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Mathematics, Engineering, Science, Achievement (MESA) and student persistence in science, technology, engineering, and mathematics (STEM) activities and courses: the perceptions of MESA teacher a...

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MATHEMATICS, ENGINEERING, SCIENCE, ACHIEVEMENT (MESA) AND STUDENT
PERSISTENCE IN SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS
(STEM) ACTIVITIES AND COURSES:
THE PERCEPTIONS OF MESA TEACHER ADVISORS IN THE EFFECTIVENESS OF
INCREASING PUBLIC MIDDLE SCHOOL EDUCATIONALLY DISADVANTAGED
STUDENTS’ INTEREST IN STEM

by
Rhonda Dee Haramis

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

May 2017

Copyright 2017 Rhonda Dee Haramis
2

MATHEMATICS, ENGINEERING, SCIENCE, ACHIEVEMENT (MESA) AND STUDENT
PERSISTENCE IN SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS
(STEM) ACTIVITIES AND COURSES:
THE PERCEPTIONS OF MESA TEACHER ADVISORS IN THE EFFECTIVENESS OF
INCREASING PUBLIC MIDDLE SCHOOL EDUCATIONALLY DISADVANTAGED
STUDENTS’ INTEREST IN STEM
by
Rhonda Dee Haramis

A Dissertation Presented

in Partial Fulfillment of the

Requirements for the Degree

DOCTOR OF EDUCATION

USC ROSSIER SCHOOL OF EDUCATION

UNIVERSITY OF SOUTHERN CALIFORNIA

2017

APPROVED:

___________________________________
Dr. Pedro Garcia, Ed.D.
Committee Chair

____________________________________
Dr. Rudy Castruida, Ed.D.
Committee Member

_____________________________________
Dr. Michael Escalante, Ed.D.
Committee Member
3

Abstract
The main purpose of this research study was to investigate the MESA teacher advisors’
perceptions of MESA’s effectiveness in increasing educationally disadvantaged middle school
students’ interest in STEM activities and courses. Additionally, the researcher explored the
resources needed to successfully support middle school students in their persistence in STEM.
The study was conducted using a mixed-methods sequential approach containing two phases of
investigation. Phase one contained an online survey distributed to 50 USC-MESA teacher
advisors currently working in various middle school sites in the greater Los Angeles area. Phase
two consisted of five MESA advisors who participated in a focus group interview, as well as
individual interviews. The interviews provided deeper insight about the advisors’ perceptions of
specific supports that were most effective in the MESA program. The findings showed that the
advisors believe the MESA program effectively supports students’ interest and persistence in
STEM through engaging hands-on activities, ongoing professional development for MESA
advisors, networking for both students and advisors, and extensive collaboration with community
partners and STEM-based organizations. However, advisors expressed the need for improved
marketing of MESA’s features to all stakeholders to increase participation. Additionally,
advisors reported that additional funding is vital in ensuring the support services meet the needs
of current educational barriers, and to improve the advisor retention rate. The findings from this
study begin to address a gap in the literature surrounding the effectiveness of STEM outreach
programs, and stakeholders’ perceptions of such programs.
4

Preface
Some chapters of this dissertation were coauthored and have been identified as such.
While jointly authored dissertations are not the norm of most doctoral programs, a collaborative
effort is reflective of real-world practices. To meet their objective of developing highly skilled
practitioners equipped to take on real-world challenges, the USC Graduate School and the USC
Rossier School of Education have permitted our inquiry team to carry out this shared venture.
This dissertation is part of a collaborative project with two other doctoral candidates,
Nisha Parmar and Jacob Jung. We three doctoral students have done a cohesive study on the
effectiveness of Mathematics, Engineering, Science Achievement (MESA) on the persistence
and retention of educationally disadvantaged students in science, technology, engineering, and
mathematics (STEM) disciplines. We examined how the MESA outreach program operates at
public middle schools, high schools, and two- and four-year universities in an effort to
understand whether institutions are retaining educationally disadvantaged students in STEM.
However, the process for dissecting and resolving the problem was too large for a single
dissertation. As a result, the three dissertations produced by our inquiry team collectively
address effective STEM outreach programs that support the persistence and retention of
educationally disadvantaged students (see Parmar, 2017; Jung, 2017).

5

DEDICATION

This dissertation is dedicated to my two sons, Nikolas and Enzo, now 11 and 8
respectively. I recognize that my decision to pursue my doctorate did not leave you unscathed.
You started this mission with me when you were so, so young: second grade and kindergarten.
You first-handedly experienced both the joys and the brutal hardships along the way. You
sacrificed SO MUCH: your golden birthday parties when you turned nine and seven on 09/09
and 07/07, numerous opportunities to build lasting friendships, mom volunteering at school to
show that she really exists, two years of pulling out of the science fair, your favorite home-
cooked meals, vacations, and time to just cuddle. I hope that my struggles and accomplishments
will inspire you throughout your lives to keep moving forward. The only time you look back is
to appreciate what you have accomplished and how far you’ve come. And please understand
that tenacity and dedication will get you farther in this world than your innate intelligence.
Never, ever, give up, even when you think that the odds are stacked against you. I love you
bigger than life!

6

ACKNOWLEDGMENTS
This dissertation would never have reached fruition without the people who opened the
gates to opportunity. I want to thank Dr. Pedro Garcia for choosing me to join his group, and
never doubting that I would produce anything less than the highest quality work. I also want to
thank Dr. Rudy Castruida and Dr. Michael Escalante for recognizing and supporting my team’s
passion for minority advocacy in today’s public school system. Ben Louie and Darin Gray were
also critical components in ensuring my team had as many opportunities to gather data for our
study. I truly admire their dedication to the MESA program.
I also want to thank Kimon for never doubting my capabilities, and allowing me the
opportunity to grow professionally. I know these three years have been just as hard on you. I’m
sorry. Our boys are so lucky that you were there to hold down the fort, and I appreciate the
strengths you bring to our family.
Mom, I can’t thank you enough for always being someone I can count on. You assumed
the role of Mom for your grandsons so I could pursue my dream. Your life experiences and
wisdom are the foundations of how I perceive the world and what I believe is my purpose. You
preached that it is my nature to take the more challenging path. Well, it may have been fate or
merely a self-fulfilling prophecy. Regardless, I have learned that nothing in this world is free.
We pay for our accomplishments, one way or another.
I must acknowledge that there were those key individuals who undoubtedly influenced
my decision to pursue my doctorate. You know who you are, and I thank you with all of my
heart. There was a purpose for our paths crossing; a purpose that we never knew existed. No
matter where we end up in our personal and professional journeys, I will never forget what you
have done for me.
7

Lastly, and most importantly, I must express my immense appreciation and gratitude for
my two dissertation partners, Jacob Jung and Nisha Parmar. We began our doctoral journey
together as part of the “Weekend Cohort,” excited, anxious, and apprehensive about the
challenges this program had in store for us. Little did we know that throughout the three years,
we would be critical life supports for each other at various points and in multiple aspects of our
professional and personal lives. Sundays were our saving graces. There were times when we
just needed that confidant to vent, to cry, to laugh, to mourn, to admire, to accept, to motivate, to
dream. I really do not know how I would have made it through the Ed.D program without these
two magnificent human beings. Honestly, I can’t imagine my life without them from here on
forward.

8

TABLE OF CONTENTS
List of Tables .....................................................................................................................10
List of Figures ....................................................................................................................11
List of Appendices .............................................................................................................12
Chapter One: Overview of the Study .................................................................................13
Background of the Problem ...................................................................................15
Statement of the Problem .......................................................................................23
Purpose of the Study ..............................................................................................24
Research Questions ................................................................................................25
Significance of the Study .......................................................................................26
Limitations .............................................................................................................26
Assumptions and Delimitations .............................................................................27
Definition of Terms ................................................................................................28
Organization of the Study ......................................................................................30
Chapter Two: Literature Review .......................................................................................32
Historical Perspective and Politics of STEM .........................................................32
STEM Pipeline .......................................................................................................41
Students in STEM Education .................................................................................57
Outreach Programs .................................................................................................69
Key Features of Effective Programs ......................................................................72
MESA Program ......................................................................................................74
Summary ................................................................................................................75
Chapter Three: Methodology .............................................................................................77
Restatement of Problem, Purpose, and Research Questions ..................................77
Research Questions ................................................................................................79
An Introduction to MESA ......................................................................................80
Quantitative, Qualitative, and Mixed-Methods Study ...........................................83
Population and Sample ..........................................................................................86
Site Selection .........................................................................................................90
Data Collection ......................................................................................................92
Data Analysis .........................................................................................................97
Instrumentation ....................................................................................................100
Ethical Practices ...................................................................................................107
Ethical Interviews ................................................................................................107
Summary ..............................................................................................................109
Chapter Four: Findings ....................................................................................................110
Background ..........................................................................................................110
Purpose .................................................................................................................111
Guiding Questions ...............................................................................................113
Participants ...........................................................................................................114
Quantitative Data .................................................................................................115
Qualitative Data ...................................................................................................116
Findings by Research Question ...........................................................................117
Ancillary Findings ...............................................................................................131
Reflection .............................................................................................................137
9

Summary ..............................................................................................................144
Chapter Five: Discussion .................................................................................................146
Overview of the Study .........................................................................................146
Summary of Findings ...........................................................................................149
Conclusion of Findings ........................................................................................157
Limitations ...........................................................................................................160
Implications for Practice ......................................................................................162
Recommendations for Future Study ....................................................................163
Conclusion ...........................................................................................................165
References ........................................................................................................................166

10

LIST OF TABLES
Table 1. Survey Item Breakdown per Research Question ...............................................102
Table 2. MESA Middle Schools ......................................................................................115
Table 3. Quantitative Survey: Number of Years Served as a Teacher/Advisor
for MESA Middle School ..................................................................................116
Table 4. Participants to the Study ....................................................................................117
Table 5. Survey Items per Research Question .................................................................118
Table 6. Total Mean for Research Question One ............................................................119
Table 7. Research Question One: Mean for Each Teacher Survey Question ..................120
Table 8. Reliability Statistics for Research Question One ...............................................120
Table 9. Participant Survey Questions Correlated to Research Question Two ...............122
Table 10. Total Mean for Research Question Two ..........................................................123
Table 11. Research Question Two: Mean for Each Teacher Survey Question ...............124
Table 12. Reliability Statistics for Research Question Two ............................................124
Table 13. Survey Items per Research Question ...............................................................125
Table 14. Total Mean for Research Question Three ........................................................126
Table 15. Research Question Three: Mean for Each Teacher Survey Question .............127
Table 16. Reliability Statistics for Research Question Three ..........................................128
Table 17. Survey Items per Research Question ...............................................................129
Table 18. Total Mean for Research Question Four ..........................................................130
Table 19. Research Question Four: Mean for Each Teacher Survey Question ...............130
Table 20. Reliability Statistics for Research Question Four ............................................131
Table 21. Ancillary Emerging Themes ............................................................................132
Table 22. Comparison of Support among Framework, Literature, and MESA ...............138

11

LIST OF FIGURES
Figure 1. Conceptual Framework of How Outreach Programs, such as MESA
Target Educationally Disadvantaged Students ...................................................25
Figure 2. Federal STEM Education Funding FY2006, by Agency ...................................37
Figure 3. Model of Leaky Pipeline in STEM ....................................................................43
Figure 4. Multiple Pathways Model of Leaky Pipeline in STEM .....................................56
Figure 5. Alternative Model of Leaky Pipeline in STEM .................................................56
Figure 6. Earned Bachelor’s Degrees in STEM by Race, Class and Gender ....................59
Figure 7. Levels of Corresponding Rigor in Mathematics Courses ...................................61
Figure 8. Levels of Corresponding Rigor in Science Courses ...........................................62
Figure 9. Top Program Goals Selected by Survey Respondents .......................................70
Figure 10. Percentage of Programs that Offer Academic Services, by Service Type .......71
Figure 11. Percentage of Programs that Offer Non-Academic Services, by
Service Type .....................................................................................................72
Figure 12. Explanatory Sequential Mixed-Methods Approach .........................................84
Figure 13. Conceptual Framework of How Outreach Programs such as
MESA Target Disadvantaged Populations .....................................................112

12

LIST OF APPENDICES
Appendix A. Information Sheet .......................................................................................191
Appendix B. Recruitment Letter ......................................................................................193
Appendix C. Consent Form .............................................................................................194
Appendix D. MESA Survey Questionnaire .....................................................................195
Appendix E. Data Collection: Interview Protocol for MESA Teachers in K-12 .............200

13

CHAPTER ONE: OVERVIEW OF THE STUDY
Authors: Rhonda Haramis, Jacob Jung, Nisha Parmar
1

Careers in science, technology, engineering, and mathematics (STEM) are growing at an
accelerated pace. The U.S. Department of Commerce Economic and Statistics Administration
(2011) reported over the past 10 years, growth in STEM careers was three times as fast as growth
in non-STEM careers. Additionally, it was estimated that as of 2012, there were 7.4 million
STEM positions available in the job market, and this number is expected to increase to 8.65
million by 2018 (Wang. M. T., & Degol, 2013). As a result, there has been a renewed focus on
STEM education in the United States in order to remain competitive in the global economy and
promote job growth (Chen, 2009).
However, participation in STEM fields has traditionally been considered a White male
endeavor in the US, with minorities and females less likely to pursue occupations in these
disciplines (Campbell, Denes, & Morrison, 2000; Riegle-Crumb, King, Grodsky, & Muller,
2012). Due to the inequities in access to STEM curricula and courses, a growing concern is
there will be a shortage of qualified individuals, in particular minorities and females, to meet the
projected growth of the STEM field (Chen, 2009). Ensuring the United States has a robust
STEM workforce is imperative for economic growth and stability, and provides minorities and
females a niche in which to excel (Sadler, Sonnert, Hazari, & Tai, 2012). In addition, having a
more diverse workforce allows for improved designs in science and technology that might have
been otherwise overlooked.
The inequity in access to STEM careers is evidenced by the subsequently lower numbers
of high school minorities and females that enter college as STEM majors, persist and graduate
with a STEM degree, and enter a STEM career (Clark Blickenstaff, 2005). While educationally

1
This chapter was jointly written by the authors listed, reflecting the team approach to this project. The authors are listed
14

disadvantaged populations constitute a growing number of students in the public school system,
their presence in STEM does not reflect this trend. A study conducted by the American Council
on Education (Anderson & Kim, 2006) found that 13% of African-American and Hispanic
students elected to pursue a major in STEM, and of those minority students who elected a STEM
major, the graduation rate is nearly half as compared to their White peers (Foltz, Gannon,
Kirschmann, 2014). Similarly, the National Center for Education Statistics’ (NCES, 2006) data
showed that female high school seniors enrolled in STEM majors at one-third the rate of male
high school seniors. Consequently, even when minorities successfully graduate with a STEM
degree, and enter the STEM workforce, they do not receive equal compensation as their White,
male colleagues (Chen, 2009).
As there is an increasing need for qualified individuals in STEM fields, this problem
becomes a priority to understand and contextualize because the absence of minorities and
females from STEM majors leads to inequities in access to STEM curricula, differences in
compensation, and a lack of diversity in the work force (Milgram, 2011). Understanding the
unique barriers that educationally disadvantaged populations face is imperative to increasing
their numbers and persistence in STEM courses during pivotal transitions throughout their
educational careers.
Among the many reasons educationally disadvantaged populations are uniquely
challenged in their pursuit of STEM degrees and careers, four main themes emerged from the
literature. Educationally disadvantaged populations face a lack of institutional support such as
inadequate resources and lack of academic assistance (Griffith, 2010), lack of social or peer
support (Szelényi, Denson, & Inkelas, 2013), negative racial and gender stereotypes (Riegle-
Crumb et al., 2012), and issues related to motivation (Wang, M. T., & Degol, 2013). Each of
15

these four themes will be further broken down into subcategories and examined in detail within
the context of the literature review in the subsequent chapter.
In response to the issue of the underrepresentation of minorities and females in STEM,
many institutions, from primary school through four-year universities, have implemented STEM
outreach programs that aim to increase the retention of educationally disadvantaged populations
in STEM by providing students with academic, social, and emotional support systems within
their institutions. In order to gain a better understanding of how STEM outreach programs work
and the experiences of undergraduate minority females in STEM outreach programs, this
dissertation will examine the effectiveness of current STEM outreach programs on the
persistence and support of English Language Learners (ELLs) in STEM courses.
Background of the Problem
The need for a strong STEM workforce in the US has led to a resurgence in ensuring
there are sufficient numbers of high quality STEM graduates (Foltz et al., 2014). Having a
strong STEM workforce would allow the US to enhance its innovative capacity, economic
development, and global competitiveness (Beede et al., 2011; Foltz et al., 2014). While STEM
specific jobs constitute only 5% of the entire US Workforce, policy makers and leaders in
academics and businesses alike, strongly believe that STEM fields have a significantly higher
impact on the US economy (Hira, 2010). For example, it is widely known that the technical and
scientific industries play an important role in maintaining national security, increasing the
standard of living in the US, and solving the nation’s most challenging issues such as disease
control, infrastructure, and global warming (Hira, 2010).

16

STEM and Federal Initiatives
The STEM workforce has been the target of political action for the past 50 years due to
growing concerns that the US would have inadequacies in the number of high quality STEM
graduates, and would not be able to compete economically with countries such as India and
China (Bare, 2008; Hira, 2010). One such policy that was recently passed by the U. S. Congress,
and signed by former President Bush, was the America COMPETES Act of 2007 (Bare, 2008).
The America COMPETES Act authorized an increase in the nation’s investment in STEM
education from kindergarten through postsecondary education (Bare, 2008). Additionally, the
act increased the number of funds allotted for national organizations focused on science and
technology research such as the National Science Foundation (NSF) and the Department of
Energy (DOE) Office of Science (Bare, 2008).
In 2013, President Obama implemented a 5-year STEM strategic plan that placed three
federal agencies – the NSF, Department of Education (ED), and the Smithsonian Institute – in
charge of oversight of STEM programs, distribution of STEM monies, and monitoring of
program effectiveness (Federal Science, Technology, Engineering and Mathematics [STEM]
Education 5-Year Strategic Plan, 2013). As a result of these national policies, the number of
STEM-focused schools and outreach programs have increased in an effort to recruit and graduate
students in STEM disciplines. However, educational policies such as the America COMPETES
Act and President Obama’s STEM: 5-Year Strategic Plan, were aimed at increasing the future
supply of STEM graduates and did not adequately address the current need for a highly qualified,
diversified STEM workforce.

