 1.71 12 3.10 1.81 11
GPA
Asian 6.14 1.87 81 6.86 1.93 51
Black 5.67 1.23 15 4.59 2.42 22
Latinx 5.67 1.86 48 5.68 1.67 47
White 6.50 1.93 12 6.55 1.29 11
Note. All scores were scaled scores.
39
Table 4
Factorial Univariate Analysis of Variance for Student Success Outcomes
Source df F p Group Differences
Persistence
Race 3 .90 .444
Gender 1 .58 .448
Race x Gender* 3 3.27 .022 Asian M > Asian F; Latino > Asian M
Credits Enrolled
Race*** 3 7.60 .000 A > B, L
Gender** 1 8.01 .005 M > F
Race x Gender 3 2.13 .096
Credits Earned
Race 3 1.25 .293
Gender 1 .30 .584
Race x Gender 3 .03 .992
GPA
Race*** 3 7.19 .000 A > L, B; W > B
Gender 1 .068 .795
Race x Gender 3 2.34 .073
Note. M = Male; F = Female; A = Asian; B = Black; L = Latinx; W = White
* p < .05; ** p < .01; *** p < .001
Credits Enrolled
Results of the 4X2 factorial univariate analyses of variance with the number of
credits/units enrolled in the current semester as the criteria variable indicated that even though
there were no significant interaction effects between gender and race in CTE students’
enrollment, F (3, 279) = 2.13, p = .096, there were significant racial, F (3, 279) = 7.60, p < .001
and gender differences, F (1, 279) = 8.01, p = .005. Follow-up post hoc analyses of variance
revealed that when examining race alone, Asian American CTE students enrolled in significantly
more credits/units than Black (p = .020) and Latinx (p < .000) CTE students in the current
semester. In addition, when examining gender alone, male CTE students enrolled in significantly
more credits/units than female CTE students, t (308.84) = 3.95, p < .001.
40
Credits Earned
Results of the 4X2 factorial univariate analyses of variance indicated that there were no
differences in the number of credits/units earned prior to the current semester based on gender or
race.
GPA
Results of the 4X2 factorial univariate analyses of variance with college GPA as the
criteria variable indicated that there were significant differences based on race, F (3, 279) = 7.19,
p < .001, but not gender. More specifically, follow-up post hoc analyses revealed that White
CTE students had significantly higher GPA than Black students, p = .016, and Asian CTE
students had significantly higher GPA than both Black, p < .001, and Latinx CTE students, p =
.019.
Research Question Two: Non-cognitive, Environmental, and Campus Ethos Domains and
CTE Community College Students Persistence
A simultaneous multiple linear regression with CTE students’ anticipated persistence as
the criteria variable and non-cognitive, environmental, and campus ethos domains as predictor
variables was conducted. Results indicated that when examined together, the three domains did
not significantly explain the variances in CTE students’ self-report likelihood to return and enroll
the next semester, F (3, 350) = .74, p = .527. None of the domains was a significant predictor.
See Table 5 for a summary of the statistics.
41
Table 5
Summary of Simultaneous Regression Analysis for Student Success Outcomes
Variables R
2
F B SE β t p
Persistence .01 .74 .527
Non-Cognitive .03 .02 .09 1.45 .149
Environmental -.02 .04 -.02 -.40 .693
Campus Ethos -.01 .02 -.04 -.69 .491
Credits Enrolled .07 8.74 .000
Non-Cognitive -.01 .02 -.03 -.51 .610
Environmental*** -.14 .03 -.22 -4.21 .000
Campus Ethos** .04 .01 .19 3.23 .001
Credits Earned .02 2.27 .080
Non-Cognitive .04 .04 .06 .99 .322
Environmental* .17 .07 .13 2.39 .018
Campus Ethos -.02 .03 -.04 -.63 .533
GPA .05 6.26 .000
Non-Cognitive*** .17 .04 .25 4.3 .000
Environmental .02 .08 .01 .26 .794
Campus Ethos* -.07 .03 -.12 -2.07 .039
* p < .05; ** p < .01; *** p < .001
Research Question Three: Non-cognitive, Environmental, and Campus Ethos Domains and
CTE Community College Students Credits Enrollment
A simultaneous multiple linear regression with CTE students’ number of credits/units
enrolled in the current semester as the criteria variable and non-cognitive, environmental, and
campus ethos domains as predictor variables was conducted. Results indicated that when
examined together, the three domains explained 7% of the variances in the number of
credits/units enrolled in the current semester, F (3, 350) = 8.74, p < .001, which was significant.