17

Retaining a Strong STEM Workforce
Previous research has shown that the STEM disciplines struggle to recruit, retain, and
graduate students (Cannady, Greenwald, & Harris, 2014). This remains especially true for
minorities and females, who are disproportionately educationally disadvantaged in STEM fields
as compared to their White peers. For instance, females occupy nearly half the jobs in the US
economy, but females only occupy about 25% of the jobs in STEM (Beede et al., 2011). This is
problematic because as the number of jobs in STEM is expected to increase, the compensation is
also expected to rise as well (U. S. Department of Commerce, 2011). The United States
Department of Commerce (2011) estimated that STEM workers earn 26% more than non-STEM
workers. Thus, it is essential that the number of minority and female students pursuing STEM
disciplines increase in order to remain representative of the US population (Carnes, Schuler,
Sarto, Lent, & Bakken, 2006; Foltz et al., 2014). Furthermore, minorities and females could
bring a much-needed diversified perspective on how to approach global issues that impact
traditionally underserved populations (Foltz et al., 2014; Milgram, 2011).
If the goal is to increase the number of educationally disadvantaged populations in
STEM, then it is imperative to understand why they are not entering STEM disciplines, and why
those who enter STEM are not persisting. Specifically, this study aimed to examine the
mechanisms that contribute to how educationally disadvantaged populations are currently being
supported in STEM endeavors through STEM outreach programs, and why educationally
disadvantaged populations are less likely to persist in STEM majors and careers.
STEM Pipeline
Historically, the conceptual model of students following a STEM trajectory has been
portrayed by an ever-narrowing leaking pipeline (Cannady et al., 2014). The pipeline model
18

suggests that as students approach milestone transitions such as the shift from middle school to
high school, students leave the STEM pipeline. Despite the hundreds of millions of dollars
dedicated to patching up the leaks to increase the number of students retained in STEM careers,
especially women and minorities, the investment has yielded poor returns, and the number of
students who leave STEM fields continues to be an issue of societal and economic concerns
(Clark Blickenstaff, 2005; Cannady et al., 2014).
Minorities and females are especially susceptible to leaking from the STEM pipeline
because these educationally disadvantaged groups face additional barriers peripheral to their
participation and persistence in STEM. They must contend with inequities in academics, societal
and cultural norms that conflict with personal goals in STEM, negative gender stereotypes, lack
of role models, peer criticism, and feelings of being an outsider, which contributes to their
overall persistence in STEM (Thoman, Arizaga, Smith, Story, & Soncuya, 2014).
Barriers to Diversity in STEM
Previous research has indicated that the strongest determinants of choosing a STEM
major in college are students’ prior academic preparation and achievement in mathematics and
science, and their attitudes (interest) in mathematics and science in high school (Cannady et al.,
2014; Correll, 2001; Tai, Sadler, & Mintzes, 2006). For both young women and men, those who
earned higher grades in advanced coursework, were 1.6 times as likely to pursue STEM majors
(Sadler, Sonnert, Hazari, & Thi, 2014). Data from previous studies found that minorities,
including African Americans and Hispanics, take lower level courses in mathematics and
sciences in high school as compared to their White peers, and are therefore inadequately
prepared for college level STEM courses, while females reported negative attitudes regarding
STEM (Tyson, Lee, Borman, & Hanson, 2007).
19

Minority students are less likely to participate in higher-level courses due to lack of
access to rigorous courses. Ogbu and Simons (1998) suggested that minorities face school
systematic factors and community forces that result in their underachievement compared to their
White peers. Additionally, minorities are faced with language barriers, that adversely lead to
limited access to high paying jobs, and result in living in poverty and attending schools with
inadequate resources (Tienda & Haskins, 2011; Yun & Moreno, 2006). Finally, parents of
minority students, specifically involuntary minorities, lack the social capital to advocate for their
students to be in higher-level courses, which are gateway courses to STEM majors (Ogbu &
Simons, 1998). Fortunately, for those minorities who are able to navigate the system and take
rigorous courses in high school, data indicated they are equally likely to pursue STEM majors in
college as their White peers (Tyson et al., 2007). These findings suggest that the lack of
adequate preparation and institutional barriers in access during high school present significant
barriers for minorities who seek to pursue STEM.
Females, on the other hand, may elect to engage in higher-level coursework in
mathematics and science in high school, but are less likely to pursue STEM degrees and careers
than their male peers due to lack of interest in mathematics and science, and lack of self-identity
in STEM (Tyson et al., 2007). First, interest related to STEM is developed during elementary
education and reinforced both negatively and positively throughout experiences in secondary and
postsecondary education. Females are discouraged from pursuing STEM disciplines due to the
competitive nature of the courses and the perceived male-dominant culture in STEM (Riegle-
Crumb et al., 2012). Second, motivational elements that heavily influence persistence and
choices for females in STEM include their self-identity and self-concept in STEM. Females
have difficulty viewing themselves as scientists and have difficulty reconciling and achieving a
20

work-life balance. These findings indicate that females, even when they have the academic
capacity to excel in STEM courses, opt out of these disciplines due to negative attitudes related
to STEM (Tyson et al., 2007).
STEM Outreach Programs and Partnerships
Outreach programs, also known as pipeline programs, are one of the oldest strategies
used to increase the enrollment of students in college and their success in higher education
(Strayhorn, 2011). STEM outreach programs are a division of these pipeline programs that are
specifically focused on the active recruitment, retention, and graduation of educationally
disadvantaged populations, such as minorities and females, in STEM majors (Contreras, 2011).
Outreach programs represent one type of intervention that seeks to improve conditions for
educationally disadvantaged populations by creating a more inclusive and balanced STEM
workforce, increasing outreach and equity to groups that have been excluded from STEM, and
preparing more high quality students for STEM careers (Gilmer, 2007). These STEM outreach
programs operate under the pretenses that implementing and developing interventions that target
the recruitment and retention of minorities and females requires that programs address the two
factors which most significantly impact students’ success rates in college – academic preparation
in mathematics and science and students’ attitudes in mathematics and sciences (Strayhorn,
2011).
STEM outreach programs are highly diverse in their organization, their duration of
program, and their targeted population/demographics. STEM outreach programs range from the
federally funded programs such as Upward Bound and GEAR UP, to state funded programs such
as Mathematics, Engineering, and Science Achievement (MESA) in California (Contreras,
2011). They also include intervention programs established by educational nonprofits, school
21

district partnership programs such as Advancement Via Individual Determination (AVID,
Contreras, 2011), and university partnership programs such as the Minority Opportunities in
Research Program (MORE) at California State University at Los Angeles (CSULA, Slovacek,
Whittinghill, Flenoury, & Wiseman, 2012). What all these outreach programs have in common
is they have evolved to address the key transition periods in a student’s educational career
identified by the conceptual pipeline model. These transitions include: primary school to middle
school, middle school to high school, and high school to college (Cannady et al., 2014).
Furthermore, they provide interventions such as academic enrichment, mentoring and social
development, cultural and gender role models, and emotional support, which for students from
educationally disadvantaged communities are instrumental in creating access where the cultural
message has not always been positive (Contreras, 2011).
Academic enrichment. Because minorities are often denied access to rigorous
curriculum in high school, targeted academic interventions implemented by outreach programs
are used to compensate for the inequities in resources (Contreras, 2011; Gilmer, 2007). The
Academic Investment Program in Math and Science (AIMS) at Bowling Green State University
was purposefully designed to target the needs of minority and female university students who are
traditionally educationally disadvantaged in STEM (Gilmer, 2007). The AIMS program
provided students with an intensive five-week summer course each year during their university
career, which integrated mathematics, science, and peer tutoring. The program was found to
foster a support system, facilitate faculty-student interaction, provide networking opportunities,
assist with financial hardships, and retain more educationally disadvantaged students in STEM
majors (Gilmer, 2007).
22

Social interactions. Outreach programs promote social and career-related pursuits
around issues in STEM, which is imperative to increasing persistence in STEM (Szelényi et al.,
2013). Research relating to the importance of social support showed that participation in a
Living Learning Program (LLP) increased the persistence of females in STEM majors. LLPs are
designed as a cohort model for students, and their use created a sense of community for students,
fostered interactions with diverse peers, and increased professional outcome expectations for
minorities and females in STEM (Szelényi et al., 2013). Moreover, mentoring and fostering
positive relationships between faculty and students in STEM, helped to break down negative
stereotypes of the STEM disciplines, and provided students opportunities to engage in STEM
related research (Gilmer, 2007; Slovacek et al., 2012).
Role models. Historically, the physical sciences, mathematics, and engineering existed
as White, male-dominated professions (Riegle-Crumb et al., 2012). This perception has led to
the gender and racial disparity in STEM. This is further confounded by the issue of a lack of
minority and female role models in STEM (Griffith, 2010; Xu & Martin, 2011). Some
researchers have hypothesized that increasing the number of minority and female faculty in
STEM may increase students’ persistence in STEM (Griffith, 2010). When students are
provided role models that they can identify as similar to themselves, then they are able to
conceptualize themselves in the same role. Accordingly, if students in STEM are provided
faculty and advisors in STEM with whom they can identify with, then they are more likely to
develop a self-identity in STEM.
Emotional support. Students’ self-efficacy is directly related to their motivation and
directly impacts students’ mental effort, active choice to engage in a task, and persistence during
adversity (Rueda, 2011). Minorities and females in STEM majors must contend with negative
23

cultural/gender stereotypes, lack of academic resources, peer criticism, and feelings of being an
outsider, which negatively affects their self-efficacy (Thoman et al., 2014). Outreach programs
that incorporated mentoring and informal professional networks have been instrumental in
helping minorities and females advocate for themselves, reshape their role in STEM, and
increase their self-efficacy (Xu & Martin, 2011). Furthermore, research indicated that the mean
academic self-efficacy and students’ social skills were significantly higher after participation in
pipeline programs (Strayhorn, 2011).
Statement of the Problem

The aim of this study was to explore the effectiveness of the Mathematics, Engineering,
Science Achievement outreach program in influencing educationally disadvantaged middle
school minorities to persist in STEM education. Minorities are the fastest growing subgroup
with the highest growth in grades seven through 12 (Calderon, Slavin, & Sanchez, 2011).
According to Luster (2011), 42% of the total number of students enrolled in US public schools
represent educationally disadvantaged minorities. These escalated numbers in various parts of
America highlight the urgency to invest in this growing population so that they are prepared to
join the workforce in STEM related fields. It is more than speculation that educationally
disadvantaged minorities repeatedly underperform in all areas of academics when compared to
the White majority as well as several other minority subgroups (Gándara, Rumberger, Maxwell-
Jolly, & Callahan, 2003). Faulty education systems and outdated policies and legislation are
significant barriers between minorities and their road to higher education (Gándara et al., 2003;
Yun & Moreno, 2006). Various factors contribute to their marginalization and identification as
educationally disadvantaged students, which include the lack of community resources and
support programs to increase minorities’ access to high demanding fields like science,
24

technology, engineering, and mathematics (STEM), and as a result, severely impede their ability
to acquire high level skills for the STEM workforce (Mohr-Schroder et al., 2014).
Purpose of the Study

The initial purpose of this study was to observe, compare, and evaluate STEM outreach
programs that are currently in place. Moreover, this study explored the effectiveness of the
MESA outreach program on the retention of educationally disadvantaged populations. The final
intent of this study was to identify the key elements that contribute toward a successful STEM
outreach program. This was crucial because it provides future implications for rethinking and
restructuring current STEM outreach programs to ensure they provide equitable services for all
educationally disadvantaged populations.
The conceptual framework was structured around the key elements that create an
effective STEM outreach program for retaining minorities and females in STEM disciplines.
The components of the conceptual framework included the following: academic support systems,
which compensate for inequities in the education system, positive social interactions with like-
minded peers and faculty mentors, built-in support network to counteract negative gender and
racial stereotypes, and motivational elements that influence students’ persistence in STEM
(Figure 1). STEM outreach programs such as the Center for Teaching, Learning, and Outreach
(CTLO) at California Institute of Technology (CalTech), the AIMS Program at Bowling Green
State University, and the MORE Program at CSULA, have proven to be successful due to their
high retention rate of educationally disadvantaged populations. Figure 1 illustrates effective
elements in outreach programs.

25

Figure 1. Conceptual Framework of How Outreach Programs Such as MESA, Target
Educationally Disadvantaged Populations.

Research Questions
1. How is the Mathematics, Engineering, Science, and Achievement (MESA) outreach
program preparing teachers to support educationally disadvantaged middle school
students in Science, Technology, Engineering, and Mathematics (STEM) activities and
courses?
2. How do MESA teachers perceive the impact of the MESA program in the retention of
educationally disadvantaged students in STEM activities and courses?
3. What resources are utilized in the MESA program to prepare and support educationally
disadvantaged middle school students in STEM activities and courses?
4. How do teachers perceive the effectiveness of the MESA program in increasing the
persistence of educationally disadvantaged students in STEM activities and courses?

26

Significance of the Study

STEM not only embodies the integration content and subject matter disciplines, it
prepares students with the skill set of problem solving and critical thinking, which are essential
for the 21st Century. This study aimed to illustrate how effective STEM outreach programs
support the persistence of educationally disadvantaged populations by providing academic
support systems, fostering positive social interactions, building support networks, and
developing student motivation. Additionally, the goal is to increase the number of educationally
disadvantaged minorities and females in identified STEM education and careers through STEM
outreach programs. Ultimately, this study sought to maximize the retention and persistence of
students flowing through the STEM pipeline, close the achievement gap/gender gap/racial gap in
K-16 STEM education, and rebalance social injustices and inequities in the STEM job market.
Limitations

The following study limitations are recognized:
1. Time availability and distance feasibility.
2. The ability to gain access to successful STEM outreach programs was limited.
3. Amount of time needed to collect and analyze the data to determine commonalities of
successful STEM outreach programs.
4. Self-report responses may not be indicative of true responses leading to issues of
reliability and validity of data collected.
5. Small sample size and self-report responses of minorities and females participating in
STEM outreach programs could reduce the generalizability of the findings for this study.

27

Assumptions and Delimitations
Assumptions
The following assumptions were made in this research study:
1. The STEM outreach programs observed in this study are representative of a typical
STEM outreach program that aims to:
a. Increase participation in STEM focused schools and STEM careers
b. Increase the number of educationally disadvantaged minorities and females in STEM
education and careers
c. Close the achievement gap in K-16 education
d. Promote retention and persistence
e. Rebalance social justice
2. The selected schools are a representative sample of a typical successful STEM outreach
program in California.
3. Participants who were surveyed or interviewed responded with honesty and provided
accurate information.
Delimitations
The delimitations of this study were as follows:
1. The low number of successful STEM outreach programs within urban communities in
Southern California available to participate in this study.
2. Only the MESA outreach programs that have been established with four or more years
were selected.
3. Interviews were delimited to educationally disadvantaged minorities and females who are
currently enrolled or have participated in the MESA outreach program.
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Definition of Terms
The following definitions and terminology below are used throughout this study:
• Achievement gap: The discrepancies in student performance outcomes (retention,
persistence, degree completion, STEM career) when comparing student subgroups at the
same program. The subgroups are often characterized by nationality, race, and gender
(Educational Testing Service, ETS, 2016).
• Advanced Placement Program (AP): Established by College Board to help gifted
students earn college course credit while still in high school (College Board, 2016).
• Educationally disadvantaged students: Students placed at special risk due to factors
such as economic status, educational environment, family and home circumstances,
gender, or race (MESA, 2016). For the purposes of this study, educationally
disadvantaged students include minorities and first-generation females.
• Engineering: Applied or practical aspect of several processes used in devising a system,
component, or protocol to meet an identified need (Carberry, Lee, & Ohland, 2010,
p. 71).
• English Language Learners (ELLs): Students who are unable to communicate fluently
or learn effectively in English, who often come from non-English speaking homes and
require specialized or modified instruction in both the English language and in their
academic courses (Kena et al., 2015).
• First-generation student: Students from families with low socioeconomic status or from
middle- or higher-income families without a college-going tradition (College Board,
2016).
29

• Interest: A mental state that is activated, or triggered, by creating “uncertainty, surprises,
novelty, complexity, or incongruity” in the learner as a response to a previously unknown
experience or information (Hidi & Renninger, 2006, p. 4).
• Mathematics: Study of patterns and relationships (Honey, Pearson, & Schweingruber,
2014).
• MESA: Mathematics, Engineering, Science Achievement is a California outreach
program designed to recruit and retain educationally disadvantaged students in STEM
(MESA, 2016).
• Motivation: The process whereby goal-directed behavior is instigated and sustained
(Schunk, Meece, Pintrich, 2012)
• Persistence: A student’s continuation behavior leading to a desired goal (Schunk et al.,
2012). For this study, persistence in STEM was defined as student enrollment in a STEM
major, graduate program, or career.
• Pipeline: The progression from middle school, high school, and postsecondary education
(Cannady et al., 2014).
• Retention: Refers to an institution’s ability to keep students (in STEM) from one
performance period to the next (Tinto, 1997).
• Science: The body of knowledge about the natural world as investigated through the
process of inquiry to uncover new knowledge (Honey et al., 2014).
• Self-efficacy: An individual’s belief or judgment of the capability of organizing and
executing required to complete a task (Schunk et al., 2012).
• Self-concept: A self-perception that influences behavior (Xu & Martin, 2011).
30

• Self-identity: The ability for students to incorporate the STEM culture and profession
into their visions of themselves (Tyson et al., 2007)
• STEM: The integration of science, technology, engineering, and math (STEM) into a
single field of study (Planty et al., 2009).
• STEM outreach program: Outreach programs to support students with curriculum and
resources in their pathway towards a STEM major and eventually a STEM career
(Dickert-Conlin & Rubenstein, 2007).
• STEM workforce: Individual who works with computers (software developers,
information technology, and analysts); engineers, mathematicians and statisticians, life
scientists, physical scientists, and limited social scientists (U. S. Department of
Commerce, 2011).
• Technology: Tools used to solve problems (Honey et al., 2014).
• Underrepresented populations/minorities: Refers to Latino English Language Learners
and female students who are traditionally left out of careers in STEM (Allen-Ramdial &
Campbell, 2014).
Organization of the Study
This study is divided into five chapters. Chapter One provided an introduction to the
study by overviewing the background of the problem, the statement of the problem, and the
purpose and importance of the study. Chapter Two is a detailed review of the existing literature
that pertains to effective STEM education/outreach programs and how they impact academic
support, social support, and emotional support. Chapter Three includes the methodology used in
this study and explains the appropriateness of the mixed-method approach. In addition, the
methodology section includes the sample population, survey instruments, and tools used to
31

analyze the data collected. Chapter Four includes the findings of the study as they relates to the
research questions proposed. Finally, Chapter Five is a summarization of the findings of the
study and provides recommendations and insights for future research opportunities related to the
problem of practice.

32

CHAPTER TWO: LITERATURE REVIEW
Historical Perspective and Politics of STEM
2

In this section, a review of the comprehensive literature details the historical perspective
and political aspects of STEM. This encompasses the ongoing concerns about the STEM
workforce, followed by key legislation that fueled the United States’ decision to make STEM
education a priority. Next, the literature examines the funding allocated to support legislative
policies, and how defining STEM is influenced by the distribution of funding. Finally, an
examination of the desired skill set is provided to support the need for highly qualified
individuals in both STEM and non-STEM fields.
STEM Workforce
During World War II, the United States was a global leader in the establishment of a
highly skilled STEM workforce (Gonzalez & Kuenzi, 2012). The efforts put forth during World
War II afforded the US to take the lead in STEM for military technology, thus improving the
country’s economic standing (Gonzalez & Kuenzi, 2012). In today’s economy, however, the
need to develop the US STEM workforce extends beyond the realm of military advancement.
Although not outwardly advertised, the demand for job candidates with STEM related skills is
becoming increasingly critical across all industries (Bayer Corporation, 2012; Gonzalez &
Kuenzi, 2012). A current debate has surfaced about whether the increase in demand for STEM
degree graduates is accurate or misdiagnosed. Individuals on one side of the spectrum claimed
that America is “overproducing the number of PhDs we need for research and development”
(Bayer Corporation, 2012, p. 618). This justification is based on stagnant wages for math-related
professionals, and the declining rate of STEM identified jobs over the past five years. However,

2
This chapter was jointly written by the authors listed, reflecting the team approach to this project. The authors are
listed alphabetically, reflecting the equal amount of work by all those listed.
33

the opposition stressed that PhDs are not the only individuals needed in STEM companies.
Graduates with 2- and 4-year STEM degrees have increased in demand in non-STEM identified
companies (Bayer Corporation, 2012).
In addition to building a larger pool of high quality individuals to meet the demands of an
evolving STEM workforce, the need for gender and ethnic diversity is a growing concern.
Museus, Palmer, Davis, and Maramba (2011) argued that the demographic composition of
America has changed dramatically over the past several decades. Within the study, the
researchers include a trajectory graph generated by the U. S. Census Bureau that shows the
country’s racial make-up by 2050, and the data predicts a 16% increase in Hispanic
representation over the next 40 years (Museus et al., 2011). Additionally, the number of women
represented in the workforce, and particularly the STEM field, continues to increase nationally
and globally (Espinosa, 2011). The number of females, specifically women of color who attend
college, has increased; however, the number who actually are conferred with a degree in STEM
is not representative of the number of females attending college (Espinosa, 2011). Empirical
studies show that “a more diverse student body in STEM fields lead to a workforce of scientists,
engineers, and mathematicians who are more equipped to function effectively in today’s diverse
and global workforce” (Museus et al., 2011, p. 5).
STEM Legislation
Longstanding interests in America’s goal to improve the country’s science and
technology literacy dates back as far as the first Congress and President George Washington
(Gonzalez & Kuenzi, 2012). However, America’s interest in taking a pioneer role in STEM
education increased during the 20th Century. The National Science Foundation Authorization
Act of 1950 (NSF, 2013) was founded to “develop and encourage the pursuit of a national policy
34

for basic research and education in the sciences” (Gonzalez & Kuenzi, 2012, p. 31; NSF, 2013).
Although the NSF’s primary purpose was to support pre- and post-doctoral STEM students, the
NSF also included teacher institutes to support the improvement of STEM education at the K-12
levels (Gonzalez & Kuenzi, 2012).
The launch of the Soviet Union’s Sputnik in 1957 was also a catalyst in the United State’s
decision to take a more aggressive role in STEM (Gonzalez & Kuenzi, 2012). Growing concerns
about “existing balances in our educational programs which have led to an insufficient
proportion of our population educated in science, mathematics, and modern foreign languages
and trained in technology” (Gonzalez & Kuenzi, 2012, p. 32) prompted the National Defense
Education Act of 1958 (NDEA, National Defense Education Act of 1958). This was the first
time the government offered federal loans to students and funding to states for science,
mathematics, and modern foreign language instruction.
Some scholars argued that the NDEA paved the way for the establishment of one of the
most influential bipartisan measures in the history of the United States, the Elementary and
Secondary Education Act of 1965 (ESEA, Gonzalez & Kuenzi, 2012). When first enacted, the
ESEA did not explicitly include STEM-specific provisions. However, throughout the
subsequent reauthorizations, and more recently, the No Child Left Behind Act of 2001 (NCLB,
U. S. Department of Education, 2002), STEM requirements have been inserted for Local
Educational Agencies (LEAs) to maintain compliance (Gonzalez & Kuenzi, 2012). As of
December 10, 2015, the ESEA bipartisan measure was again reauthorized as the Every Student
Succeeds Act of 2015 (ESSA), and continues to incorporate science and math accountability
measures for each state (Every Student Succeeds Act, ESSA, Sec. 1005 State Plans, 2015a;
STEM Education Coalition, 2015). Officially beginning implementation in the 2017-2018 fiscal
35

year, California legislation will enforce ESSA’s STEM initiatives by ensuring LEAs implement
the New Generation Science Standards (NGSS), assess all students in mathematics in the third
through eighth and eleventh grades, and assess all fifth, eighth, and tenth grade students in
science (California Department of Education, 2015; Every Student Succeeds Act, 2015a).
Moreover, ESSA now permits states to use a portion of its federal funding to integrate
engineering and technology concepts into states’ science assessments (ESSA, 2015b).
In addition to NDEA and ESEA, several policies and initiatives that were passed between
1965 and 2007 continue to influence the persistence of STEM Education and the STEM
workforce today (Gonzalez & Kuenzi, 2012). The Higher Education Act of 1965 (HEA)
authorized funding for higher institutions to assist students and their families with financial
assistance while completing a postsecondary degree (Gonzalez & Kuenzi, 2012; Higher
Education Act of 1965, HEA). However, HEA was reauthorized as the Higher Education
Reconciliation Act of 2005 (HERA, 2006) to earmark approximately $1.4 billion in federal
funding for the Science Mathematics and Research for Transformation (SMART) Grant program
until the 2010-2011 academic year, which awarded $4,000 to students majoring in STEM
degrees (Gonzalez & Kuenzi, 2012; Higher Education Reconciliation Act of 2005, 2006).
Three legislative acts shaped the U. S. Department of Education (ED) to become a
prominent agency in the creation and management of STEM education programs. The
Department of Education Organization Act of 1979 recognized ED as an independent federal
agency. Within this act, science education programs such as the Elementary and Pre-school
Science Teacher Training, and the Minority Institutions Science Improvement, were transferred
over to ED (Gonzalez & Kuenzi, 2012; Department of Education Organization Act, 1979). Soon
afterward, the publication of A Nation at Risk through the National Commission on Excellence in
36