Furthermore, environmental domain and campus ethos were both significant predictors, offering
significant unique contributions to CTE community college students’ number of credits enrolled
in the current semesters. More specifically, those CTE students who experienced less
42
environmental external institutional factors (e.g., hours working off-campus, hours providing
care to dependents, etc.) enrolled in more credits/units in the current semester, t = -4.21, p <
.001; and those CTE students who experienced more campus ethos factors (e.g., experiencing
more validations from faculty and staff, and more sense of belonging from faculty) also enrolled
in more credits/units in the current semester, t = 3.23, p = .001.
Research Question Four: Non-cognitive, Environmental, and Campus Ethos Domains and
CTE Community College Students Earned Credits
A simultaneous multiple linear regression with CTE students’ number of credits/units
earned prior to the current semester as the criteria variable and non-cognitive, environmental,
and campus ethos domains as predictor variables was conducted. Results indicated that when
examined together, they did not significantly explain the variances (2%) in CTE community
college students’ number of credits/units earned, F (3, 350) = 2.27, p = .080. However, the
environmental domain was a significant predictor, t = 2.39, p = .018. This means that even
though environmental domain has a significant predictive relationship with the number of
credits/units earned prior to current semester (i.e., those CTE students who experience more
environmental external stress factors were also more likely to have more credits/units prior to
current semester), the variances it contributed were not significant enough to explain or predict
CTE students’ earned credits.
Research Question Five: Non-cognitive, Environmental, and Campus Ethos Domains and
CTE Community College Students GPA
A simultaneous multiple linear regression with CTE students’ college GPA as the criteria
variable and non-cognitive, environmental, and campus ethos domains as predictor variables was
conducted. Results indicated that when examined together, the three domains explained 5% of
43
the variances in CTE community college students’ GPA, F (3, 350) = 6.26, p < .001, which was
significant. Furthermore, non-cognitive domain and campus ethos were both significant
predictors, offering significant unique contributions to CTE community college students’ number
of credits enrolled in the current semesters. More specifically, those CTE students who reported
more intrapersonal non-cognitive factors (e.g., academic self-efficacy, degree utility, etc.) were
more likely to have higher GPA, t = 4.32, p < .001; and those CTE students who experienced
more campus ethos factors (e.g., experiencing more validations from faculty and staff, and more
sense of belonging from faculty) were more likely to have lower GPA, t = -2.07, p = .039.
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Chapter Five: Discussion
The study's purpose was first to investigate group differences of Career and Technical
Education (CTE) community college students to the success measures of anticipated persistence,
current credits enrolled, units earned, and GPA as administered through the Community College
Success Measure (CCSM). The study then explored the predictive relationship between the non-
cognitive, environmental, and campus ethos domains to student success measures for CTE
students.
The study revealed that success measures differ depending on CTE students' race and
gender as hypothesized. What is more, the intersection of race and gender also produced
statistically significant results. Moreover, the results showed that the three domains (non-
cognitive, environmental, and campus ethos) do predict some of the success measures as
hypothesized. This chapter will provide a discussion of these results, as well as implications for
practice. Limitations of this study, and possible avenues for future research, will be included in
this discussion.
The Relationship Between Students Background and Success Measures for Community
College CTE Students
The current study investigated the racial and gender group differences of CTE
community college student outcomes measured by the CCSM. Four racial groups and their
corresponding genders were analyzed in their relationship to anticipated persistence, current
credits enrolled, units earned, and GPA as the dependent variables and race and gender as
independent variables. The following describes statistically significant group differences for
CTE students in relation to the success measures.
45
Anticipated Persistence
The study revealed several statistically significant group differences when gender and
race were examined together. However, there were no racial differences among the female CTE
students. Among male CTE students, there were racial group differences. Latino male CTE
students reported statistically significantly higher likelihood to return the next semester than
Asian male CTE students. This finding is in line with the literature that Latino students may
indicate having a higher level of persistence based on parental and social support where a "good
education" means going to community college or earning an occupational certificate which is
deemed a success (Lee & Zhou 2013; Hurtado et al., 1996). Furthermore, Latinos do not
distinguish between a neighborhood community college, a local college, and a four-year
university, though they are more likely to go to a community college (Desmond & Lopez, 2009).
On the other hand, Asian Americans may seem to have a lower persistence because they see
community colleges as a stepping stone towards moving on to a four-year school such as a
University of California (UC) or a California State University (CSU). Lee and Zhou (2015) point
out that among the Asian American community, any deviation from attending a four-year
university may be admonished and would be disapproved by parental and social support systems.
Therefore, Asian American students may appear to have a lower persistence level at the
community college because of the perception that a community college is a "lower" level
institution (Lee & Zhou, 2015).
Second, among Asian American students, female Asian American students reported a
statistically significantly higher likelihood to return the next semester as anticipated persistence.
This may be because many of the respondents were nursing students who see the importance of
46
nursing and or health-related degree because of family expectations and influence (Dos Santos,
2020).
Current Credits Enrolled
Results of the analyses of variance with the number of units enrolled in the current
semester as the criteria variable indicated that even though there were no statistically significant
interaction effects between gender and race in CTE students' enrollment, there were statistically
significant racial and gender differences. Follow-up post hoc analyses of variance revealed that
Asian American CTE students enrolled in statistically significantly more units than Black and
Latino CTE students in the current semester when examining race alone. This is corroborated by
research that shows that Black and Latino students generally take fewer units than their peers due
to financial and employment obligations (Harris III & Wood, 2016). Furthermore, credits
enrolled may be affected by discontinuous enrollment, where students do not enroll for a period
of time due to financial pressures and are common to lower socioeconomic status (Goldrick-Rab,
2006).
When examining gender alone, male CTE students enrolled in statistically significantly
more units than female CTE students. Community college female enrollment intensity certainly
outpaces their male counterparts in non-CTE programs (Harris III, 2010; Mamiseishvili &
Deggs, 2013). CTE male students may enroll in more units due to several factors. One such
factor includes a masculine identity where male students take on a "breadwinner" role where
work and earning money are prioritized over academic endeavors (Harris III & Wood, 2016).
Another factor contributing to a lower enrollment intensity for female CTE students could point
to a male-dominated CTE culture that creates an unwelcome classroom environment by both
47
faculty and their male counterparts. Women thus, choose to opt-out and go into more feminized
CTE and Non-CTE programs (Lester, 2017).
Credits Earned
The analyses indicated no differences in the number of units earned before the current
semester based on gender or race. This data is remarkable because Black and Latino students are
earning units in comparable numbers with their peer groups; however, they do not enroll in
significantly more units than their peers during the semester. This data indicates that Black and
Latino students are taking units at a lower intensity but taking more units over a period of time,
which could explain lower completion rates over time. Which can point to the breadwinner
orientation discussed by Harris III and Wood (2016) in that black and Latino males often
prioritize earning money and work over their educational endeavors. The literature on excess
units and community college efficiency models shows that the CTE students of color in this
study may be exploring different programs and may also lack quality advising (Shulock 2011;
Ziedenberg, 2015). Not to mention that community colleges' low cost may be another reason
students may want to learn about other subjects that may pique their interests, and colleges have
a budgetary incentive to lure students in to take more classes. However, Kramer (2018) reports
that efficiency models increase Latino student completion rates, whereas Black student
completion rates were marginal.