Education (NCEE, 1983) highlighted the ascending economies in Germany and Japan; this
heightened America’s concern about its descending rank globally in educational competitiveness
and spurred the enactment of the Education for Economic Security Act of 1984 (EESA).
EESA’s policies mandated ED to improve teacher training and development in STEM
education by providing grants to states and LEAs (Gonzalez & Kuenzi, 2012 Museus et al.,
2011; EESA, 1984). More recently, the America COMPETES Act of 2007, and its
reauthorization in 2010, approved the creation of a variety of STEM education programs at
several federal science agencies in addition to ED such as NSF, the Department of Energy
(DOE), the National Aeronautics and Space Administration (NASA), and the National Oceanic
and Atmospheric Administration (NOAA, Gonzalez & Kuenzi, 2012; America COMPETES
Reauthorization Act of 2010, 2011). Given the increase in agencies, America COMPETES also
established a federal government-wide STEM education coordinating committee, the National
Science and Technology Council (NSTC), to monitor program effectiveness and reduce the
duplication of services (Gonzalez & Kuenzi, 2012).
STEM Funding
Both the NSTC and the Government Accountability Office (GAO, 2014) conducted
inventory reports in 2011 and 2012, respectively, which identified between 209 and 252 distinct
STEM education programs, and about $3.4 billion dollars earmarked to sustain these programs
(Gonzalez & Kuenzi, 2012; Kuenzi, 2008; Kuenzi, Matthews, & Mangan, 2006). Figure 2
shows the percentage of funding allocated to the key agencies that facilitate STEM education
programs (Kuenzi, 2008).

37

Source: Kuenzi, Jeffrey J. (2008). Science, Technology, Engineering, and Mathematics (STEM) Education:
Background, Federal Policy, and Legislative Action (p. CRS-21). Congressional Research Service Reports. Paper
35.http://digitalcommons.unl.edu/crsdocs/35.

Figure 2. Federal STEM Education Funding FY2006 by Agency

Three distinct programs monopolized approximately $622 million of the total federal
dollars dedicated to STEM education: the Health and Human Services (HHS 27%), the National
Science Foundation Graduate Research Fellowship (NSF, 29%), and the Mathematics and
Science Partnership (MSP, Education 23%) program (Gonzalez & Kuenzi, 2012).
Although the overarching goal of government support in STEM is to increase America’s
competitiveness in the global STEM workforce, the avenues in reaching this goal are numerous
and varied. The Ruth L. Kirchstein National Research Service Awards program, which is
administered by HHS and awards $274 million in STEM funding, targets postgraduate students
who are awarded individual fellowships to support their area of research, particularly in health-
related fields. Award applicants must be US citizens, nationals, or permanent resident aliens
(Gonzalez & Kuenzi, 2012; Kuenzi, 2008).
38

Similar to Kirchstein, the NSF Graduate Research Fellowship awards about $198 million
in federal funding annually to students pursuing master’s and doctoral degrees. This program’s
goal is to increase the size and diversity of the US workforce in science and engineering, with an
emphasis on increasing the representation of women in engineering and computer information
services (Kuenzi, 2008). The program has a capacity to support approximately 1,000 fellows per
year; each selected candidate receives $40,500 in stipends and cost of education to complete
their research (Gonzalez & Kuenzi, 2012; Kuenzi, 2008). Enacted in 1952, the NSF fellowships
represent one of the longest-running federal STEM programs in the history of STEM grants
(Kuenzi, 2008). NSF also established the Research Experiences for Undergraduates (REU)
program; it is the largest of the NSF STEM education programs that supports undergraduates’
participation in active research in both individual and group projects (Kuenzi, 2008). Applicants
for the NSF graduate and undergraduate programs must also be US citizens, nationals, or
permanent resident aliens.
Both NSF and ED have established the Mathematics and Science Partnerships (MSP).
While NSF’s MSP program aims to create partnerships between businesses, communities, and
schools to improve K-12 student achievement outcomes, ED’s MSP program focuses on
community partnerships to improve the knowledge and skill set of STEM teachers (Kuenzi,
2008).
STEM Definitions
The U. S. Department of Education’s (2007 as cited in Brown, 2012) definition of STEM
education refers to the programmatic aspects,
Science, Technology, Engineering, and Mathematics education programs are defined as
those primarily intended to provide support for, or to strengthen, science, technology,
39

engineering, or mathematics (STEM) education at the elementary and secondary through
postgraduate levels, including adult education. (p. 7).
Merrill (2009 as cited in Brown, 2012), however, defined STEM as
A standards-based, meta-discipline residing at the school level where all teachers,
especially science, technology, engineering, and mathematics (STEM) teachers, teach an
integrated approach to teaching and learning, where discipline specific content is not
divided, but addressed and treated as one dynamic, fluid study. (p. 7)
Researchers argued that defining STEM is quite complicated due to its ties to federal
funding, vastness in program goals, and a variety of targeted subgroups (Gonzalez & Kuenzi,
2012; Kuenzi, 2008; Kuenzi et al., 2006). The $3.4 billion earmarked, and the 207 plus
programs dedicated to STEM education, target a number of groups such as existing individuals
in the STEM workforce, postgraduate students, undergraduate students, kindergarten through
12th grade students, educationally disadvantaged minority subgroups, and women (Bayer
Corporation, 2012; Gonzalez & Kuenzi, 2012; Kuenzi, 2008; Kuenzi et al., 2006). Moreover,
Gonzalez and Kuenzi (2012) and Kuenzi (2008) asserted that STEM education programs define
STEM based on the targeted disciplines such as engineering and physical sciences, biological
and biomedical sciences, computer and information sciences, mathematics and statistics, and
environmental sciences.
Program goals also affect the STEM definition; the study conducted by the GAO (2014)
on federally funded STEM programs in 2005 found multiple goals within and among the
identified 207 programs, which influenced the definition of STEM (Gonzalez & Kuenzi, 2012;
Kuenzi, 2008; Kuenzi et al., 2006). Six major goals were found to recur throughout the
programs: (1) attract and prepare kindergarten through postsecondary students to pursue and
40

persist in all areas of STEM coursework, (2) attract students to pursue and persist postsecondary
degrees and postdoctoral appointments, (3) provide college and graduate students with research
opportunities in STEM fields, (4) attract graduates to pursue careers in the STEM field,
(5) improve teacher education and preparation in STEM areas, and (6) improve or expand the
capacity of institutions to promote STEM fields (Kuenzi, 2008). These goals, along with the
targeted group of individuals, and the identified disciplines within the STEM field, have
generated an array of definitions in STEM education. Zollman (2012 as cited in Brown, 2012)
suggested that educators should “focus more on defining STEM education as a dynamic process
that changes over time, not as a set construct” (p. 7). Zollman (2012 as cited in Brown, 2012)
also emphasized that “the overall goal should be to move from learning for STEM literacy to the
ability to use STEM literacy for continued learning (p. 18),” ( p. 7).
STEM Skill Set
According to Bayer Corporation (2012), STEM identified companies that expect 4-year
and 2-year STEM degree graduates to enter the workforce well equipped with a particular STEM
skill set. Moreover, Bayer Corporation’s (2012) study found that non-identified STEM
companies and industries are increasingly demanding candidates who possess STEM skills to fill
current and future positions. Talent recruiters who were interviewed in the study noted that
today’s candidates are lacking in certain competencies such as leadership, conflict resolution,
complex problem solving, and team building. Most Fortune 1000 companies have internal
trainings and mentorships to address the mismatch in the skill set needed to thoroughly fulfill the
job requirements, but they are hoping to have these skills incorporated into the higher education
curriculum for STEM degrees (Bayer Corporation, 2012, Gonzalez & Kuenzi, 2012).

41

STEM Pipeline
The conceptual metaphor of a leaky pipeline has been widely used to model the pathway
to careers in STEM (National Academy of Sciences, 2007; Clark Blickenstaff, 2005; Cannady et
al., 2014; Metcalf, 2010). The pipeline model is based on supply side economics, and describes
the linear sequence of steps that are necessary to become a scientist or engineer (Metcalf, 2010).
Ever since the leaky pipeline model was introduced, it has repeatedly been referenced to quantify
the flow of students who move from elementary and secondary education to higher education
and STEM occupations (Clark Blickenstaff, 2005; Cannady et al., 2014; Metcalf, 2010).
Additionally, researchers have used this leaky pipeline model to project the future shortages of
highly qualified individuals entering the STEM workforce (Metcalf, 2010). Though, highly
criticized, this pervasive model has persisted for over 40 years, and remains a significant
foundation and framework for developing policies and practices with regard to STEM
persistence (Cannady et al., 2014; Metcalf, 2010). Largely conceptualized as a quantitative and
statistical model, the leaky pipeline has been the basis of recruitment and retention efforts of
minorities and females in STEM for the past 40 years (Metcalf, 2010).
In this section, a review of the salient literature surrounding the conceptual model of the
pipeline in STEM is provided. Specifically, a description of the pipeline model in STEM is
presented using relevant literature, which is followed by a summary of the key transitional
periods depicted in the pipeline model. Subsequently, the educational implication of a leaky
pipeline is examined through the lens of the previous research. Finally, literature is presented
which critically analyzes the shortfalls of the leaky pipeline model in STEM, and alternative
models that have been suggested are discussed in detail.

42

Conceptual Model of the Pipeline of Students in STEM
The leaky pipeline model was first conceptualized and designed by engineers and the
National Research Council’s Committee on the Education and Utilization of the Engineer
(Metcalf, 2010). The pipeline model was introduced to the NSF in the 1970s as a framework for
the movement of students through the educational system by tracking past events and projecting
future needs (Lucena, 2000; Metcalf, 2010). In the 1980s, the pipeline model was used as a basis
to make long-term projections and policy decisions as the US sensed technological competition
from Japan (Lucena, 2000; Metcalf, 2007; Metcalf, 2010). At this point in history, government
involvement in education was more acceptable as government funding was used to bolster the
competitiveness of the US in science and technology (Gonzalez & Kuenzi, 2012; Metcalf, 2010;
Slaughter & Rhoades, 1996). Since the model’s inception, it has been widely referenced to
describe the attrition and persistence of students in STEM (Maltese & Tai, 2011), and it has
served as a model to illustrate that females and minorities are educationally disadvantaged in the
STEM fields (Clark Blickenstaff, 2005).
While the conceptual model has varied slightly with regard to the specific age and grade
of students who enter the pipeline, the overall metaphor is accepted as a logical model for the
number of students who leave the STEM field (Allen-Ramdial & Campbell, 2014; Metcalf,
2010). For example, Snyder, Dillow, and Hoffman (2009) used data from the National Center of
Education Statistics (NCES, 2009) to trace the progression of all 9th grade students as water
flowing through a narrowing pipeline. Similarly, Allen-Ramdial and Campbell (2014) used the
pipeline analogy to describe the movement of pre-college students through advanced
postgraduate levels. Cannady et al. (2014) and Soe and Yakura (2008) suggested the pipeline
begins as early as elementary school and shows the leakage of students through middle school,
43

high school, and beyond (see Figure 3). Though these models have slight nuances, they all stem
from a foundational ideology that has been used to represent the underrepresentation of
minorities and females in STEM careers.

Reprinted with permission.
3

Figure 3. Model of Leaky Pipeline in STEM.

According to the conceptual model of the leaky pipeline, all students enter the pipeline
and flow through the ever-narrowing pipeline whereby they approach milestone junctions that
impact their pathway to a STEM career (Cannady et al., 2014; Snyder et al., 2009). As students
approach a pivotal junction or transitional education period, some students will leak out of the
pipeline, implying at each junction, there is a net loss of students (Clark Blickenstaff, 2005;
Cannady et al., 2014; Soe & Yakura; 2008). This pattern of successive leakage at specific
junctions continues as students progress through the pipeline to a STEM career. Cannady et al.
(2014) summarized this concept by suggesting, “fewer students select careers in STEM than earn
degrees in STEM; fewer students earn degrees in STEM than select majors in STEM; and fewer
students graduate from high school prepared to pursue majors in STEM than enter high school’

3
Reprinted from “What’s Wrong with the Pipeline? Assumptions about Gender and Culture in IT Work,” by L. Soe
and E. K. Yakura, 2008, Women’s Studies, 37, p. 179. Copyright 2008 by Taylor & Francis Group, LLC. Reprinted
with permission.
44

(p. 444). Thus, the implication is, at the end of the pipeline, there are relatively less students
who have persisted in STEM careers compared to the larger number of students who entered the
pipeline (Cannady et al., 2014).
The model was based on the principles of supply-side economics, flow modeling, and
social engineering and was used to depict the linear progression of individuals to a STEM career
(Metcalf, 2010; Soe & Yakura, 2008). During a designated span of time, the model attempts to
quantify the number of students who enter the pipeline, leave the pipeline, and persist to a STEM
occupation. Many US STEM workforce studies that have been conducted over the past four
decades are based on the pipeline model, which has been used to predict workforce shortages
based on the supply of individuals (Metcalf, 2010). Despite being highly criticized for its
supply-side focus and its faulty predictions, the pipeline model has survived for decades and has
become the pervasive model for recruitment and retention of individuals in STEM (Cannady et
al., 2014; Metcalf, 2010; Soe & Yakura, 2008). Moreover, the pipeline model has influenced
researchers to direct their attention to key transitions and populations along the pipeline in an
effort to bolster the supply of STEM individuals (Cannady et al., 2014; Metcalf, 2010; Soe &
Yakura, 2008).
Pivotal Educational Transitions
There is little question that the pipeline to a STEM career is leaky – a term that is used to
explain the net loss of students from STEM disciplines (Allen-Ramdial & Campbell, 2014). The
leaky pipeline model is constructed to illustrate the key transitional junctions or stages that
impact students’ educational progression to a STEM career (see Figure 2) (Soe & Yakura, 2008).
It is at these transitional junctions that some students who entered the initial inlet of the pipeline,
leak from the pipeline, and end their pathway to a STEM career.
45

Researchers have identified that there are certain points along the pipeline that are
especially leaky (Clark Blickenstaff, 2005; Blum, 2006; Cannady et al., 2014; Metcalf, 2010).
These pivotal points along the pipeline include the transitions from middle school to high school,
high school graduation, college to graduate school, and graduate school to STEM occupation
declaration (Clark Blickenstaff, 2005; Maltese & Tai, 2011). Cannady et al. (2014) suggested
that these pipeline junctions were aligned with milestones in a student’s educational STEM
career path such as high school graduation, enrolling in college, majoring in STEM, and earning
a STEM degree. Knowing these milestones are critically associated with attrition in STEM,
researchers have focused their attention on determining who is leaking from the pipeline, where
the leakage is most severe, and how to increase the flow of students at each junction (Cannady et
al., 2014; Metcalf, 2010). However, there has been a considerable amount of debate as to which
milestones are correlated with the greatest amount of leakage.
Berryman’s (1983) landmark study suggested the initial pool of future STEM
professionals begins in elementary school and reaches its maximum size right before the 9th
grade. According to Berryman, during high school some students will enter the pipeline, but
even more will leave the pipeline. After high school, the resulting flow of students is out of the
pipeline, with little to none entering after this point, and the trend persists through graduate
school (Berryman, 1983). Furthermore, Berryman concluded that talent (achievement) and
interest were relevant to students’ persistence in the pipeline, but in different ways for different
subgroups. Berryman’s study was significant for many reasons, but most importantly, it
provided a framework to examine the loss of students from the STEM pipeline, and it led to
subsequent studies on the underrepresentation of subgroups in STEM.
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Elementary school experiences. During elementary school, students’ achievement in
mathematics and sciences is predominantly driven by their interest levels in mathematics and
science (Berryman, 1983; Oakes, 1990). Armstrong (1980) found that in many schools, the
students who achieved the highest grades were the most likely to learn mathematics and science
and to develop interest in these fields. Armstrong suggested that high achieving students were
given more opportunities to participate in accelerated or enrichment programs than low
achieving students.
Middle school transition. Middle school is the first significant transition where students
leak from the pipeline. Opportunities to participate and enroll in mathematics and science
courses in middle school may be influenced by academic achievement in elementary school
(Oakes, 1990). Students who achieved high test scores and had high interest were the students
that enrolled in mathematics courses, which prepared them for high school (Oakes, 1990). For
example, high achieving students were given opportunities to enroll in pre-algebra and algebra
during middle school, while low achieving students who were perceived to have low interest
were relinquished to remedial courses (Oakes, 1990). This is crucial to note because one of the
variables that has been found to distinguish STEM college graduates from their non-STEM peers
was taking algebra by middle school (Cannady et al., 2014; Maltese & Tai, 2011; Nicholls,
Wolfe, Besterfield-Sacre, & Shuman, 2010; Tai, Salder, & Mintzes, 2006). By placing students
with low test scores and low interest in remedial courses, students would be unprepared for the
higher-level thinking skills needed in advanced mathematics and science courses (McKnight,
1987; Oakes, 1985). Also, because they are not exposed to practical skills, it is unlikely they
will develop interest in mathematics and science, thus they are less likely to persist in the
pipeline (Oakes, 1990).
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High school transition. Hilton and Lee (1988) investigated college degree attainment in
STEM and concluded that high school was a period of flux for students as approximately equal
numbers of students lost interest in studying STEM in college as who gained interest in STEM.
While interest was a large indicator of which students persisted in STEM through middle school,
beginning in high school, the pool of future STEM professionals is influenced by achievement
(Berryman, 1983).
Students’ achievement and curricular choices are indicators of potential opportunities
post graduation (Oakes, 1990). Furthermore, Ware and Lee (1988) found that high school grade
point averages (GPAs) were significant predictors for STEM persistence in high school.
Typically, students who maintained higher GPAs would be afforded more opportunities and have
higher perceptions of their prospects of success because of their prior achievements (Oakes,
1990). Furthermore, high achieving students who plan to pursue 4-year college degrees will be
required to enroll in several years of mathematics and science courses, which will introduce
students to advanced concepts and processes in preparation for college (Oakes, 1990). In
contrast, Oakes (1990) suggested that lower-achieving students, who were placed in remedial
courses, may pursue a non-academic or general curricula that includes taking less mathematics
and science courses. Moreover, low-achieving students are less likely to take rigorous
coursework, which impacts their preparation for college-level academics (Tyson et al., 2007).
Adelman (2006) suggested that high school curriculum intensity was a significant factor
for college degree attainment, yet his work was not specific to students in STEM degrees.
However, regression analyses conducted independently by researchers supported Adelman’s
ideas about the importance of curriculum intensity on STEM persistence. Data from their studies
indicated that enrollment and achievement in calculus by the end of high school was a significant
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benchmark that influenced STEM persistence because it predicted college-level preparedness in
students (Cannady et al., 2014; Maltese & Tai, 2011; Nicholls et al., 2010; Tai, Salder, &
Mintzes, 2006). Additionally, Sadler, Sonnert, Hazari, and Thi (2014) found that students who
earned high grades in advanced and rigorous coursework were 1.6 times more likely to pursue
STEM majors as their peers.
George (2006) also reiterated that the transition from middle school to high school was a
threshold point where students, in particular, females, begin to lose interest in science. An
empirical study conducted by Baram-Tsabari and Yarden (2011) demonstrated how during early
childhood, defined as kindergarten to third grade, boys’ and girls’ science interests were the
same. However, by the end of high school, the gap in science interest increased 20-fold, with
young males more interested in physics than young females (Baram-Tsabari & Yarden, 2011).
For females, positive attitudes fostered by positive classroom experiences in mathematics and
sciences were associated with choosing a STEM major (Tai, Sadler, & Maltese, 2007). Sadler,
Sonnert, Hazari, & Tai (2012) discussed as males and females prepare to declare their majors at
post-secondary institutions, young males are three times as likely to choose a STEM major as
young females.
In addition, Maltese and Tai (2011) investigated the variable classroom experiences of
students in mathematics and science and found that the type of learning experiences students had
impacted who entered STEM and who left. Students were more likely to have positive attitudes
towards STEM when their teachers utilized hands-on learning activities, incorporated relevant
topics, used cooperative learning, provided appropriate scaffolding, and employed pedagogical
strategies (Maltese & Tai, 2011; Myers & Fouts, 1992; Piburn & Baker; 1993).
49