GPA
The analyses of college GPA as the criteria variable indicated that there were statistically
significant differences based on race, but not gender. More specifically, follow-up post hoc
analyses revealed that White CTE students had a statistically significantly higher GPA than
Black students. Asian CTE students had a statistically significantly higher GPA than Black and
48
Latino CTE students. The results thus, confirms the literature regarding racial differences in
GPA among general education students (Bumphus, 2016; Harris III & Wood, 2014; Palacios &
Alvarez, 2016; Pino, 2004). More recently, policy groups such as the National Skills Coalition
and the Association of Career and Technical Education recently taken up the equity challenge
and have released reports and recommendations to alleviate educational inequities within CTE
(James-Gallaway et al., 2020; Johnson et al., 2019; Romanillos, 2019). One notable research
article outlined the influence that CTE professors have on student learning; however, it did not
address racial group differences (Lancaster, 2019). On the other hand, the Asian American
Paradox (2015) provides evidence of what Lee describes as "stereotype promise" where teachers
and counselors "routinely perceive underachieving Chinese and Vietnamese students as smart
and high-achieving, anointing them as deserving of placement on the most competitive academic
tracks." In contrast, their black and Latino counterparts are not given that "stereotype promise,"
which can explain one factor in racial group differences in GPA for CTE students.
The Relationship between Non-Cognitive to Student Success Measures
The present study examined the relationship between the non-cognitive domain and
student success measures. This study focused on the interpersonal factors which were combined
to create a composite score; these subscales included; academic self-efficacy (confidence in
academic achievement), degree utility (beliefs in the value of their academic endeavors), locus of
control (perception of control over their academics), and action control (perception to overcome
educational obstacles) and intrinsic interest (how students enjoy and are interested in learning the
subject matter). According to researchers, the non-cognitive domain influences student success
(Harris III & Wood, 2016; National Academies of Sciences, Engineering, & Medicine, 2017;
Palacios & Alvarez, 2016; Palmer & Strayhorn, 2006; Wood et al., 2014;). Besides, these non-
49
cognitive scores were, according to researchers, more influential to student success than purely
cognitive factors for nontraditional students (Harris III & Wood, 2013; Hyatt, 200; Sedlacek
2005).
The results from this study revealed that the non-cognitive domain was a statistically
significant predictor of CTE community college students' number of units enrolled in the current
semester in addition to GPA. Thus, CTE students in this study who reported higher intrapersonal
non-cognitive scores were also more likely to have a higher GPA. These findings show that
students who have higher non-cognitive scores will have higher confidence in their academic
ability and will help their cognitive scores measured in GPA. As previously noted, the GPA
variable indicated that there were statistically significant differences based on race. The GPA
variable may influence students’ own perception of success and would also reinforce the non-
cognitive domain through both positive and negative stereotypes as teacher perceptions influence
student outcomes (Lee & Zhou, 2015).
In the preliminary correlational analysis, campus ethos was also statistically significant in
its relationship to gender. Women reported higher non-cognitive intrapersonal scores. This
finding may represent women's representation in this study, whom researchers report complete
and achieve greater success measures than men in postsecondary education (Lee & Ransom,
2011). Furthermore, the women in this study were primarily in healthcare programs, which
shows the gendered nature of certain majors and disciplines (Fluhr et al., 2017; Teig & Susskind,
2008). This finding may also be representative of social and familial norms in Asian American
culture, like the article I Am a Nursing Student but Hate Nursing: The East Asian Perspectives
between Social Expectation and Social Context (2020). Furthermore, this gendered CTE program
may point to a sense of responsibility that women have to their family and profession as
50
caregivers. Also, female students may perceive that their academic performance may be tied to
higher earnings when they complete their program, thus helping their families and fulfilling their
role as caregivers (Lester, 2017).
The Relationship between Environmental to Student Success Measures
This study's environmental domain was a statistically significant predictor of current
credits enrolled. CTE students who reported experiencing more environmental stress factors
(e.g., hours working off-campus, hours providing care to dependents, stressful life events, and
commuting to campus) were enrolled in fewer units in the current semester. In line with this
finding the U.S. National Center for Education Statistics (2016) found that 86% of students in
CTE programs were employed, compared to 82% of students on the transfer track. Additionally,
74% of CTE students worked in the field they studied, compared to 53% of academically
oriented transfer students (U.S. National Center for Education Statistics, 2016). This points to the
fact that CTE students are working in their chosen field, contributing to environmental pressures
that affect their enrollment patterns. What’s more, students who worked more than 30 hours per
week showed a likelihood of leaving programs all together compared to those who worked less
than 30 hours a week (Guaracha, 2014; Harris III & Wood, 2017; Vasquez et al., 2019; Wood &
Williams, 2013).
The environmental domain also revealed that those CTE students who experience more
environmental external stress factors were also more likely to have more units before the current
semester. However, the variances in the data were not enough to predict the number of units
earned. This finding's significance may be due to the changing circumstances of both the student
and the CTE program in real-time. The life circumstances of each student can change enrollment
patterns. As CTE programs update due to industry trends, it will also affect students' enrollment
51
patterns. Both of these factors may be inhibiting students' ability to complete coursework on
time, which may influence the number of units taken and may be represented as excess units as
this study revealed (Shulock 2011; Van Noy et al., 2016; Ziedenberg, 2015). Also, some
programs may take longer for students to complete as they are bound by professional accrediting
standards (such as nursing, or electrical programs), thus lengthening the time to complete
coursework. This finding shows that CTE programs must consider ways for students to have a
clear program with embedded milestones, program alignment, active advising and support that
will thus increase completion rates (Fox, 2020; Lamothe, 2015; Van Noy et al., 2016).
The Relationship Between Campus Ethos to Student Success Measures
Campus ethos showed a direct influence on students' non-cognitive domain and academic
outcomes, such as persistence and GPA (Vang, 2018; Vasquez et al., 2019; Wood et al., 2015).
In this study, CTE students who experienced more campus ethos factors (i.e., those students
experiencing more validations from faculty and staff and more sense of belonging from faculty)
enrolled in more units in the current semester. This finding was consistent with the research, as
students who felt validated were enrolled in more units (Harris III & Wood, 2016; Palacios &
Alvarez, 2016a).
On the other hand, this study found that CTE students who reported experiencing more
campus ethos factors also reported having a lower GPA. On the surface, this finding sounds like
it is conflicting with the researchers' SEO framework that encompasses campus ethos as a
positive influence on academic achievement (Harris III & Wood 2016). When Palacios and
Alvarez (2016) applied the SEO model to students of color have they found that, while campus
ethos was high it did not influence their GPA. This finding is consistent with the research that
student of color, who report high anticipated persistence and high campus ethos also reported
52
lower GPA. This finding coupled with what Lee and Zhou (2015) found regarding both positive
and negative stereotypes that influence student success and GPA may point to how CTE faculty
may validate students but may also negatively stereotype Black and Latino students. Moreover,
the findings by Lee and Zhou (2015) show that even though CTE programs in particular and
community colleges in general are enrolling students of color they are not adequately addressing
the low academic achievement of students of color adequately. As Bensimon (2019) points out
about Hispanic Serving Institutions, they are merely programs and schools that enroll students of
color and have yet to truly embrace what it means to be serving those students’ needs.
On a positive note, students may feel that CTE faculty who also have worked in similar
industries are validating agents (Fletcher & Gordon, 2017). Students in CTE, in general, are
currently working in fields similar to their major (U.S. National Center for Education Statistics,
2016). This fact may help in understanding the CTE student’s perception of validation. When
CTE professors who come from a similar field are teaching and reinforce professional industry
norms this may come off as a validating experience. However, when disaggregated by race, the
success measure of GPA shows that Black and Latino students are not on par with their peers.
Faculty may be welcoming to Black and Latino students as enrollees but have yet to combat their
own negative stereotypes (Lee & Zhou, 2015).
Implications for Practice
This study's data provides important implications for Community College administrators,
faculty, staff, and researchers. Community college professionals should become familiar with
CTE and the demographic differences of CTE students' outcomes, environmental stressors,
perceptions, and experiences. Becoming more familiar with how CTE students perceive their
environment inside and outside the classroom will improve the learning environment and
53
facilitate more equitable programs to serve students better. In a new era where California has
recently tied educational budgets to student success outcomes, knowing what helps CTE students
succeed is critical. Additionally, the importance of the non-cognitive, environmental, and
campus ethos domains for CTE students was brought to light so that CTE faculty and staff can
better serve students inside and outside the classroom. For researchers, this study begins to add
to the limited existing literature of community college CTE students and the factors that affect
their success.