College major selection and graduation. Berryman (1983) stated that of the pool of
potential STEM professionals declines after high school. Similarly, Hilton and Lee (1988) found
that the greatest attrition of students in STEM occurred between high school graduation and
undergraduate matriculation. Students’ decisions to pursue college and pursue a major in STEM
are essential to pipeline persistence (Oakes, 1990). Students’ selection of a mathematics or
science major is contingent upon end-of-high-school academic performance and completion of
rigorous coursework in mathematics and science (Oakes, 1990; Tyson et al., 2007; Ware & Lee,
1985 as cited in Oakes, 1990).
The persistence in STEM majors is directly related to high achievement in high school as
indicated by high Scholastic Aptitude Test (SAT) scores, class rank, and high achievement in
college courses (Maltese & Tai; 2011; Oakes, 1990; Strayhorn, 2011). However, Astin and
Astin (1992) conducted a study of 26,000 college students and determined that intention to enter
a STEM major during the freshmen year of college was the strongest predictor of completing a
STEM degree. Similar findings from Bonous-Harnmarth (2000) indicated that declaration of a
STEM major during the first year of undergraduate school was a more salient factor in STEM
persistence than high school GPA or SAT scores.
Graduate school. For those students who graduate with a STEM degree and elect to
pursue graduate study in a STEM field, persistence is affected by admission into a graduate
program and high achievement in college courses (Oakes, 1990). Specifically, high grades in
quantitative courses were a predictor of entrance and persistence in graduate programs
(Berryman, 1983; Oakes, 1990).
These pivotal junctions along the STEM pipeline help researchers understand the
particular points in students’ educational careers that are important for students’ success in
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STEM. Through analysis of these pivotal milestones, three themes emerged regarding the
STEM pipeline. First, students must be afforded opportunities to learn mathematics and science
in order to persist in the pipeline. Second, students’ achievement in mathematics and science
courses, especially during secondary school, indicated students’ preparedness for more rigorous
coursework in college. Finally, students’ attitudes and interests in mathematics and sciences are
factors that are important to their enrollment in the appropriate courses that allow them to persist
through adversity.
However, the utility of these milestones in students’ pathways to STEM careers requires
the following two numeric assumptions about the pipeline metaphor: 1) the proportion of
scientists and engineers who actually flowed through the pipeline as suggested, and 2) the
uniqueness of these factors as being predictors of STEM outcomes (Cannady et al., 2014). This
means that the greater the number of scientists and engineers included in the pipeline, the more
general the criteria must be for differentiating scientists and engineers from the remaining
population (Cannady et al., 2014). Because the pipeline metaphor needs to be so broad, the
model leads to insufficient understanding of the variables for students who are likely to persist in
STEM (Cannady et al., 2014). Cannady et al. (2014) suggested that it might be possible that
some benchmarks, such as graduating from high school, are necessary and prevalent amongst all
STEM professionals, while others are not as essential.
Students Who Leak from the Pipeline
Berryman (1983) traced the progression of students in the STEM educational pipeline
and specifically studied persistence and field choice. Berryman’s study revealed that all
subgroups experience losses throughout the pipeline; however, there are specific subgroups that
experience more losses than others. Moreover, these losses occur at different points along the
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pipeline (Berryman, 1983; Oakes, 1990). Using national data, Berryman examined the times that
losses from the STEM pipeline occurred and disaggregated the data by subgroup. The data
indicated that the loss of women from the STEM pipeline transpired at the end of secondary
school (pre-college years), and during college (Berryman, 1983; Oakes, 1990). Moreover, the
loss of Hispanic and African-American students from STEM was found to happen significantly
earlier in their educational careers (Berryman, 1983; Oakes, 1990).
Implications for STEM Education
The supply side, quantitative pipeline model has been the basis for targeted efforts of
recruiting and retaining females and students of color in STEM for the past 40 years (Clark
Blickenstaff, 2005; Blum, 2006; Metcalf, 2010). Policymakers and researchers alike have
referenced the pipeline to illustrate there will be a shortage of highly qualified individuals in
STEM to maintain a robust STEM workforce (Metcalf, 2010). In fact, the NSF (2007) used data
from pipeline studies to predict there would be a shortfall of 675,000 earned bachelor’s degrees
in science and engineering fields due to the leaky pipeline in STEM (Lucena, 2000; Metcalf,
2010; NSF 2007). In turn, the NSF (2007) claimed that females and minorities would be an
optimal untapped resource to fill-in the ever-growing needs in STEM.
Policymakers underestimate the difficulty of designing effective programs and initiatives
for recruiting and retaining females and minorities in STEM. A leaky pipeline presents overly
simplistic ideals to fix the issue of retention is STEM – find the leaks, and fix the patches
(Metcalf, 2010). Yet, despite the popularity of the STEM pipeline model, data continually show
there are still problems with inequities and underrepresentation in STEM (Clark Blickenstaff,
2005; Blum, 2006; Metcalf, 2010).
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The leaky pipeline has been a common reference point and model for developing broad
initiatives to increase the number of students in STEM. For example, California and Wisconsin
were among the states that tried to require all students to take algebra in 8th grade (Best, 2011;
Liang, Heckman, & Abedi, 2012). The rationale for the movement was based on the STEM
pipeline benchmark that suggested students who took algebra by 8th grade would be more likely
to persist in STEM (Best, 2011; Liang et al., 2012). However, researchers pointed out that there
is very little evidence that forcing all students to participate in a gatekeeper course such as
algebra, when they are unprepared, produces higher numbers of students entering STEM.
Berryman (1983) concluded that any intervention that could be implemented to stop the
flow of students must specifically occur right before high school and continue throughout high
school. In addition, Berryman proposed that strategies to prevent attrition should be
implemented throughout the pipeline because students leak at each point throughout the pipeline.
Berryman’s landmark study has no doubt contributed to the many subsequent studies that
followed which aimed to focus on retention along junctures in the pipeline. For example, a
number of summer bridge programs and pipeline programs in STEM have been created to bridge
the gap between high school and college (Strayhorn, 2011). Regardless of their popularity and
prevalence, there is little empirical evidence to indicate their effectiveness (Strayhorn, 2011).
Policymakers are still faced with the underlying issues that need to be reconciled regarding how
to recruit females and minorities to STEM, and which strategies to implement in order to retain
females and minorities and STEM.
Limitations of the STEM Pipeline Model
Even though the pipeline model has managed to serve as the predominant frame of how
students become a STEM professional for several decades, there are several critiques of the
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model that have emerged (Clark Blickenstaff, 2005; Cannady et al, 2014; Maltese & Tai, 2011;
Metcalf, 2010). First, Cannady et al. (2014) cautioned that the use of a leaky pipeline as a
conceptual model and solution for addressing the persistence of minority and female students in
STEM, may be insufficient to explain these students’ trajectories in STEM careers.
The oversimplification of the pipeline model as a single career trajectory with one inlet,
one outlet, and one direction of flow does not explore students’ variable experiences in STEM
(Cannady et al., 2014; Hammonds & Subramaniam, 2003; Metcalf, 2010; Xie & Shauman,
2003). According the Metcalf (2010) and Soe and Yakura (2008), the linearity of flow is
insufficient to explain students’ pathways in STEM because the model treated all students, even
marginalized populations, equally, resulting in ineffective patches to fix the leaks. Moreover,
Soe and Yakura noted many students entered the pipeline at nontraditional junctures, such as
graduate school, and the pipeline model cannot account for these alternative pathways. Cannady
et al. (2014) elucidated that the use of one-size-fits-all benchmarks such as calculus by 12th
grade are also misleading because the pipeline fails to account for inequities in education and
motivational pathways.
Second, the pipeline model was used to illustrate students who flow through the pipeline
as passive resources (Cannady et al., 2014). Cannady et al. (2014) stated that reducing females
and minorities to passive participants who merely flow through a pipeline, ignores personal
agency and perpetuates the marginalization of females and minorities. Furthermore, researchers
suggested that regarding females and minorities as passive resources ignores their personal
choices, abilities, and motivation that could contribute to their leakage from the pipeline
(Cannady et al., 2014; Metcalf, 2010; Soe & Yakura, 2008).
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Third, the supply-side STEM pipeline model produced flawed data as to the shortfalls of
qualified individuals entering STEM. The pipeline model focused on creating adequate supply
through the recruitment and retention of individuals in STEM at key junctions and transitions
(Metcalf, 2010). However, as Metcalf (2010) noted, the measure of retention becomes a short-
term measure because it is defined as a supply for a given juncture in the pipeline, without much
concern for the demand at the subsequent juncture in the pipeline (Metcalf, 2010). A major
critique with this model is that the supply-side focus does not account for those individuals who
successfully earn a college degree or graduate degree in STEM, only to be unemployed from the
field due to lack of available positions (Metcalf, 2010).
Finally, as a frame to develop initiatives and policy, the pipeline model was severely
inadequate (Cannady et al., 2014). The metaphor of a pipeline has ill-served policy makers
because it suggested patching up the leaks at given junctures is the solution to increasing flow
through the pipeline. Yet, this notion is a very simplistic view that does not consider the
individual differences in the students who pursue STEM (Cannady et al., 2014). Also, it
suggested that all students must flow through a linear pipeline and experience the same set of
academic benchmarks (Cannady et al., 2014). Because the focus is on the homogenization of
students rather than scrutiny of the academic benchmarks, the path elevates the importance of the
benchmarks and narrows the range of acceptable and adequate political responses to fix the
underlying issues in underrepresentation (Cannady et al., 2014). Simplistic policies that indicate
students must develop an early interest in STEM and then take calculus in high school eliminates
a high number of individuals who did not fulfill this attribute yet still managed to become
scientists and engineers (Cannady et al., 2014). Cannady et al. (2014) found that three out of
55

five students who did not possess both of these attributes became scientists or engineers, while
16% have neither attribute.
Alternative conceptual models. Sensing that the linear pipeline model was inadequate
for addressing the attrition of educationally disadvantaged populations, many researchers have
proposed alternative conceptual pipeline models that aim to conceptualize the trajectory of
students in STEM. Allen-Ramdial and Campbell (2014) re-envisioned the STEM pipeline as a
vertical structure where students enter the pipeline at the bottom of the structure and flow
upwards until they enter the STEM workforce. According to this model, the vertical STEM
pipeline is subject to the laws of physics, whereby downward forces such as lack of mentoring,
institutional culture, and poor academic preparation oppose students upward flow (Allen-
Ramdial & Campbell, 2014). This model is suggested to be an improvement from the original
horizontal flow model because it illustrates how students must overcome many built-in
challenges and innate obstacles to become a scientist or engineer.
Cannady et al. (2014) re-envisioned the pipeline as a multiple trajectory pathway
metaphor rather than a singular pipe with only one inlet and outlet. Cannady et al. used a four-
pathway model to a STEM occupation with non-linear paths to better explain the various
trajectories experienced by students in STEM. Similarly, Museus et al. (2011) proposed a model
of a STEM circuit to better explain how students progressed to a STEM career. Museus et al.
suggested that their circuit model serves as an improved framework for guiding future research,
policy, and practice (see Figure 4).

56

Reprinted with permission.
4

Figure 4. Multiple Pathways Model of Leaky Pipeline in STEM.

Soe and Yakura (2008) used a cultural-layers approach to redesign the original linear
pipeline model. Their model incorporated the societal, occupational, and organizational cultural
layers that influence students’ pathways to STEM (Soe & Yakura, 2008) (see Figure 5).

Reprinted with permission.
5

Figure 5. Alternative Model of the Leaky Pipeline in STEM.

4
Reprinted from “Problematizing the STEM Pipeline Metaphor: Is the STEM Pipeline Metaphor Serving Our
Students and the STEM Workforce?,” by M. A. Cannady, E. Greenwald, and K. N. Harris, 2014. Science Education,
98(3), p. 455. Copyright 2014 by Wiley Periodicals. Reprinted with permission.
5
Reprinted from “What’s Wrong with the Pipeline? Assumptions about Gender and Culture in IT Work,” by L. Soe
and E. K. Yakura, 2008, Women’s Studies, 37, p. 184. Copyright 2008 by Taylor & Francis Group, LLC. Reprinted
with permission.
57

Students in STEM Education
In this section, a review of the relevant literature surrounding students in STEM
education is provided beginning with a description of the STEM enrollment trends. Next, a
review of the literature pertaining to predictors of entering a STEM major that includes
curriculum and attitudes being essential predictors of persisting in STEM. Subsequently, the
educational implication of underserved and educationally disadvantaged students in STEM is
examined through the lens of the previous research. Finally, literature is presented which
suggests possible factors in low enrollment of underserved and educationally disadvantaged
students in STEM.
Over the past several decades, it has been prominent that fewer students are entering into
STEM career fields (Bergeron & Gordon, 2015). The total number of bachelor degrees awarded
in the United States has tripled in the last 40 years; however students earning STEM degrees
have only accounted for a third of those bachelor degrees earned (NSF, 2010). STEM majors
accounted for 14% of all undergraduates enrolled in US postsecondary education in the years
2007 – 2008 (Snyder & Dillow, 2011). Chen (2009) found that a total of 56% of postsecondary
students who declared themselves as STEM majors in their freshmen year left the field over the
next six years. There has been evidence linking STEM attrition to such factors as weaker
academic backgrounds, motivation, confidence, and beliefs about one’s capacity to learn STEM
subjects (Burtner, 2005). The demand for graduates in STEM fields continues to grow at a
relatively rapid rate. The education pathway to major in a STEM field begins as early as middle
and secondary school, with the greatest loss of potential STEM majors transitioning between
secondary and postsecondary education (Tyson et al., 2007). STEM focused schools have
increased throughout the United States in the hopes that their availability will increase the
58

percentage of secondary students who enter the higher education pipeline, anticipating a STEM
career and exit the pipeline as STEM professionals (Capraro, Capraro, & Morgan, 2013).
Enrollment Trends
The authors of the Institute of Education Science (IES) found that the percentage of
students entering STEM fields was higher among male students, younger students, students
financially dependent on family, Asian/Pacific Islander students, foreign students, students with
more advantaged family background, and students with stronger academic preparation than their
counterparts (Wang, X., 2013). When considering STEM completion rates in the U.S., data has
shown that White and Asian-American students outperform their African-American, Latino,
Native American, and women counterparts. A report by the Higher Education Research Institute
(as cited in Chang, Sharkness, Hurtado, & Newman, 2014) indicated “that 33% of White and
42% of Asian American students at a national sample of institutions completed their bachelor’s
degree in STEM within 5 years of entering college, compared to only 18% of African American
and 22% Latino students.” (p. 556).
There is a larger disparity between males and females; the U. S. Department of
Commerce’s Economics and Statistics Administration Census report (Langdon, McKittrick,
Beede, Khan, & Doms, 2011) stated that females make up more than half of the college
graduates (54%); however females are earning less than 15% of the collegiate degrees in STEM
programs whereas their male peers are earning 87% of collegiate STEM degrees. Out of the 3.8
million freshmen high school students, only one out of 100 will go on to pursue a STEM degree
(Lauff & Ingels, 2013) (see Figure 6).

59

Reprinted with permission.
6

Figure 6. Earned Bachelor’s Degrees in STEM by Race, Class and Gender

Predictors of Entering a STEM Major
The GAO Report (2014) stated that early preparation during K-12 in STEM emerged as a
factor in students’ decisions to pursue STEM degrees and careers. The UMass Donahue Institute
(UMDI, 2011) indicated that 94% of 8th graders make course-taking decisions related to
preparing themselves for a career or a postsecondary education. Additionally, middle school
students who do not consider a STEM degree or career may not enroll into the necessary high
school coursework to prepare them for STEM education (UMDI, 2011). Interestingly, Maltese
and Tai (2011) analyzed the data from the National Education Longitudinal Study of 1988
(NELS) and indicated that 80% of students who graduated with a STEM degree entered the
pipeline in high school or college, which is contradictory to the pipeline model.
Research completed by Schneider, Marschall, Teske, and Roch (1998) found that the
effects of high school course taking were more of a factor for enrolling into a STEM discipline

6
Reprinted from “Science, Technology, Engineering, and Mathematics (STEM) Pathways: High School Science and
Math Coursework and Postsecondary Degree Attainment,” by W. Tyson, R. Lee, K. M. Borman, and M. A. Hanson,
2007, Journal of Education for Students Placed at Risk, 12(23), p. 259. Copyright 2007 by Lawrence Erlbaum
Associates, Inc./Taylor and Francis Group.
60

rather than background factors such as parental education or income. STEM education and
student success in STEM has been well established and associated with supportive teachers, high
expectations, rigorous curriculum, and student engagement (Aud, Fox, & KewalRamani, 2010;
Bodilly & Beckett, 2005; Kerr, 2005; Krause, Culbertson, Oehrtman, & Carlson, 2008; Lantz,
2009; Marzano, 2003; McComas & McComas, 2009; Morrison, 2006; National Assessment of
Educational Progress, 2011; Toldson, 2008).
Math and science curriculum. A number of studies have explored that the quantity and
level of science and mathematics courses have been an essential part to the educational pathway
to a STEM degree (Csikszentmihalyi & Schneider, 2000; Lee & Frank, 1990; Maltese & Tai,
2011). Students who initially expressed interest in STEM education had the inability to pursue
higher levels of math and science curricula in high school due to the fact that 75% of America’s
youth failed to meet 8th grade standards of mastery in math (U. S. Congress Joint Economic
Committee, 2012). Adelman (1999) found that success in high school mathematics and science
had a correlation with students aspiring to major and persist in a STEM discipline. Supported
later by Anderson and Kim (2006), strong performance in pre-college math and science
significantly correlated with college students persisting in a STEM discipline beyond their first
year. Advanced courses in math and science not only prepared students for the rigorous college-
level STEM courses, but also provided students with the academic confidence to be successful
and persist in STEM (Burkam & Lee, 2003; Horn & Kojaku, 2001). In addition, students taking
higher-level science courses made greater gains in proficiency on science assessments, regardless
of their initial levels. This indicated the academic level of courses mattered more than the
number of classes completed (Madigan, 1997), as well as increased their chances in enrolling
into a postsecondary institution (Schneider, 2002).
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Schneider et al. (1998) identified sequences of science and mathematic courses taken in
high school and categorized the courses into low, intermediate, and high levels of rigor. It was
organized by Burkam and Lee (2003) into a detailed category of eight levels for math, and seven
for science (see Figure 7 and Figure 8), which allowed for a better indicator for future behavior
and achievement in STEM-related coursework. Using previous research, Burkam and Lee
identified advanced courses in mathematics to be trigonometry, analytical geometry, statistics,
pre-calculus, and calculus. Chemistry 2 and physics were identified as advanced courses in the
sciences (Burkam & Lee, 2003).