Recommendations
California community college educational leaders are challenged with understanding the
various factors that either support or undermine academic success for CTE community college
students. This study explored the differences in success measures for CTE students by race and
gender and found several statistically significant differences in outcomes. Besides, this study
showed several statistically significant relationships between the non-cognitive, campus ethos,
and environmental domains for CTE student success measures. The following recommendations
came from this study.
Institutional Recommendations
In closing the achievement gap, Bensimon (2005) puts forward the importance of
disaggregating data to find and alleviate the achievement gaps for underserved populations. CTE
programs have been historically marginalized as a ‘backwater’ of education and left on the
outskirts of more traditional academic transfer programs. Therefore, CTE programs are often the
last to be thought of when discussing institutional change at community colleges, especially
when it comes to equity-minded practices. What’s more, CTE programs are an entry point for
many working-class Black and Latino students into higher education.
54
In this study, Blacks and Latinos had lower GPAs, higher number of units, and lower
completion rates, which corresponds to the California community college chancellor's office
data. College practitioners and leaders should find ways to provide interventions for both faculty
and for Black and Latino students who need support in developing their academic skills, which
would, in turn, increase their college success rates. Black and Latino students make up the
majority of the state's community college population, and without serving their needs, CTE
professionals will not be able to meet the growing needs of industry. Therefore, it is imperative
that mandating equity-minded practices for CTE administration, faculty, and staff be at the
forefront.
California CTE faculty, at a minimum, must have an Associate's degree, plus six years of
experience to teach in a CTE program. However, the educational and equity-minded knowledge
that this subset of educators must be called into question. If it is the institution that has to meet
students' needs, how prepared are CTE faculty in developing students in a higher education
setting? Are CTE faculty trained in equity-minded practices, and are these faculty and programs
evaluated on equity-minded and culturally relevant pedagogy? How often are these progams
evaluated and when they do, how often is this cycle of inquiry? The clear answer is that only
until recently have CTE educational leaders are now speaking to the issue of equity within the
field of CTE (James-Gallaway et al., 2020; Johnson et al., 2019; Romanillos, 2019). Although
having industry experience is valued, having equity-based racially inclusive practices is not and
is standard for most community college campuses to value content over equity-minded practices.
It is, therefore, imperative that educators find a renewed focus on students of color and how they
succeed within these historically highly minoritized programs such as CTE. Lastly, what is
important to note is that the CTE faculty and administration are limited in their foundational
55
understating of student identity development and pedagogy. One massive barrier for CTE faculty
is the level of expertise required to be CTE faculty as the value is industry experience over
equity based inclusive pedagogy, essentially CTE faculty are skilled on what to teach and not
necessarily how to teach.
Limitations of the Study
The current study's primary limitation was a reliance on existing data carried out by
Community College Equity Assessment Lab (CEAL). What is remarkable is that the instrument
was developed explicitly for community college students, so it is highly relevant for this study.
The CEAL team of researchers selected students randomly, even so as it stands, the inclusion of
CTE is a byproduct. What this data also confirms is the California Chancellor's Office data,
which shows that 35% of community college students are enrolled in some type of CTE
coursework (Career Technical Education in California, 2019). This secondary analysis focused
on a subset of that data, which included CTE students, so this data set cannot necessarily be
generalizable to all CTE community college students. This data set also contains only a small
sample of CTE students within the overall community college system. Therefore, a more
targeted study that exclusively focused on CTE students would have provided a more vibrant and
more detailed CTE student population profile.
Another limitation is the generalizability of the results due to the demographics of the
data set. The community college used in this study has a large percentage of Latino students
(51%). It is a designated Hispanic Serving Institution (HSI) school; however, Asian American
students comprised 39.8% of the current study while only making up approximately 24% of the
school population. Latinos at the school make up 51% of the population, whereas Blacks make
up about 4% of the student population. Within the California Community College system, Asian
56
Americans make up about 14.25% of the population, whereas Latinos make up 44.5%, Whites at
25.8%, and 5.9% Black (CCCCO-Key Facts, 2020).
The CCSM was also limited to self-reported success measures and perceptions of
persistence. Published institutional reports show that this study showed merit in that it verified
this data set for the academic year of 2016-2017. However, a post-test was not conducted, which
would show more substantial and more direct evidence of this study's results. Moreover, the
measure was not used longitudinally and was used at only one point in time.
Implications for Research
The emergent literature for CTE community college students and their success is coming
to the forefront. More importantly, the student perspective and experience in the three domains in
this study show the promise of increasing student success through additional research, which
would inform community college professionals. This study demonstrates that a variety of
research opportunities exist to understand these emerging areas in CTE.
First, this study was taken from a larger data set. It would be beneficial to know the
differences between CTE community college students and other students who have differing
collegiate educational goals such as certificate, transfer, degree, and adult education. These
community college populations may be different, and differences would likely emerge when
studying the various groups of students. Additionally, understanding these differences would
better inform administrators, faculty, and staff on planning more effective programming and
interventions for CTE students.
Secondly, gender and racial group differences within CTE should be examiner further.
Notable differences in persistence, enrollment, units earned, and GPA between groups should be
57
further examined, in addition how and in what ways the different domains affect these differing
populations, and how negative stereotyping affects Black and Latino students.
This study used the CCSM instrument to study CTE community college students.
However, many opportunities exist to understand more broadly these students and what makes
them unique. The importance of the non-cognitive, e.g., academic self-efficacy, degree utility,
etc.), should be further researched in CTE community college students. Also, the broader
understanding of the actors and institutional agents, including professors and counselors, who
can impact CTE students' academic skills on how they contribute or hinder their development,
may yield a better understanding of how to better teach students these skills. Also, a deeper
understanding of how students' skills develop over time through a longitudinal study, or a more
detailed understanding through qualitative measures, such as a focus group, may provide deeper
insight into how students are developing their academic skill set.
Conclusion
The American economy needs more CTE community college graduates to fill job
openings that require a STEM-based specialized skill set. Colleges must increase the number of
students completing degrees and certificates to provide workers who will contribute to the future
economy's growth and success. Understanding how to develop CTE students' non-cognitive and
campus ethos domains and faculty perception of academic stereotypes may increase the number
of students completing college degrees and certificates. Therefore, having more college
graduates, in turn, will assist in filling skilled and high-wage jobs. Furthermore, when educators
can adequately address environmental stressors that influence student success and help students
succeed promptly.
58
The purpose of this study was to understand the demographic differences in success
measures of CTE community college students and to investigate the relationships between these
in the three domains of the non-cognitive, environmental, and campus ethos domains of students.
Differences in success measures emerged, and many of these differences were consistent with
equity gaps in academic achievement in existing literature between historically underrepresented
groups. Additionally, this study found that non-cognitive and campus ethos domains were
predictive of GPA. Notably, the non-cognitive domain is highly predictive of GPA. This study
highlights the importance of understanding negative academic stereotypes and how campus ethos
may not be a predictor for academic success. With this new knowledge, researchers can continue
to understand the importance of the student experience inside and outside the classroom and how
they can contribute to CTE community college student success.
59
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Abstract (if available)
Abstract
Although the demand is high for a Career and Technical Education trained workforce, people of color and women remain underrepresented in the industry and have lower community college completion rates
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Asset Metadata
Creator
Flores-Zamora, Juan Pedro
(author)
Core Title
Factors that contribute to community college career and technical education student success
School
Rossier School of Education
Degree
Doctor of Education
Degree Program
Education (Leadership)
Publication Date
12/13/2020
Defense Date
11/18/2020
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
Career and Technical Education (CTE),community college,OAI-PMH Harvest,Socio-Ecological Outcomes (SEO) Model,student success
Language
English
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Electronically uploaded by the author
(provenance)
Advisor
Chung, Ruth (
committee chair
), Andres, Mary (
committee member
), Olivo, Cynthia (
committee member
)
Creator Email
jfloresz@usc.edu,jtradetech@gmail.com
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https://doi.org/10.25549/usctheses-c89-404153
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UC11668251
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etd-FloresZamo-9215.pdf (filename),usctheses-c89-404153 (legacy record id)
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etd-FloresZamo-9215.pdf
Dmrecord
404153
Document Type
Dissertation
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Flores-Zamora, Juan Pedro
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texts
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(contributing entity),
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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...
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Tags
Career and Technical Education (CTE)
community college
Socio-Ecological Outcomes (SEO) Model
student success