Reprinted with permission
7

Figure 7. Levels of Corresponding Rigor in Mathematics Courses

7
Reprinted from “Science, Technology, Engineering, and Mathematics (STEM) Pathways: High School Science and
Math Coursework and Postsecondary Degree Attainment,” by W. Tyson, R. Lee, K. M. Borman, and M. A. Hason,
2007, Journal of Education for Students Placed at Risk, 12(23), p. 253. Copyright 2007 by Lawrence Erlbaum
Associates, Inc./Taylor and Francis Group.
62

Reprinted with permission
8

Figure 8. Levels of Corresponding Rigor in Science Courses

Burkam and Lee (2003) concluded only a small percentage of students completed
advanced levels of mathematics and sciences; students who progressed further into the higher
levels for mathematics courses took those courses based on personal interest and majored in a
STEM discipline; students who took physics had the largest increase in science proficiency.
Since 1990, the trend in US high school students taking advanced mathematics and science
courses has increased (Lauff & Ingels, 2013). Specifically, the percentage of high school
students who completed calculus doubled (7% to 16%) between the years of 1990 – 2009, and
25% more students completed algebra II and trigonometry (Lauff & Ingels, 2013). Moreover
approximately 20% more high school students had taken science courses in chemistry and
physics (Lauff & Ingels, 2013). Trusty (2002) concluded that there was a positive correlation
between high school coursework and selection of a STEM major; specifically, high school
females who enrolled in advanced mathematics and males who enrolled in physics were more
likely to choose a major in STEM. Although Tyson et al. (2007) found that females completed

8
Reprinted from “Science, Technology, Engineering, and Mathematics (STEM) Pathways: High School Science and
Math Coursework and Postsecondary Degree Attainment,” by W. Tyson, R. Lee, K. M. Borman, and M. A. Hanson,
2007, Journal of Education for Students Placed at Risk, 12(23), p. 254. Copyright 2007 by Lawrence Erlbaum
Associates, Inc./Taylor and Francis Group.
63

more advanced coursework than males, they were less likely to complete the highest level of
math and science than males. Moreover, significantly fewer Latinos and African Americans
completed advanced math and science coursework when compared to their White and Asian
counterparts (Tyson et al., 2007).
Attitudes and aspirations in STEM. A data report by the NSF (2004) indicated gender
differences in students’ interests in math and science and self-perceptions of their abilities among
4th, 8th, and 12th graders. At each grade level, females were less likely than males to say they
liked mathematics and science and had the self-perception of not being good at those subjects.
For the majority of the students across racial/ethnic groups, interests and self-concepts in math
and science were lower in 12th graders compared to 4th and 8th graders, with the exception of
Asians, who liked mathematics and science more in high school (NSF, 2004). The NSF (2004)
added that mathematics and science scaled scores between those females and males were similar
at the elementary, middle, and high school, which suggested that females may demonstrate equal
achievement, but their self-perceptions play a significant factor in their decision to persist in
STEM.
Even when students succeed academically, literature suggested that success in STEM
requires deep content knowledge with STEM self-confidence (Hartman & Hartman, 2008). Self-
confidence was shown in multiple studies as a common theme in persisting in STEM (Soldner,
Rowan-Kenyon, Inkelas, Garvey, & Robbins, 2012). Building STEM self-confidence involved
mentoring, real-life experiences, and collaboration in coursework (McInnes, James, &
McNaught, 1995; Sonnert, Fox, & Adkins, 2007; Tinto, 1997). Understanding attitudes in
mathematics and science has been a focus in STEM education due to the degree of influence in
STEM persistence, particularly stressing the importance of positive attitudes toward their fields
64

of study (Myers & Fouts, 1992; Seymour & Hewitt, 1997; Weinburgh, 1995). Students with
positive self-concepts and high levels of self-efficacy to learn mathematics and science were
most likely to choose a STEM degree (Huang, Taddese, & Walter, 2000; Leslie, McClure, &
Oaxaca, 1998).
Underserved and Educationally Disadvantaged Students in STEM
As the US strives to maintain global economic competitiveness, there is a pressing need
to encourage, support, and increase underserved and educationally disadvantaged minorities in
pursuing STEM field careers. Underserved and educationally disadvantaged students in STEM
fields can assist the US in remaining competitive in an increasingly diverse economy (Ward &
Wolf-Wendel, 2011). Multiple studies have found that women, educationally disadvantaged
minorities, first-generation students, and low-income backgrounds leave the STEM fields at a
higher rate than their counterparts (Lauff & Ingels, 2013). The President’s Council of Advisors
on Science and Technology (PCAST, 2010) presented a wide range of recommendations and
identified the most critical priorities for rapid action. The recommendations included the
following: preparation of all students while maintaining a focus on females and minorities who
are educationally disadvantaged in the STEM fields, proficiency of all students in STEM, and
motivation and encouragement of all students to learn STEM and pursue STEM careers (PCAST,
2010).
Research indicated there are differences in the persistence of students in STEM based on
gender and ethnicity. In 2009, females completed 72% of the degrees in life science, whereas
males completed significantly more degrees in physical sciences, geosciences, mathematics,
computer science, and engineering (NSF, 2010). White and Asian students earned the majority
of STEM degrees compared to their counterparts. Women and minorities are less likely to
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persist in a STEM field major during college than male and non-minority students (National
Science Board, 2007). Females and Latinos are underserved and educationally disadvantaged
not only in STEM careers, but also in STEM courses (Halpern et al., 2007).
Possible Factors in Low Enrollment of Females and Minorities in STEM
Burkam and Lee (2003) suggested that males and females have the capacity to compete at
the same level in mathematics and science, but when they enroll in more advanced courses,
females do not persist at the same rates. Past research has attributed the low enrollment of
females and minorities in STEM to a number of factors: (1) a lack of students’ understanding of
the career opportunities available to them, (2) a misunderstanding of what STEM education is,
(3) a lack of mentoring opportunities, especially for females, (4) a low number of females and
minorities teaching advanced mathematics and science courses, with the exception of Asians,
(5) the perception of their ability to succeed in mathematics and science, and (6) personal interest
and self-efficacy in excelling at mathematics and science (NSF, 2007; Rinn, McQueen, Clark, &
Rumsey, 2008).
Females. Females may elect to engage in higher-level coursework in mathematics and
science in high school, but are less likely to pursue STEM degrees and careers than their male
peers due to lack of interest in mathematics and science, and lack of self-identity in STEM
(Tyson et al., 2007). Interest related to STEM is developed during elementary education and
reinforced both negatively and positively throughout experiences in secondary and
postsecondary education. Females are discouraged from pursuing STEM disciplines due to the
competitive nature of the courses and the perceived male-dominant culture in STEM (Riegle-
Crumb et al., 2012). Hewlett, Luce, and Servon (2008) examined the responses from 2,493
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workers in science fields and concluded 52% of those who enter the STEM field eventually leave
due to the perceived masculine culture.
Oakes (1990) suggested that as early as elementary school, females experience gender-
related differences in mathematics and science. For example, males are more likely than females
to be placed in the high-ability mathematics groups (Oakes, 1990). Additionally, research into
educational practices in the science classroom demonstrated teachers interact more often and in
more detail with boys than girls, resulting in young men being twice as likely to participate in
course discussions as young women (Sadker & Sadker, 1994; Tindall & Hamil, 2004).
Tindall and Hamil (2004) described societal factors such as gender stereotypes and
familial obligations as explanations for the lack of female interest in STEM fields. Traditional
gender roles, which are imposed upon boys and girls from a very young age, can foster or
dissuade a child’s interest in science. While girls are encouraged to draw and sew, activities
which develop verbal and fine motor skills, boys are encouraged to build models and play sports,
activities which promote spatial visualization and mathematics aptitude (Tindall & Hamil, 2004).
Due to this discrepancy in child-rearing practices, Tindall and Hamil (2004) concluded girls do
not have the same opportunity to develop basic mathematics and science skills, and are,
therefore, less likely to pursue them in secondary and postsecondary education
Motivational elements that heavily influence persistence and choices for females in
STEM include their self-identity and self-concept in STEM. Females have difficulty viewing
themselves as scientists and have difficulty reconciling and achieving a work-life balance (Xu &
Martin, 2011). Previous literature showed that role models, specifically faculty role models, may
influence female students’ persistence in STEM (Griffith, 2010). While the data are
inconclusive regarding same gender mentors, the relationship between faculty and student is
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influential in females’ persistence in STEM at the college level. These findings indicated that
females, even when they have the academic capacity to excel in STEM courses, opt out of these
disciplines due to negative attitudes related to STEM (Tyson et al., 2007).
Minorities. Latino and African-American students begin their exit out of the STEM
pipeline as early as elementary school due to lower achievement in mathematics courses
(Berryman, 1983; Oakes, 1990). Researchers found that White and Asian children were
identified in elementary school to exhibit higher achievement in mathematics and science than
non-Asian minorities despite reporting equal enthusiasm and positive attitudes about
mathematics and science (Carpenter, Hiebert, & Moser, 1983; Dossey, Mullis, Lindquist, &
Chambers, 1988; Oakes, 1990). Subsequently, as Latino and African-American students
progress through middle school and high school, the gap in achievement in mathematics and
science continues to widen and the number of students who exit the STEM pipeline grows
(Oakes, 1990).
Researchers investigated the reasons why minorities were less likely to persist through
the STEM pipeline and found that minorities were less academically prepared than their White
and Asian peers for college coursework. Studies conducted by Klopfenstein (2004) and Mayer
and Tucker (2010) suggested that racial and ethnic minorities, first-generation students, and low
income students are disproportionately placed in remedial classes and special education courses
in high numbers, regardless of comparable test achievement to their White peers (Klopfenstein,
2004; Mayer & Tucker, 2010). Additional data suggested that minorities are more likely to
attend high schools with fewer resources, less qualified teachers (McDonough & Fann, 2007;
Strayhorn, 2011), lower academic expectations (Mayer & Tucker, 2010; Werkema & Case,
2005), and insufficient opportunities to participate in honors and advanced placement (AP)
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courses (Zarate & Pachon, 2006). As a result of these challenges, minorities are likely to
underperform on college entrance exams, express feelings of low confidence in their abilities to
earn college degrees, and engage in remedial courses in college (Strayhorn, 2011).
Furthermore, Ogbu and Simons (1998) suggested that minorities face additional cultural
and community forces that exacerbate their underachievement and inadequate preparation to
pursue STEM as compared to their White and Asian peers. First, minority students are more
likely to be pressured to work and they may have the added burden of family responsibilities that
deter them from taking more rigorous courses in high school even when such courses are offered
(Klopfenstein, 2004). Second, minorities are faced with language barriers, that adversely lead to
limited access to high paying jobs, and result in living in poverty and attending schools with
inadequate resources (Tienda & Haskins, 2011; Yun & Moreno, 2006). Third, parents of
minority students, specifically involuntary minorities, lack the social capital to advocate for their
students to be in higher-level courses, which are gateway courses to STEM majors (Ogbu &
Simons, 1998). Finally, minorities are not provided with an adequate number of relevant role
models and supportive peer groups to stress the importance and value of a STEM career
(Klopfenstein, 2004). These findings suggest that the lack of adequate preparation and
institutional barriers in access during high school present significant barriers for minorities who
seek to pursue STEM.
Tyson et al. (2007) suggested that for those minorities who are able to navigate the
system and take rigorous courses in high school, data indicated they are equally likely to pursue
STEM majors in college as their White peers. For example, Allen-Ramdial and Campbell (2014)
stated that between 2000 and 2010, 34.8% of underrepresented minorities (URM) and 37.6%
non-URM college students declared STEM majors during their first year of college. However,
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the total number of URMs enrolled as undergraduates was 24.1% as compared to the 75.9% of
non-URM undergraduates enrolled (Allen-Ramdial & Campbell, 2014). These data are
misleading because they indicated there were comparable percentages of students from both
populations declaring STEM majors, yet the overall number of URMs enrolled in college is
significantly less than non-URMS. Thus, the potential pool of STEM graduates is much smaller
for the URM subgroup.
Outreach Programs
Educationally disadvantaged students deal with a significant number of barriers toward
higher education, such as lack of access to information and resource networks, lack of peer
support for academic achievement, segregation, ineffective counseling, low expectations, and
aspirations (Gándara & Bial, 2001). According to Adelman (1999), educationally disadvantaged
students are overrepresented in schools that are underfunded and lack resources; as a result, the
schools are less likely to offer challenging curriculum, including rigorous math courses, which is
one of the most important predictors to succeed in STEM. Not only has the educational system
failed to prepare educationally disadvantaged students academically, the system has also failed to
address the social and psychological barriers (Gándara & Bial, 2001). As a result, institutions of
higher education have invested a substantial amount of time to develop outreach programs for
educationally disadvantaged students with the opportunity to be college and career ready
(Villalpando & Solórzano, 2005). Outreach programs serve to compensate for the inadequacies
that the education system has placed and aim to find ways to promote and maintain students’
interests and achievement in academic and social success (Armstrong, 1980; Berryman, 1983;
Cannady et al., 2014; Swail & Perna, 2001; Oaks, 1990). Research indicates that educationally
disadvantaged students significantly benefit from attending an outreach program, especially
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improving their access towards college (Gándara & Bial, 2001; Macy, 2000; Vargas, 2004). In
fact, moderate- to high-risk students doubled the odds of enrolling into a postsecondary
education when attending an outreach program in high school (Horn & Chen, 1998).
The National Survey of Outreach Programs (NSOP) estimated that two million students
are enrolled in outreach programs across the United States each year (Swail & Perna, 2001).
According to NSOP (Swail & Perna, 2001), two-thirds of the programs offer services to students
K-9 and one-third focusing on the later years of high school, targeting low-income, first-
generation, and minority students. Figure 9 shows the frequency of outreach program goals with
the highest goals of promoting college attendance, college awareness, and college exposure
(Swail, Quinn, Landis, & Fung, 2012).

Reprinted from 2012 Handbook of Pre-College Outreach Programs, by S. Swail, K. Quinn, K. Landis, & M. Fung,
2012.

Figure 9. Top Program Goals Selected by Survey Respondents
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Although services provided by outreach programs may vary, mostly all programs that reported to
the NSOP (Swail et al., 2012) included services that prepare students for the academic and social
life experiences of college (see Figure 10 and Figure 11).

Reprinted from 2012 Handbook of Pre-College Outreach Programs, by S. Swail, K. Quinn, K. Landis, & M. Fung,
2012,

Figure 10. Percentage of Programs that Offer Academic Services, by Service Type

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Reprinted from 2012 Handbook of Pre-College Outreach Programs, by S. Swail, K. Quinn, K. Landis, & M. Fung,
2012,

Figure 11. Percentage of Programs that Offer Non-Academic Services, by Service Type

Key Features of Effective Programs
Schultz and Mueller’s (2006) report complied key features of effective programs based
on previous research, literature reviews, program evaluations, and commonalities found in
programs with the best evidence for effectiveness.
a. Prepare students academically. Effective outreach programs help prepare students
academically by providing academic counseling, enrichment, remediation, study skills,
and allowing for personalized learning environments (Gándara & Bial, 2001).
b. Balance academic support with social support. Strong social networks support students’
academic and emotional development, influencing each other to enroll in college
(Cabrera & La Nasa, 2001).
c. Intervene early. Programs with the strongest evidence for effectiveness begin serving
students prior to high school (Schultz & Mueller, 2006).
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d. Involve and encourage parents/family. Parents who are knowledgeable about college
allow them to know how to support their child’s education and are more likely to attend
college (Corwin, Colyar, & Tierney, 2005; Perna, 2002).
e. Help students navigate the college admissions process. Helping students complete
college admissions and prepare for entrance exams are important initial predictors of
enrolling in college (Horn & Chen, 1998).
f. Provide comprehensive, long-term support. Programs that are comprehensive and offer
support for at least four years showed a strong correlation on student success and college
enrollment (Cabrera & La Nasa, 2001; Swail et al., 2012).
g. Encourage systemic reform. Programs that partnered between secondary schools and
postsecondary institutions ensured that students completed graduation and college
entrance requirements (Martinez & Klopott, 2005).
h. Provide financial assistance. Programs that provide students with information and assist
students in applying for financial aid positively associated with college enrollment
(St. John et al., 2004). Students who receive financial aid persist in college more than
those who do not receive aid (Hu & St. John, 2001).
Out of the thousands of available outreach programs nation-wide, only 13 programs had
acceptable levels of evidence for effectiveness (Gándara & Bial, 2001). Swail and Perna (2001)
stated that evaluating the effectiveness of outreach programs is challenging due to the
availability of empirical data, along with appropriate use and reporting of data for many
programs.

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MESA Program
The Mathematics Engineering Science Achievement (MESA) program is one of the core
members of the University of Southern California (USC) Community Educational Academy
(CEA, Hong, 2009). The MESA program was founded in 1970 with the mission to promote
persistence for educationally disadvantaged populations in STEM, beginning in elementary
through university (MESA, 2016). The MESA program was chosen for 35 years of motivating
and preparing students for STEM majors in the greater Los Angeles area (MESA, 2016).
Moreover, MESA reported that 53% of MESA pre-college students go to college in STEM
majors and 97% of MESA community college students transfer to four-year institutions in
STEM majors (MESA, 2016). According to MESA’s mission, students who participate in the
MESA program succeed for the following reasons (MESA, 2016):
• Academic support based on high standards
• Individual counseling to ensure that college prerequisites and transfer/college graduation
requirements are met
• Industry involvement in activities and strategic planning
• Reinforcement of California math and science standards through hands-on projects and
collaborative learning
• Supportive student communities based on academic success
• Professional development for math and science teachers in low-performing schools
• Networks of parents, educators, industry leaders, and community resources to support
students

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Summary
The purpose of this chapter was to provide an overview of literature that examined the
historical perspective of STEM education in the United States, the pipeline that leaks
educationally disadvantaged minorities and females at key transitional points, barriers that deter
educationally disadvantaged minorities and females in persistence in STEM, and lastly outreach
programs that support and provide opportunities for educationally disadvantaged minorities and
females for 21st century college and career readiness.
The literature review revealed in order to remain competitive in the STEM workforce the
United States needs to strengthen the number of students who enter STEM fields. As a result,
several federal initiatives including the National Science Foundation Act of 1950, NDEA Act,
NCLB, ESSA Act, America COMPETES Act, and Obama’s STEM 5 Year Strategic Plan have
increased the accountability measures for mathematics and science achievement in public
schools. These federal initiatives have also sought to address the underrepresentation of
minorities and females in STEM as typically indicated by a leaky pipeline model. According to
previous literature, minorities and females are more likely than their peers to exit the STEM
pipeline prior to obtaining STEM careers because they are inadequately prepared for the rigors of
college coursework, are provided with less opportunities to engage in mathematics and science
courses, and report lower levels of interest in mathematics and science courses.
Moreover, educationally disadvantaged students deal with additional barriers such as lack
of access to information and resource networks, lack of familial support, ineffective counseling,
and low expectations, which hinder their persistence in STEM. Many higher education
institutions have invested substantial amounts of funding for outreach programs to level the
playing field and close the inequities in STEM. One such outreach program that has
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demonstrated success for educationally disadvantaged populations in STEM is the MESA
Program in California. The MESA Program provides students with academic and social support,
community partnerships, college counseling, and research opportunities outside of the classroom.
For this reason, the MESA Program was investigated for its effectiveness in retaining
educationally disadvantaged populations in STEM. In Chapter Three, the research design,
participant selection, study site, data collection approach, and data analysis techniques are
discussed in detail to further investigate how the MESA Program operates and its effectiveness
for promoting student retention in STEM.

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CHAPTER THREE: METHODOLOGY

The purpose of this chapter is to discuss the research design and methodology of this
study. The first part of this study restates the problem, purpose, and research questions from
Chapter One. Next, the methodological design, participants and setting, data collection protocol,
data analysis, and ethical considerations are described. Finally, this chapter summarizes and
introduces Chapters Four and Five.
Restatement of Problem, Purpose, and Research Questions

The literature has revealed that while US was once the frontrunner in science and
technology, as a result of globalization, competition from growing nations is threatening the
U.S.’s position as a global leader. The National Academy of Sciences (2007) suggested that the
scientific and technical building blocks of the U.S.’s economic leadership are collapsing at a time
when other nations are garnering strength. The gradual decline of the U.S.’s economic
prosperity has been attributed to the declining numbers of highly qualified individuals entering
the science, technology, engineering and mathematics (STEM) training fields and the STEM
workforce. In order to compete with nations such as Finland, China, and India, whose
economies are growing, the US must optimize its knowledge, leverage its resources, and refocus
its attention to bolstering the STEM pipeline from primary through postsecondary education
(National Academy of Sciences, 2007).
Previous research indicated that strengthening the pipeline in STEM would require that
appropriate interventions target the retention of educationally disadvantaged students in STEM
fields beginning as early as primary school. However, because educationally disadvantaged
students are highly vulnerable to leaking from the pipeline, a concerted effort must be made to
track the progression of these students through the pipeline (Cannady et al., 2014; Griffith,
2010). Berryman (1983) suggested that subsequent age and gender specific interventions must
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continue to occur at each pivotal junction within the pipeline to maximize the retention of
educationally disadvantaged students in STEM fields.
Researchers urged that middle school is a pivotal time when students are most influential
in moving forward in the STEM field (Mohr-Schroeder et al., 2014). STEM magnet middle
schools and extracurricular enrichment programs have been established to address the
underrepresentation of minorities in the STEM field. However, there is still a huge deficit in the
amount of support programs needed to prepare America’s populations to meet the industry’s
demands (Goldsmith, Tran, & Tran, 2014).
It is imperative to further investigate how the MESA program is providing access to
support educationally disadvantaged in order to increase their representation in science and math
activities in middle school, science and math college preparatory courses in high school, STEM
majors in higher education, and STEM jobs post graduation. The gap in the number of White
males and educationally disadvantaged minorities who persist in a STEM field continues to
widen at each junction within the pipeline from middle school to high school, and career
selection (Thoman et al., 2014). This suggests that there are additional factors, when controlling
for academic preparation, that are inhibiting educationally disadvantaged minorities from
persisting in STEM majors. Such factors are hypothesized to include motivational factors such
as self-efficacy, negative gender and racial stereotypes, and poor self-identity due to lack of role
models.
Mathematics, Engineering, Science Achievement (MESA) has received a great deal of
recognition for their effort in recruiting and retaining educationally disadvantaged populations in
STEM. MESA provides academic, social, networking, and motivational supports to retain
students in STEM fields beginning in elementary school and continuing on through higher
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education. At the postsecondary level, MESA offers the following two programs: MESA
Community College Program at two-year colleges, and MESA Engineering Program at four-year
colleges and universities. As such, current educationally disadvantaged students in higher
education may have participated in MESA at previous pivotal junctures throughout their
educational careers, and may still be participating in MESA at the postsecondary level. The
primary purpose of this study was to discover and identify how effective MESA is in the
persistence of educationally disadvantaged students in STEM activities, electives, and courses.
A second goal of the study sought to evaluate the components of the MESA Program that have
been widely publicized as increasing educationally disadvantaged students to persist in STEM.
Research Questions
Research questions are essential for the researcher to design an effective methodology,
and they help the researcher articulate what he/she would like to answer from the study
(Maxwell, 2013). For this study, it was necessary to understand how MESA outreach programs
at middle schools were providing support to educationally disadvantaged students. Moreover,
additional components of the research study investigated the impact that MESA had on middle
school educationally disadvantaged students’ continued interest in STEM related content, and the
required resources needed to promote persistence in taking stem courses and activities in middle
and high school. Finally, it is essential to evaluate the effectiveness of MESA middle school
programs in increasing educationally disadvantaged students’ persistence toward participating in
STEM courses and activities in middle school and high school. As such, the following research
questions will serve as the framework that will guide this research study:
1. How is the Mathematics, Engineering, Science, and Achievement (MESA) outreach
program preparing teachers to support educationally disadvantaged middle school
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students in Science, Technology, Engineering, and Mathematics (STEM) activities and
courses?
2. How do MESA teachers perceive the impact of the MESA program in the retention of
educationally disadvantaged students in STEM activities and courses?
3. What resources are utilized in the MESA program to prepare and support educationally
disadvantaged middle school students in STEM activities and courses?
4. How do teachers perceive the effectiveness of the MESA program in increasing the
persistence of educationally disadvantaged students in STEM activities and courses?
The aforementioned questions were important to address because they served to qualify,
measure, and evaluate the impact that MESA had on the persistence of educationally
disadvantaged students in STEM courses and activities.
An Introduction to MESA
The research study was conducted on the effectiveness of MESA for retaining
educationally disadvantaged students in STEM careers. MESA was founded in 1970 to promote
the retention and graduation of educationally disadvantaged students in mathematics-based
academic degree programs (Hong, 2009). The MESA program is dedicated to ensuring that
educationally disadvantaged students are provided the necessary resources to enter a four-year
institution or transfer to a four-year institution and persist with STEM. MESA provides
individual academic support, study skills training, hands-on competitions, career and college
exploration, parent leadership development, teacher training opportunities, field trips and
workshops. Due to the unique combination of enrichment activities MESA has been nationally
recognized for being innovative and having an effective academic development program for
STEM (MESA, n.d.). In 2004, MESA served as a model for the Hewlett-Packard Diversity in
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Engineering Program, preparing more educationally disadvantaged students at community
colleges and successfully transferring to a four-year institute as engineering and computer
science majors (Hewlett-Packard Philanthropy & Education Annual Report, 2005). In 2006,
“MESA was named by Bayer Corporation as one of 21 exemplary programs to help K-12
students, especially educationally disadvantaged and girls to participate and succeed in STEM
fields” (Bayer Corporation, 2006 as cited in Wikipedia, 2017, para. 4); and, “The Silicon Valley
Education Foundation named MESA its 2013 STEM Innovation awardee in math” (Wikipedia,
2017, para. 4). MESA has received awards from both the White House and the Ford Foundation,
has been replicated in 11 states, and is the basis for many other programs (MESA, n.d.).
In 2011-2012, MESA served a total of 28,192 students within the state of California. The
largest MESA program serving the pre-college K-12 institutions, followed by community college
and the universities (USC Viterbi School of Engineering, n.d.). Among the 20,299 students
serviced in the pre-college K-12 program, 53% of those students entered college declaring a
STEM major, and of the 4,707 students who represented the MESA Community College
program, 97% of the students transferred to a four-year institution (USC Viterbi School of
Engineering, n.d.).
History
In the late 1960s, educators from California launched a study to determine why few
African Americans, Latinos, and American Indians were enrolling into the Engineering
Department at University of California Berkeley (MESA, n.d.). As a result, educators developed
a solution based on a pre-college intervention program, and began the MESA program at
Oakland Technical High School in 1970. The intended goal was to develop academic and
leadership skills, and build confidence for historically educationally disadvantaged students in
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engineering, physical science, and math-based fields (MESA, n.d.). Over the years other states
such as Arizona, Colorado, Hawaii, Illinois, Maryland, New Mexico, Oregon, Pennsylvania,
Utah, and Washington have partnered with MESA to become a National program. California
MESA serves students in pre-college (K-12) through the MESA schools program, community
college through the MESA community college program, and four-year college level students in
the MESA engineering program (MESA, n.d.).
The MESA program operates based on a partnership with local industries, higher
education as well as K-12 institutions. MESA is funded by the State of California, and
administered by the University of California and the California Community College Chancellor’s
Office. MESA services students who are the first in their families to attend college. Most are
low-income and attend low-performing schools with limited access to resources.
USC-MESA Program Description
USC-MESA program is housed under the USC Viterbi School of Engineering department
and provides a pipeline of academic services from middle school through the University level.
USC-MESA currently serves 12 middle schools and 15 high schools to improve achievement
and increase the number of students who graduate with a STEM degree in the greater Los
Angeles region. The school districts that are supported by USC-MESA are Alhambra Unified
School District (AUSD), Culver City Unified School District (CCUSD), Hawthorne Unified
School District (HUSD), Inglewood Unified School District (IUSD), Los Angeles Unified
School District (LAUSD), and two charter school programs. Student participation is based upon
their personal interest and potential in math and science. MESA advisors cultivate their interest
and potential by facilitating workshops and clubs, organizing competitions and incorporating
high-interest activities during the MESA period.
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Middle school USC-MESA students begin the process by developing important study
skills, meeting STEM career professionals, hands-on experiments, field trips to high schools and
colleges. High school USC-MESA students receive a full range of services to be prepared and
eligible to the university or college of their choice and major in a STEM-based field. High
school MESA students receive academic support, career exploration opportunities, hands-on
math and science competitions, leadership training, college counseling and participate in pre-
college day.
Quantitative, Qualitative, and Mixed-Methods Study
This study employed a two-phase explanatory sequential mixed-methods design as shown
in Figure 12 (Creswell, 2009). The first phase of the mixed methods design entailed the
collection of quantitative data through survey administration, analyzing the results, and using the
results to plan and inform the second phase (Creswell, 2009). The second phase of the
methodology utilized the quantitative data analysis and results to purposefully design a
qualitative research study to meaningfully answer the research questions (Creswell, 2009). The
overall intent of an explanatory sequential mixed-methods design was to have the qualitative
data help explain, in detail, the initial quantitative results, and develop a better understanding of
changes needed for a marginalized group through a combination of both types of data (Creswell,
2009). Figure 12 illustrates the sequence of phases associated with the research design.

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Figure 12. Explanatory Sequential Mixed-Methods Approach

Quantitative Approach
The quantitative research method is a deductive approach that examines a relationship
between and among variables, which is central to answering questions and hypotheses through
surveys and experiments (Creswell, 2009). As part of the researcher’s quantitative approach, an
electronic survey was administered through SurveyMonkey™ to female undergraduate and
graduate students who are pursuing STEM, and recent female graduates from STEM disciplines.
In both cases, females who were selected to partake in this study had previously participated in
one of the MESA programs at the middle school, high school, or higher education level. The
survey design provided objective numeric description of trends, attitudes, and opinions of a
sample population (Creswell, 2009). From the survey results, the researcher then generalized
and drew inferences about the population sample (Creswell, 2009).
For the study, a quantitative approach was appropriate to include for the following
reasons. First, the researcher sought to determine the association and relationship between two
variables. Specifically, the researcher investigated whether a there was a correlation between
participation in the MESA outreach programs and college females’ persistence in STEM majors.
Second, the baseline data collected from the surveys was used to purposefully select participants
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for the qualitative methodology, and develop a line of questioning that would appropriately
expand on the survey responses. Finally, the quantitative approach was appropriate because the
sample size is larger and sample data can be extrapolated to represent the given population of
study (Creswell, 2009).
Qualitative Approach
Qualitative research is distinguished from quantitative research because it is an inductive
process that includes gathering data, analyzing data, and making interpretations from the data
(Merriam, 2009). Qualitative research focuses on uncovering the meaning of a phenomena
rather than making predictions and examining cause and effect relationships (Merriam, 2009). A
researcher may elect to use qualitative methods when he/she is interested in understanding how
individuals interpret and construct meaning from their experiences (Merriam, 2009).
Furthermore, qualitative research is effective when the objective of research is to gain rich,
descriptive data.
The use of a qualitative research approach was appropriate for this study because the
researcher was interested in gaining meaningful data of the experiences of MESA advisors and
teachers who support educationally disadvantaged students to persist in STEM. The qualitative
portion of the study sought to explore how MESA advisors and teachers perceived the MESA
program’s effectiveness in educationally disadvantaged students’ persistence in STEM courses,
electives, and activities. Understanding the experiences of MESA advisors and teachers
provided genuine insight to which components of the program directly affected the students’
persistence in STEM. Advisors and teachers were able to detect the small nuances that enhanced
effectiveness because of their daily interactions with educationally disadvantaged students and
being immersed in the school’s routine.
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In qualitative research, interviews are essential because they provide information that
cannot be obtained through direct observations such as feelings, thoughts, and actions that
occurred in the past (Patton, 2002). Furthermore, a researcher cannot observe how another
person constructs meaning from an experience; a researcher would have to ask about that
(Merriam, 2009). Thus, the qualitative design included conducting interviews with MESA
advisors and teachers who support educationally disadvantaged students. A review of the
literature surrounding the topic of persistence in STEM revealed that while academic support
programs are increasing, much of the research reveals the impact of outreach programs on
college access and persistence and excludes which program features contribute the most to the
program’s success (Schultz & Mueller, 2006).
Population and Sample
Participant Selection
Units of analysis. According to Patton (2002), a particular population may be selected as
a unit of analysis based upon characteristics the population has which are important for
understanding the phenomenon studied. The units of analysis for this study included advisors
and teachers who currently worked at school sites overseen by the USC-MESA program. The
rationale for selecting advisors and teachers was based on their daily interactions with
educationally disadvantaged students participating in the MESA program at some capacity and
the public school system routine.
Recruitment of participants. The first step in recruiting the intended sample population
was to create meaningful relationships with gatekeepers who could facilitate connections with
potential survey participants and interviewees. For this reason, the MESA Program Office at the
University of Southern California was approached about a collaborative study that could be
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mutually beneficial regarding the information about the effectiveness of MESA for retaining
educationally disadvantaged students in STEM.
An initial meeting with the director of MESA, associate director of MESA, and the
research study group was held in February 2016 to determine if the research study could be
feasibly conducted and whether the data produced could be informative for the MESA program.
At this time, potential recruiting techniques, intended study population, and methodologies were
discussed and refined. Feedback regarding the survey instrument was discussed in order to
establish validity of the tool. Also, a follow-up meeting was held in May 2016 once the study
was approved by the Institutional Review Board (IRB).
At the follow-up meeting, the finalized survey instrument was reviewed and approved by
the director and associate director of MESA. It was determined during the May 2016 meeting
that the researchers would attend an in-person Virtual MESA Academy for Science and
Mathematics Educator (vMASME) event held on the campus of the USC on August 6, 2016.
The purpose of this conference was to encourage the sharing of mathematics and science
strategies amongst regional MESA teachers and MESA program directors at the middle school
level through postsecondary education. The vMASME was a whole day event whereby MESA
teachers and directors participate in professional development and foster collaborative learning
techniques to improve the effectiveness of MESA.
The vMASME event served as the initial point of contact to facilitate distribution of the
electronic survey to MESA advisors and teachers. Current MESA middle school and high
school teachers from the greater Los Angeles region were asked at vMASME to complete the
teacher survey during their lunch break. MESA teachers were informed that participation in the
survey was voluntary and confidential, and that their responses would be used for the purposes of
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the research study. Participants were also informed about the potential benefits of participation
in the research study such as the evaluation of the MESA program and its effectiveness for
retaining students in STEM. All eligible participants were provided with a copy of the
Information Sheet to explain the nature of this research study, how their participation would be
used in the data collection, and the measures that would be taken to maintain their confidentiality
(see Appendix A). Participants were also given the Recruitment Letter, provided by the
researcher, as a formal invitation to join the study (see Appendix B). Prior to access to the
survey, the researcher handed the Consent Form to all eligible individuals who were interested in
participating in this study (see Appendix C). Once the Consent Form was completed, signed,
and dated, an electronic web link to the survey and access to a computer lab with desktop
computers were provided for teachers to complete the anonymous survey.
Sample
Quantitative approach. For the quantitative portion of the study, a survey instrument
was created with the intended sample population in mind, and the survey was distributed during
the summer of 2016. The instrument consisted of 21 closed-ended response items that anchored
at a 5-point Likert Scale, and ranged from “Strongly Disagree” (1) to “Strongly Agree” (5). A
total of 54 electronic questionnaires were distributed to the sample population. The survey
instrument was distributed to participants through an electronic web link using SurveyMonkey™
on August 6, 2016, as well as emailed to other eligible participants on August 8, 2016. The web
link remained active through the end of August 2016. The rationale for distributing the
electronic surveys at the vMASME event was to ensure there was an adequate number of
responses for the research study. Also, the number of surveys distributed was designed to take
into consideration a 95% confidence level, margin of error, and a conservative 50% response rate
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(Creswell, 2009; Fowler, 2009). A detailed description of the sampling method employed in this
study are discussed below.
To obtain an ample sample size that would be representative of the study population, the
researcher used the purposive convenience sampling method. The potential sample population
was identified using an online database of teachers and advisors involved in a site-based MESA
program under USC-MESA. Within each identified subgroup, purposive convenience sampling
was used to target a sample size of 50 or more participants, which ensured the data collected was
representative of the target population (Fink, 2013).
Qualitative approach. For the qualitative portion of this study, multiple layers were
used to collect data. The first layer entailed a review of MESA documentation, which included a
list of advisors and teachers eligible to partake in the survey and interview portions of the study.
The next layer was informed by the results of the quantitative data analysis. Of the participants
surveyed, five participants were purposefully selected to participate in the interview process.
The criteria for selecting these participants included voluntary participation, which was indicated
on the previously administered electronic survey, and whether participants’ experiences would
provide deeper insight about how MESA influenced educationally disadvantaged students’
persistence in STEM. Teachers and advisors who currently taught MESA courses or coordinated
MESA activities, and who also indicated a willingness to participate in an in-depth interview
after completing the electronic survey, were contacted for the qualitative interview process.
Access/Entry
Negotiating relationships with the participants in the study and with gatekeepers who can
either facilitate or inhibit the study is a key part of designing an effective qualitative study
(Maxwell, 2013). Gaining access to the study site and participants needed to be considered prior
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to conducting the study to ensure that data can be collected ethically and without harm, and so
that the information collected will answer the research questions (Maxwell, 2013). Obtaining
access to participants’ sites to conduct research was granted by the USC-MESA program
director. The researcher informed the program director about the proposed research design to
ensure the gatekeeper was fully aware of the intentions and purpose of this study.
Site Selection
Site selection was determined by accessibility, proximity to the Greater Los Angeles
Area, and ability to survey and interview criterion based populations. The researcher selected
the MESA Program that is housed and operated by the University of Southern California (USC)
MESA program. The researcher selected the USC Viterbi School of Engineering to conduct the
research study. The Viterbi School of Engineering works in partnership with the MESA Schools
Program to support educationally disadvantaged students to persist in STEM. The goal for USC
Viterbi is to support and matriculate students who are going through the MESA pipeline in the
greater Los Angeles Region, and in turn, increase the number of students earning STEM degrees.
Site Specifics
Under the USC-MESA Program, MESA advisors and teachers from four school districts
participated in both the survey and interviews.
District one. District One is located near the foot of the Angeles Forest and the San
Gabriel Mountains. Considered a “large” school district, approximately 18,000 students attend
the thirteen kindergarten through eighth grade schools and five high schools (reference withheld
for confidentiality). The majority of District One’s demographics consist of 50% Asian, 43%
Hispanic/Latino with 72% of the population identified as low socioeconomic. The middle and
high school sites offer the MESA program through the after school club format formats.
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District two. District Two is a mid-sized school district located near the Los Angeles
International Airport in the Los Angeles Basin of Southern California. Approximately 9,000
students attend seven elementary schools, three middle schools, and one science and math
magnet charter high school (references withheld for confidentiality). The students not enrolled
in District Two’s charter high school attend a public high school in a neighboring school district.
About 82% of the population are categorized as low socioeconomic and about 33% are part of
the English Language Learner (ELLs) subgroup (reference withheld for confidentiality).
MESA’s three middle schools and one middle school offers clubs, after school, and activity-
based programs.
District three. The District Three is located near the southwest region of Los Angeles
County. The total enrollment is approximately 3,000 students with the White and Hispanic
subgroups dominating the demographics at 53% and 22% respectively, and the Black and Asian
subgroups trailing at 15% and 10% respectively. Thirty-three percent of the student population
fall under the low socioeconomic subgroup, and approximately 3% are ELLs. District Three’s
charter school offers the MESA program through after school clubs.
District four. Established in 2004 and located near downtown Los Angeles, District
Four is a STEM-focused educational program, which is part of a three-school-site educational
program; one elementary, one middle, and one high school. Together, the schools service over
1,300 students with over 93% qualifying as low socioeconomic, and just over 24% identified as
part of the ELL subgroup (reference withheld for confidentiality). Students have the opportunity
to access the MESA program through District Four’s middle and high school clubs.
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Data Collection
Prior to conducting any surveys or interviews, the study design was approved by the
Institutional Review Board (IRB) at the University of Southern California. An explanatory
sequential mixed-methods approach, including a quantitative phase followed by the qualitative
phase, was used for this study (Creswell, 2009). The quantitative data were collected through the
surveys administered to the initially selected participants. In accordance with the explanatory
sequential mixed-methods research design, quantitative data were collected and analyzed prior to
initiating the second phase of qualitative data collection (Creswell, 2009).
Qualitative data collection occurred subsequently in order to provide rich, meaningful
data that elaborated upon the survey responses. Qualitative data consisted of collecting interview
data from five participants who volunteered to be interviewed. Because the researcher is the
instrument of data collection in qualitative research, research bias is a potential limitation of the
study (Creswell, 2009; Merriam, 2009). The process of triangulation, or the use of various data
sources, was essential in providing checks and balances on the results (Maxwell, 2013).
Triangulating the data allowed the researcher to increase the validity in the findings and reduce
the risk of any bias based on the use of only one method (Maxwell, 2013).
Data Collection Protocols
Both the survey instrument and interview protocol were influenced by the conceptual
framework and literature review. There were several factors that were outlined in the literature
which narrowed down the focus for this study. Specifically, the literature pertaining to the
persistence of first generation females in STEM majors suggested that they are uniquely
challenged by the lack of institutional support (Griffith, 2010), negative gender stereotypes
(Riegle-Crumb et al., 2012), and issues self-efficacy (Wang, M. T., & Degol, 2013). Using these
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challenges to frame the study, the study was designed to address the research questions and
understand the reasons for how MESA influences female students to persist in STEM majors.
Quantitative Data Collection
The data collected from the quantitative survey administered through SurveyMonkey
TM

served as a springboard to design a meaningful, in-depth interview protocol that provided
detailed explanations for how MESA has influenced the persistence of educationally
disadvantaged students in STEM courses, clubs, and activities (Creswell, 2009). The researcher
elected to utilize SurveyMonkey
TM
for its capacity to analyze open-ended results, create
comparison reports, and filter responses.
The research team was invited to attend a virtual MESA Academy for Science and
Mathematics Educators (vMASME) event in August, 2016. During the event, a total of 54
electronic surveys were administered using SurveyMonkey
TM
via web link to eligible USC-
MESA advisors and teachers. Some of the participants were present at the vMASME, while
others attended the event virtually. The USC-MESA directors allocated 30 minutes of the
vMASME schedule for the participants to voluntarily complete the survey. Of the total number
of surveys administered, 37 were completed and collected in August, 2016 for quantitative data
analysis.
Survey collection. Upon beginning the electronic or paper-based surveys, participants
were notified their responses would be considered confidential, their names would not be
associated with their responses, and their participation was completely voluntary. Participants of
this research study were given a time frame of approximately one month to complete the
confidential and anonymous survey. Beginning in August 2016, the electronic link for the
survey on SurveyMonkey
TM
became active and accessible to the participants, and the link
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remained open for responses through the end of August 2016 to accommodate the collection of
data from snowball sampling. Responses were gathered and stored directly on the
SurveyMonkey
TM
website which was password protected and only accessible to the research
team. On August 31, 2016, the link to the electronic survey on SurveyMonkey
TM
became
inactive and no further responses were recorded. Once all survey data had been entered, item
responses for the closed-ended questions were prepared for analysis by exporting the results
from SurveyMonkey
TM
into an SPSS Statistics, a software tool that allows for statistical analyses
of quantitative data.
Confidentiality. Confidentiality was established through the use of an anonymous and
confidential survey. Through the use of SurveyMonkey
TM
, a web-based survey application,
participants were able to complete the electronic survey without identifying themselves. The
researcher ensured the feature, which encrypts IP addresses, was selected to ensure complete
anonymity of electronic surveys. Furthermore, as the sample participants have no association or
previous connection with the research team, there is no way to identify participants.
An open-ended item on the survey was included, which allowed for participants to
indicate whether they were willing to be contacted for a follow up interview. Participants could
respond by selecting “No” and there answers would be stored as completely anonymous.
Alternatively, if participants selected “Yes,” they were provided a text box to provide their
personal contact information such as their name, email, and phone number. In this case, the
participants who volunteered to move forward with the interview process were granted
confidentiality by having an assigned code name. Throughout the data collection and data
analysis process, the researcher separated participants’ contact information from participants’
respective code names, and stored each list on two different password protected laptop
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computers. Furthermore, when not in use, the two laptop computers were stored under lock and
key in separate locations. Only the team of researchers coded all surveys and had access to the
survey data collected.
Qualitative Data Collection
Qualitative data collection occurred subsequent to quantitative data collection and
analysis. In order to identify the effectiveness of the MESA program for increasing the
persistence of economically disadvantaged students in STEM majors, a series of interviews with
various stakeholders were conducted during the summer and fall of 2016. The research team
interviewed MESA teachers and advisors who indicated a willingness to provide in-depth
responses via their electronic survey. The interviews were conducted in various formats based
on participant convenience, as well as opportunities for the research team to attend key MESA
events where greater numbers of advisors and teachers were present in one location. The
research team selected the focus group format during the Fall, 2016 MESA Advisors Planning
Retreat in order to maintain the integrity of the event’s scheduling. Participants who agreed to
the interview, yet did not attend the retreat, were given the option to conduct the interview at
their school site, by telephone, or at an agreed upon site. The highest priority for the research
team was to ensure that the participants were in a location where they felt comfortable enough to
answer honestly without fear of being overheard by school stakeholders. Environment-wise, the
interview locations and times were selected when it was relatively quiet in order to minimize
distractions and clearly hear the participants’ responses.
A semi-structured interview protocol was formulated to gain rich, meaningful data
(Merriam, 2009). The interview protocol, including an anticipated sequence of questions and
appropriate probes, was predetermined prior to conducting any interviews, but was adapted to fit
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the needs of each interview. One reason the researcher employed a semi-structured interview
protocol was it allowed for a structured approach when specific data needed to be elicited, and it
provided flexibility to include probes or follow-up questions if more information from the
respondent was needed (Merriam, 2009). For this study, a semi-structured interview was also
advantageous because it utilized the time allotted efficiently and afforded the researcher the
ability to collect the data necessary to answer the research questions.
During the actual interview, all participants were reassured their responses would only be
used for the purposes of this study and that their responses would be anonymous. Also, each
participant was verbally asked if they would consent to being audio recorded to accurately
capture the data. During each interview, the researcher wrote down key responses via paper and
pencil in addition to audio recording. The researcher remained neutral, but reassuring through
use of non-verbal cues such as nodding and frequent eye contact. Post data collection, the audio
records were transcribed using a professional transcriber from rev.com (2016). The rev.com
transcriber was a neutral outside member who is not affiliated with the research study.
Williams and Katz (2001) suggested that the use of focus groups in education offers the
potential to generate rich, detailed data that may not otherwise be gleaned through individual
interviews. According to Krueger and Casey (2014), people are more likely to share their
opinions when they are alike in some ways. Individuals decide to reveal based on their
perceptions of the people they are with (Krueger & Casey, 2014). For this study, the researcher
was interested in learning not only the effective practices that promote the persistence of
economically disadvantaged students in STEM, but areas that the MESA Schools program can
improve to increase access and retain as many students in the pipeline.
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Confidentiality measures were also established for the qualitative data collection. The
materials were transcribed by a professional third party transcriber, who had no affiliation to the
MESA program. Additionally, the transcribed interview responses, audio recordings, and
codebook were stored in separate locations on two password-secured laptop computers.
Data Analysis
The researcher analyzed the data collected from surveys using a quantitative method, and
the data collected from interviews and documents using a qualitative method (Creswell, 2009;
Merriam, 2009). Quantitative and qualitative data were analyzed separately in accordance to the
explanatory sequential mixed-methods design (Creswell, 2009). Quantitative data were analyzed
first so that the results of the data could inform the sampling procedure and the planning of the
qualitative data collection and analysis approach (Creswell, 2009).
Qualitative Data Analysis
Prior to analyzing qualitative data collected in the form of focus groups and interviews,
documentation and data provided by the MESA program was analyzed first. The USC-MESA
director provided the database of the school districts and school sites supported by USC-MESA,
a list of eligible participants, and a description of each site’s program. After analyzing the data
provided by the USC-MESA director, the interview data collected by the researcher were coded
using two steps. First, the researcher conducted an informal debrief immediately following each
interview and the focus group session, and second, the researcher employed a thorough analysis
using the Constant Comparative Method (Strauss & Corbin, 1990). The process of data analysis
is elaborated upon in more detail below.
The first step involved the data analysis, an informal process of reflective commentary
following each interview as recommended by Bogdan and Bilken (2007). Initially, all data were
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handwritten with pen and paper, and interview data were audio recorded. Audio recordings were
securely submitted to rev.com for transcription. Rev.com keeps all client information
confidential (rev.com, 2016). The files for this research study were securely stored and
transmitted using 128-bit SSL encryption, which is currently the highest level of security
available (rev.com, 2016). Rev.com did not share files or personal information with anyone
outside of the rev.com company. Files were visible only to the professional who signed strict
confidentiality agreements. Once the service was complete, rev.com deleted the study’s files at
the research team’s request (rev.com, 2016).
Following each interview, audio recordings and interview notes were compared to
confirm consistency of recorded responses. In addition, each evening after an interview had
been held, questions, and memos were jotted down near the raw data to begin developing ideas
(Maxwell, 2013). Finally, to prepare the handwritten data for analysis and interview, data were
imported into Dedoose, a web-based coding application, to facilitate the coding process.
Next the researcher analyzed the patterns identified from Dedoose, and applied the
Constant Comparative Method to code the data (Strauss & Corbin, 1990). The Constant
Comparative Method is rooted in the Grounded Theory approach (Glaser & Strauss, 1967). The
goal of using the Grounded Theory approach was to develop a theory to explain how an aspect of
the social world operates, thus the theory that emerges is connected to the reality from which it
was formed (Glaser & Strauss, 1967). Glaser and Strauss (1967) suggested that when the
Constant Comparative Method is used to generate a theory, the process includes the following
steps: selecting a phenomenon to study, identifying key concepts, making decisions about the
data collection techniques, and determining a relevant study sample. Using these ideals, the
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researcher ensured the study sample was appropriate for understanding the phenomena studied,
and that the data collected would directly address the research questions.
The first cycle of coding in the Constant Comparative Method was Open Coding (Strauss
& Corbin, 1990). During Open Coding, each line of text was typed into the Dedoose coding
program and organized, compared, and contextualized at the broadest level while trying to
maintain the integrity of the interviewees’ responses. Each code was highlighted in Dedoose and
a comment was added in the margins. The process of Open Coding continued until saturation
was achieved and no further codes could be derived from the data (Strauss & Corbin, 1990).
Following Open Coding, the next cycle of coding, Axial Coding, was used to identify
larger recurring themes and ideas within the data (Strauss & Corbin, 1990). During Axial
Coding, the researcher systematically categorized the smaller Open Codes based on emergent
cross-cutting themes in the literature, and common ideas within the interview and observation
data.
Finally, the researcher used the Axial Codes to complete the final step of Selective
Coding (Strauss & Corbin, 1990). The Selective Codes were the core themes that were used to
construct meaning from the data collected and derive a working theory grounded in the research.
All Open, Axial, and Selective Codes were recorded in the Dedoose application.
Merriam (2009) and Creswell (2009) indicated that the final step in data analysis involves
a period of intensive analysis with findings. Using data collected, in addition to literature review
and theoretical framework, the researcher was able to triangulate the data to determine if each of
the findings supported other findings, and whether they were aligned with the research questions.

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Instrumentation
The instrumentation selected to collect data for this study was based on the requirements
of conducting an explanatory sequential mixed-methods design. The first instrument used was
an electronic questionnaire, followed by the researcher as the instrument to review MESA
documents, and lastly, the semi-structured interview protocol to interview participants. The
survey contained a brief description of the research study, which was followed by a section for
participants to indicate informed consent regarding their willingness to voluntarily complete the
survey questionnaire (Appendix C).
Quantitative Data Collection Instrument
Pilot testing. The electronic survey was pilot tested in June 2016, a month prior to
distributing the survey to the sample population. The link to complete the electronic survey was
emailed to ten volunteers, including the advisor and associate advisor of MESA at USC. All ten
volunteers completed the survey within the time frame of one week. Pilot testing established that
the average completion time for the survey was between 10-15 minutes. Moreover, pilot testing
revealed two significant factors that were reconsidered prior to distributing the survey to
participants. First, five of the 20 closed-ended items from the survey were slightly reworded to
be clear for participants, one question was added as per the request of the advisor, and the
aesthetics of the survey were redesigned to include the MESA logo and pictures to further appeal
to participants. However, this minimal revision did not significantly affect the content of the
survey questionnaire or the information that was assessed. Once these changes were made to the
survey questionnaire, the link was redistributed two weeks after the original administration of the
pilot test to the same ten volunteers to establish test-retest reliability.
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Instrumentation. The survey instrument used to collect data in this study was an
anonymous, self-report questionnaire. The questionnaire was distributed to eligible site-based
MESA advisors and teachers. The survey contained a brief description of the research study,
which was followed by a section for participants to indicate informed consent regarding their
willingness to voluntarily complete the survey questionnaire (see Appendix D). In addition,
participants completed demographic data indicating their school district and number of years as
an advisor/teacher.
The 21-item instrument was measured using a 5-point Likert-type scale ranging from
“Strongly Disagree” to “Strongly Agree” (Fink, 2013). Point values were assigned to each
response in order to facilitate data analysis and values are indicated as follows: Strongly
Disagree (1), Disagree (2), Neither Agree or Disagree (3), Agree (4), and Strongly Agree (5).
The decision to provide participants with a neutral response was based on the principle that not
all items would be applicable to each participant completing the survey (Fink, 2013).
Furthermore, because the survey required an answer for each of the closed-ended items, this
allowed participants to denote their neutral stance without skipping an item or quitting the
survey. The final question asked participants to indicate whether they would like to be contacted
for a follow-up interview, and provided a space for participants to denote their contact
information.
In reference to the 21-item survey questionnaire, the closed-ended items were constructed
in order to address one of the four research questions guiding the study. A detailed item
breakdown for each research question is included in Table 1.

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Table 1
Survey Item Breakdown per Research Question
Research Questions Survey Items
Research Question One:

How is the Mathematics, Engineering,
Science, and Achievement (MESA) outreach
program preparing teachers to support
educationally disadvantaged middle school
students in Science, Technology, Engineering,
and Mathematics (STEM) activities and
courses?
4. The MESA program is structured to monitor
students’ progress throughout the math and science
courses.
5. The MESA program provides the students with
opportunities to network with like--minded peers.
6. The MESA program facilitates networking
opportunities with like--minded professionals.
9. The hands-on STEM activities prepare and supports
students in STEM learning.
12. I believe that MESA has influenced students’
persistence in STEM.
Research Question Two:

How do MESA teachers perceive the
impact of the MESA program in the
retention of educationally disadvantaged
students in STEM activities and courses?
7. I have seen an improvement in my students’ self-
efficacy in their science and math courses because of
the MESA program.
8. My students’ science and math course grades have
improved because of their experiences in the MESA
program.
10. My MESA students have a positive attitude
towards math and science courses because of their
experiences in the MESA program.
11. MESA has helped my students find other peers
with similar goals in STEM.
Research Question Three:

What resources are utilized in the MESA
program to prepare and support
educationally disadvantaged middle
school students in STEM activities and
courses?
3. The activities in the MESA program motivate the
students to persist in STEM.
13. The MESA program provides opportunities for
students to be exposed to careers in STEM.
15. MESA has provided professional development
opportunities that I would not have otherwise been
exposed to.
17. The MESA program shows me how to get the
resources I need to teach my courses effectively.
18. MESA provides opportunities for students to visit
universities/colleges to learn about STEM majors.
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Table 1 (Cont’d.)

Research Questions Survey Items
Research Question Four:

How do teachers perceive the effectiveness
of the MESA program in increasing the
persistence of educationally disadvantaged
students in STEM activities and courses?

14. The MESA program is essential for educationally
disadvantaged populations to succeed in a STEM
workforce.
16. Without the MESA program, my students would
have difficulty competing with their Southern
California peers in STEM.
19. What percentage of your MESA students
participated in supplemental STEM opportunities?
20. What percentage of you MESA students in
question 19 participated in Pre-MESA Day?
21. How often do your students in question 20
participate in other STEM competitions within a school
year?

Validity and reliability. Threats to the reliability and validity of quantitative data can
occur when the instrument has not been tested prior to being administered to the sample
population (Kurpius & Stafford, 2006). Prior to item generation, the researcher thoroughly
investigated the literature and theories related to the effectiveness of STEM outreach programs at
four-year universities in influencing the persistence of first generation females in STEM majors
(Kurpius & Stafford, 2006). Next, the researcher scrutinized the survey using item analysis,
which determined whether each item contributed to building a strong test by analyzing whether
the content matches the information, attitude, character, or behavior being assessed (Kurpius &
Stafford, 2006). Finally, the survey was administered to a pilot group, and the answers were
analyzed to determine if they were clearly understood by the participants and the answers
provided were within the expected range based on the literature review (Fink, 2013).

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Qualitative Data Collection Instruments
The researcher used MESA program descriptions and longitudinal data provided by
MESA to examine patterns that corroborated the survey data. After analyzing descriptive
statistics generated by the quantitative survey, and reviewing documentation provided by MESA,
the interview data protocol was established.
Interviews in the format of focus groups were conducted in qualitative research with the
intent to gain insight into another person’s mind when they are with others who have like
interests, professions, and lifestyles (Williams & Katz, 2001; Krueger & Casey, 2014; Merriam
2009). In qualitative research, interviews are essential because they provide information that
cannot be obtained through direct observations such as feelings, thoughts, and actions that
occurred in the past (Patton, 2002). Furthermore, a researcher cannot observe how another
person constructs meaning from an experience; a researcher would have to ask about that
(Merriam, 2009). For this study the researcher conducted interviews of MESA teachers and
advisers to understand their perceptions about MESA’s supplemental educational and student
support services, and had them describe their experiences in their own words. Moreover, the
interviews were semi-structured, which included open-ended questions and probes (Merriam,
2009). The semi-structured interview protocol allowed the researcher to gain rich data about
how teachers and advisors construct meaning from their experiences (see Appendix E).
Moreover, though the protocol was established prior to conducting interviews, the use of a semi-
structured approach allowed for flexibility in the interview process.
According to Merriam (2009), internal validity deals with the question of how well the
findings from a research study are congruent with reality. Because humans are the primary
instrument for data collection in qualitative methods, assessing validity is relative to how people
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construct the meaning of reality (Merriam, 2009). In turn, it is almost impossible for qualitative
researchers to objectively declare one truth or reality; instead, qualitative researchers must ensure
they employ strategies to increase the credibility, or trustworthiness, of their research findings
(Lincoln & Guba, 1985; Merriam, 2009).
Lincoln and Guba (1985) suggested that trustworthiness of findings is contingent upon
establishing the following: credibility, confirmability, transferability, and dependability.
Throughout the inquiry process of answering research questions, the researcher established
credibility and trustworthiness through peer review/examination, triangulation, and an adequate
amount of engagement in the data collection (Merriam, 2009; Miles, Huberman, & Saldaña,
2014).
Triangulation is a well-known practice to increase credibility of the researcher’s findings
(Merriam, 2009; Miles et al., 2014). When data is extrapolated from a variety of sources, the
researcher is able to cross-check for consistencies and inconsistencies (Merriam, 2009). The
researcher selected the explanatory sequential mixed-methods design to collect data from
multiple sources. For this study, survey responses and MESA document analysis were
corroborated with the data results from interviewing MESA teachers and advisors about the
persistence of educationally disadvantaged students in STEM. The researcher cross-checked the
data from each source and analyzed whether it validated or contradicted the findings. In
addition, to ensure credibility, all participants were fully informed of the purpose of the pilot
study, provided informed consent, and were told they could elect to withdraw from the study at
any point (Shenton, 2004).
The researcher was part of a team of three individuals who had similar research topics.
The team worked together to reach saturation of the relevant literature on STEM education, craft
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research questions, and design the interview protocols. The team engaged in frequent
discussions about how to analyze the data collection findings. In the early stages of analysis, the
team reviewed the raw data and discussed whether the codes and emergent themes were logical,
plausible, and tied to the literature reviewed (Merriam, 2009).
The researcher also devoted an adequate amount of time engaging in the raw data
collection to the point of saturation (Merriam, 2009). The researcher reviewed the raw data
repeatedly to generate an extensive list of codes and emergent themes. The time spent
exhausting the raw data is what allowed the researcher to extrapolate variations and themes that
were not necessarily evident in the early stages of data analysis (Merriam, 2009).
Confirmability, is analogous to objectivity in science, and ensures the data collected is
the true voice of the informants (Patton, 2002). Additionally, the researcher used
position/reflexivity throughout the entire inquiry process. Merriam (2009) suggested that the
researcher keep a journal, use observer comments, and record one’s thinking post observations
and interviews in order to continuously monitor for personal biases. The research team shared
the reflective journals, observer comments, and voice recordings, and cross-checked the raw data
to look for evidence of biases or misinterpretation.
Transferability refers to showing the findings are applicable in other contexts, while
dependability shows that the findings are consistent and repeatable (Lincoln & Guba, 1985).
With regard to transferability and dependability, limitations in the duration of the study, as well
as the small sample size and single sampling site, constrain the results of the study. However,
corroboration and triangulation attempted to address these issues. More data would need to be
collected over a larger scale and longer time frame to ensure transferability and dependability
(Merriam, 2009).
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Ethical Practices
Patton (2002) stated that credibility includes “intellectual rigor, professional integrity,
and methodical competence” (p. 570). These characteristics are important to any study because
all research must be conducted with integrity and the researcher should maintain an ethical
stance at all times (Merriam, 2009). Thus, it is important that research be conducted in an ethical
manner so that participants are protected from harm, given the right to privacy, are fully
informed of the study design, and are shielded from deceptive practices (Merriam, 2009).
In the quantitative portion of the study, the researcher maintained ethical practices by
creating a sound survey instrument and respecting the confidentiality of the participants who
took part in the survey. Furthermore, using Patton’s (2002) literature as a reference, Merriam
(2009) stated that the researcher’s level of credibility, rigorous methods of ensuring validity and
reliability, and upholding a deep respect for the qualitative inquiry process, are the essential
components of true qualitative research. The researcher constantly monitored the process for
collecting data by employing multiple credibility and trustworthiness strategies, as well as
preserved the confidentiality of the participants and the educational institution. Additionally,
Corbin and Strauss’ (2008) analytic tools were used to help the researcher dissect the data
through a lens that was not skewed by personal biases.
Ethical Interviews
In order to ensure ethical practices were maintained, the researcher reflected upon one’s
own personal values and ethical beliefs prior to designing the study and conducting any
interviews. One of the strategies the researcher implemented was to inform all participants of the
purpose of the study. Furthermore, the researcher ensured confidentiality of their responses and
obtained each participant’s verbal and written consent to interview and audio record prior to
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beginning each interview (Merriam, 2009). The researcher’s goal in doing this was to show the
participants that their time, perceptions, and experiences were valued, but more importantly, their
expertise of knowledge was well respected. It was very important to preserve the integrity of the
interviewees’ responses and to construct meaning from their perspectives. Finally, while
conducting interviews, the researcher consciously avoided passing judgments on participant
responses by a warm, but neutral stance.
Focus groups require additional ethical considerations that are above and beyond
conducting individual interviews. Since more than one person is part of the interview process,
the researcher requested that all participants commit to keeping the information, opinions and
discussion confidential (Longhurst, 2003). Additionally, the researcher took into consideration
that the confidentiality of the shared information cannot be guaranteed, so the researcher
reminded all participants to only share those things that they would feel comfortable being
repeated outside of the group (Krueger & Casey, 2014; Longhurst, 2003). Lastly, the researcher
paid careful attention to participant responses that may offend others in the group such as sexist,
racist, and other offensive remarks. Since the manner in handling each comment is unique and
sensitive to the context, the researcher was careful to take into consideration each participant’s
culture, gender, and beliefs to ensure that the content remained at a professional level (Krueger
& Casey, 2014; Longhurst, 2003). Participants who felt the need to share their thoughts and
opinions in a more confidential manner were able to speak with the researcher after the focus
group session. All participants’ comments were recorded with permission from the participants.
The following are additional ethical practices guided by Creswell (2009) that were
persistently monitored during the data collection, analysis, and interpretation process:

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a. Protecting the anonymity of individuals
b. Storing data in a safe location
c. Debriefing between the researcher and respondents to check for accuracy of the data
d. Anticipating repercussions of conducting the research on certain audiences and not
misusing results to the advantage of any one group, which is part of the IRB process
Summary
The explanatory sequential mixed-methods approach was utilized to support the
researcher in the investigation of how the MESA Schools Program prepares and supports
educationally disadvantaged middle school students in STEM activities and courses, the impact
MESA had on educationally disadvantaged students’ decision to persist in STEM, the resources
needed for teachers, advisors, and students to promote persistence, and how effective MESA has
been in retaining educationally disadvantaged students in the pipeline? Data were first collected
using surveys provided to MESA Schools’ teachers and advisers who worked at a school in the
greater Los Angeles County area. Then MESA documentation was analyzed, and finally
purposefully selected individuals from the surveyed population participated in interviews
conducted by the researcher. In Chapter Four, the researcher will present the findings, including
emerging themes, on MESA’s impact on the persistence of educationally disadvantaged students
in STEM courses and activities. Chapter Five will connect the findings from the data with the
literature and theoretical practices reviewed in Chapter Three. The researcher will also evaluate
MESA’s effectiveness for supporting and retaining educationally disadvantaged students in
STEM as well as promising practices for the MESA Schools program, the study’s limitations,
and recommendations for future studies.

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CHAPTER FOUR: FINDINGS
Background
The charge to improve America’s STEM workforce has increased in urgency over the
past 50 years. With the US steadily falling behind in the global ranks for math and science, the
government has flooded K-12 education, higher education, and the existing workforce with
STEM-based initiatives to promote persistence and retention in the STEM field (Gonzalez &
Kuenzi, 2012). Moreover, America’s trajectory graphs report a change in demographics over the
next 40 years. Both Hispanic and women are increasing in representation over the next 40 years,
yet the STEM workforce does not reflect these proportions. The STEM initiatives also address
the multicultural and gender deficiencies within the pool of high quality individuals to supply the
demands of the STEM industry (Bayer, 2014; Museus et al., 2011).
The leaky pipeline is the most widely used model to depict the pathway to careers in
STEM (National Academy of Sciences, 2007; Clark Blickenstaff, 2005; Cannady et al., 2014;
Metcalf, 2010). Over the course of elementary, secondary and higher education, students fail to
persist in entering the STEM workforce, thus contributing to America’s shortage of highly
qualified individuals (Metcalf, 2010). Additionally, target populations such as minorities and
females are particularly vulnerable to falling out at multiple points of the pipeline. Researchers
attribute the loss at each juncture to students’ lack of interest at the elementary level, limited
access and positive exposure to more complex math and science courses at the middle and high
school levels, and the indecisiveness to commit or “declare” a STEM major during the first year
of undergraduate school (Adelman, 2006; Berryman, 1983; Bonus-Harnmarth, 2000; Cannaday
et al., 2014; Hilton & Lee, 1988; Maltese & Tai, 2011; McKnight, 1987; Oaks, 1990; Strayhorn,
2011).
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STEM initiatives, also known as outreach programs, are designed to remove the
significant barriers that the education system has placed between underrepresented populations
and their opportunities to persist in STEM. Although the outreach programs vary, mostly all
provide services that prepare students for college level academic and social life experiences
(Swail et al., 2012). The Mathematics, Engineering, Science Achievement (MESA) program has
provided 35 years of motivating and preparing students for STEM majors and jobs throughout
California (MESA, 2016). The core of MESA’s mission is based upon the research that has
determined what STEM outreach programs should include in order to effectively support
educationally disadvantaged students (MESA, 2016). According to the meta-analysis data
results from the Wilder Research Report (Schultz & Mueller, 2006), effective STEM outreach
programs feature academic preparation, social networking and support, early intervention, parent
involvement, navigating the education system, long-term support, financial assistance, and
promoting systematic reform. MESA asserted that students who participate in its program
succeed because they have received rigorous academic support, individualized college and career
counseling, opportunities for industry related activities, opportunities for hands-on projects and
collaborative learning, student community support, well-trained math and science teachers, and
extensive networking (MESA, 2016). The body of literature reviewed by the researcher suggests
that support in these key areas play an important role in motivating students to persist in STEM.
Purpose
The purpose of this study is to explore the effectiveness of the MESA Schools Program
(MSP) on the retention of educationally disadvantaged populations in STEM activities and
courses. The intent of this study is to identify the key elements that contribute toward a
successful STEM outreach program. The findings will help provide future implications for
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rethinking and restructuring current STEM outreach programs, and to ensure they provide
equitable services for all traditionally disadvantaged populations.
The conceptual framework is structured around the key elements that create an effective
STEM outreach program for retaining educationally disadvantaged populations in STEM
activities and disciplines. The components of the conceptual framework include the following:
academic support systems, which compensate for inequities in the education system, positive
social interactions with like-minded peers and faculty mentors, built-in support network to
counteract negative gender and racial stereotypes, and motivational elements that influence
students’ persistence in STEM (see Figure 13). STEM outreach programs such as the Center for
Teaching, Learning, and Outreach (CTLO) at California Institute of Technology (CalTech), the
AIMS Program at Bowling Green State University, and the MORE Program at CSULA, have
proven to be successful due to their high retention rate of underrepresented populations.

Note: This figure illustrates effective elements in outreach programs.

Figure 13. Conceptual Framework of How Outreach Programs such as MESA Target
Disadvantaged Populations.

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Coding of Data

Once the data were collected, the researcher used an open-coding system to consolidate
the results and interpret what the participants stated in the interviews in order to conduct data
analysis (Merriam, 2009). The first step of data analysis involved an informal process of
reflective commentary following each interview as recommended by Bogdan and Bilken (2007).
Following each interview and the focus group session, audio recordings and interview notes were
compared to confirm consistency of recorded responses. In addition, after each interview,
questions and memos were jotted down near the raw data to begin developing ideas (Maxwell,
2013).
After collecting and reviewing all the survey results using the SPSS quantitative analysis
program, and the interview data using Dedoose, the researcher finalized the categories/
subcategories and coded the information. Next the researcher analyzed the transcribed
interviews and identified common emerging themes from the data to align with the guiding
research questions.
Guiding Questions
The following questions served as the framework that guided this study:
1. How is the Mathematics, Engineering, Science, and Achievement (MESA) outreach
program preparing teachers to support educationally disadvantaged middle school
students in Science, Technology, Engineering, and Mathematics (STEM) activities and
courses?
2. How do MESA teachers perceive the impact of the MESA program in the retention of
educationally disadvantaged students in STEM activities and courses?
3. What resources are utilized in the MESA program to prepare and support educationally
disadvantaged middle school students in STEM activities and courses?
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4. How do teachers perceive the effectiveness of the MESA program in increasing the
persistence of educationally disadvantaged students in STEM activities and courses?
This chapter will review the participants, schools, and organizations that participated in this
study. The guiding questions stated above will be addressed individually following the key
statements made by the participants. Themes will emerge from data analysis and from
participants’ responses.
Participants
This study was completed with the support of the USC-MESA directors. Participants
were surveyed and interviewed based on availability during the data gathering process. Surveys
and interviews using a focus group format were used to help triangulate the data collected in
order to present descriptive information, reduce bias, and increase reliability of data (Creswell,
2009). Participants have been kept anonymous for confidentiality and to ensure authentic
information was obtained. Table 2 lists the participating school sites that are serviced by a
college-designated MESA service center, which is located within the boundaries of the greater
Los Angeles area. Since each site’s program depends upon on the school’s culture, facility
resources, and student demographics, the type of program, total number of students participating
in the MESA Schools Program, as well as the total student body count are noted.

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Table 2
MESA Middle Schools
Sites Type of Program
Offered
Total Number of Enrollment
at all USC-MESA Sites
Site A
Site B
Site C
Site D
Site E
Site F
Site G
Site H
Site I
Site J
Site K
Site L
Site M
Site N
Site O
Site P
After School
After School
MESA Period
Lunch
MESA Period
After School
After School
After School
After School
Club
Club
After School
After School
After School
After School
After School

783

The majority of the participants from the 16 middle school sites completed the survey at the
vMASME conference on August 6, 2016. The most common format for offering the MESA
program is after the school day. Eleven school sites offer MESA after school component, two
have preserved a course period for MESA, two use a club format, and one school site provides
MESA during the students’ lunchtime.
Quantitative Data
Based on the selection criteria, a quantitative survey (Appendix D) was distributed to 48
eligible MESA advisors and teachers. From those 48 MESA advisors and teachers, 25 responses
were received. Participants responded to a 21 closed-ended item survey through
SurveyMonkey™. Participants were asked to report their years of service as a MESA
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advisor/teacher. Table 3 presents a breakdown of the total number of survey participants and the
years they have been an advisor/teacher for the USC-MESA program.

Table 3
Quantitative Survey: Number of Years Served as a Teacher/Advisor for MESA Middle School
Measure 0-2 years 3-5 years 6-8 years 9 years or more Grand Total
Number
Percentage
7
28.0
6
24.0
6
24.0
6
24.0
25
100

The amount of years participants have served as MESA advisors ranged from zero, or brand
new, to nine or more years. Although the span is somewhat evenly distributed between 0-2
years, 3-5 years and 6-8 years, almost one-third of the participants fall into the 0-2 year category.
Qualitative Data
The qualitative portion of the study consisted of one focus group meeting, in-person
interviews and phone interviews. Of the 25 survey respondents, a total of five advisors/teachers
voluntarily participated in a focus group interview (see Table 4). A predetermined set of open-
ended questions (Appendix E) were utilized for the interview protocol.

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Table 4
Participants in the Study

Participant

Years as a MESA
Advisor/Teacher
Total Number of
Years in
Education
Teacher #1
Teacher #2
Teacher #3
Teacher #4
Teacher #5
5
3
9
7
5
5
4
12
10
5

All five teachers participated in the focus group interview held at the MESA Advisor
Workshop in the Natural History Museum conference room on September 7, 2016. Additionally,
each teacher participated in a follow-up interview in October either in person or by telephone.
The researcher interviewed Teachers 1, 3 and 4 in person, and Teachers 2 and 5 completed the
interview by phone.
Findings by Research Question
The tools that helped identify the factors that contributed toward preparing and
supporting educationally disadvantaged students in STEM included the self-administered survey
using SurveyMonkey™ and the semi-structured interviews in both individual and focus group
formats. Combined, the data was synthesized and analyzed to determine how the Mesa Schools
Program (MSP) is being implemented at the selected sites. In order to narrow the focus down to
the most influential components that contribute toward an effective STEM outreach program, the
researcher compiled a list of best practices based on the literature reviewed. These practices
were translated into the survey questions that helped extrapolate measureable data to determine
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which practices MESA teachers and advisors considered the most effective. The survey results
revealed patterns that guided the researcher in the preparation of qualitative-based questions that
provided a more detailed participant response about how MESA implemented these supports and
what that actually looked like at the participating sites.
Data was collected using self-report survey instruments and was analyzed in SPSS using
an appropriate statistical test to answer the four research questions shown in Chapter One. To
answer Research Question 1, the researcher provided a teacher survey that was sub scaled based
on the research questions. SPSS provided the overall mean, the mean for each individual teacher
survey questions, standard deviation, and reliability for how closely related the teacher survey
questions were to the research question. The questions in the teacher survey that helped answer
Research Question 1 are noted in Table 5.
Research Question One
How is the Mathematics, Engineering, Science, and Achievement (MESA) outreach program
preparing teachers to support educationally disadvantaged middle school students in Science,
Technology, Engineering, and Mathematics (STEM) activities and courses?

Table 5
Survey Items per Research Question
Survey
Question
Number

Survey Items
4: The MESA program is structured to monitor students’ progress throughout the
math and science courses.
5: The MESA program provides the students with opportunities to network with
like-minded peers.

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Table 5 (Cont’d.)
Survey
Question
Number

Survey Items
6: The MESA program facilitates networking opportunities with like-minded
professionals.
9: The hands-on STEM activities prepare and supports students in STEM
learning.
12: I believe that MESA has influenced the students’ persistence in STEM.
Note. Results expressed as the average of teacher responses made on a 5-point scale (1=Strongly Disagree,
2=Disagree, 3=Neutral, 4=Agree, and 5=Strongly Agree).

Table 6 indicates that the overall results for research question 1 were (M= 4.02, SD=.48)
conveying that there is an overall agreement that the MESA middle school teachers felt that they
were being prepared to support educationally disadvantaged students in STEM activities and
courses.

Table 6

Total Mean for Research Question One
Computation N Mean Std. Deviation
(SQ4 + SQ5 + SQ6 + SQ9 + SQ12) / 5 25 4.0160 .479317

Table 7 shows the results for each teacher survey question that helped answer Research
Question 1. Exception for survey question 4, the other survey questions were above a mean
scaled score of 4, suggesting that the teachers agreed with the survey question asked. Survey
question 9 resulted with the highest mean (M= 4.32) and survey question 4 resulted with the
lowest mean (M= 3.28). Survey question 9 asked if the hands-on STEM activities prepared and
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supported ED students. Survey question 4 asked if the program was structured to monitor
students’ progress throughout the math and science courses.
The alpha coefficient for the five teacher survey items was .704, suggesting that the items
have relatively a high internal consistency in regards to research question one.

Table 7

Research Question One: Mean for Each Teacher Survey Question

SQ N Mean Std. Deviation
4 25 3.28 1.137
5 25 4.24 .436
6 25 4.08 .759
9 25 4.32 .557
12 25 4.16 .374

Table 8

Reliability Statistics for Research Question One
9

Reliability Statistics
Cronbach's Alpha N of Items
.704 5
Note. A reliability coefficient of .70 or higher is considered acceptable.

The survey items that revealed which types of support were most impactful in preparing
and supporting students were SQ5, SQ9, and SQ12. Survey question 9 received the highest
mean score of 4.32 , which indicates that teachers and advisors strongly believe that the hands-on

9
This table is provided to show the Survey Questions were closely aligned with the Research Questions.
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activities equipped students to be successful in STEM. When cross-analyzing SQ9 with the
teacher and advisor participant responses in the focus group interviews, the teacher and advisor
responses reinforced their belief that the MESA hands-on activities are highly effective. One
emerging theme showed that teachers and advisors believe that the hands-on activities are
beneficial for students struggling in their math and science courses.
For example, participant statements showed evidence of perceived value of the hands-on
STEM-based activities leading to increased chances for success in math, sciences, and other
STEM courses. Teacher 3 stated, “But a lot of kids I think would respond well to the hands-on
type approach in MESA, who perhaps are having difficulty with abstract mathematics.” Teacher
1 further supported Teacher 5’s statement by providing an example which explained why ED
students respond well to the hands-on activities.
I know talking to the STEM coordinator last year, I had a student failing my Introduction
to Engineering Drawing and he wanted to push to get him into MESA. He thought he
would respond better to that than the more academic setting. (Teacher 1)
Research Question Two
How do MESA teachers perceive the impact of the MESA program in the retention of
educationally disadvantaged students in STEM activities and courses?

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Table 9

Participant Survey Questions Correlated to Research Question Two

Survey
Question
Number

MESA program on Student Retention in STEM
7: I have seen an improvement in my students’ self-efficacy in their science and
math courses because of the MESA program.
8: My students’ science and math course grades have improved because of their
experiences in the MESA program.
10: My MESA students have a positive attitude towards math and science courses
because of their experiences in the MESA program.
Note. Results expressed as the average of teacher responses made on a 5-point scale (1=Strongly Disagree,
2=Disagree 3=Neutral, 4=Agree, and 5=Strongly Agree).

As shown in Table 9, the survey questions specifically addressed the MESA teachers’
perceptions of whether the MESA program showed an improvement in students’ grades for
science and math courses, students’ perceived abilities and attitudes in successfully completing
STEM courses, and an increase in networking among student peers in order to continue
supporting one another in STEM courses and activities. The response data indicated which types
of support most significantly impacted student retention in STEM. From the results, additional
semi-structured qualitative questions were generated in order to gain insight about MESA
teachers’ beliefs and perceptions of why they thought the identified support was successful in
retaining ED students in STEM education.
The overall quantitative data results for Research Question 2 were (M= 3.68, SD=.67).
This signifies that MESA middle school teachers/advisors were neutral, but slightly leaned
toward the agreement that the program makes an impact in retaining ED students in STEM
activities and courses (Table 10).

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Table 10

Total Mean for Research Question Two

Computation N Mean Std. Deviation
(SQ7 + SQ8 + SQ10) / 3 25 3.6800 .66999

Table 11 indicates that survey question 10 had the highest mean score of 3.88 in teachers’
beliefs that support provided by the MSP positively impacted students’ grades in math and
science courses as well as improved their attitudes towards STEM courses and activities. The
qualitative data corroborates with the survey results for SQ10 and further explains why teachers
believe students’ attitudes towards STEM have improved due to activities and supports in the
MSP. The MESA program requires the teachers and advisors to retain the same student
enrollment for consistency. In the focus group interview, Teacher 4 explained,
The expectation that we re-enroll students has actually worked to their benefit. I just
talked to the kids, and they stay in the program because they have to at first, but then after
those first couple of years of becoming a team together, they really, really want to stay in
the program. They like the camaraderie.
Teacher 5 added, “They like the thinking and stuff that goes on and think it's going to
help them no matter what they do.” The advisors believe that as the students continue in the
MESA program year after year, they not only see the value in applying deductive reasoning
coupled to the hands-on activities, but also the socializing and peer connections along the way.

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Table 11

Research Question Two: Mean for Each Teacher Survey Question

SQ N Mean Std. Deviation
7 25 3.48 .963
8 25 3.68 .690
10 25 3.88 .781

Table 12

Reliability Statistics for Research Question Two
10

Reliability Statistics
Cronbach's Alpha N of Items
.752 3
Note. A reliability coefficient of .70 or higher is considered acceptable.

Research Question Three
What resources are utilized in the MESA program to prepare and support educationally
disadvantaged middle school students in STEM activities and courses?
Research Question 3 addresses the need to provide educationally disadvantaged students
with resources to support and prepare them in STEM activities and courses. The body of
literature reviewed by the researcher suggested that underrepresented minorities, including
females, benefit from STEM outreach programs that provide support specific to preparing them
for academic and social life experiences (Swail et al., 2012). MESA utilized the meta-body of
literature for effective STEM outreach programs to craft its mission statement as well as the

10
This table is provided to show the Survey Questions were closely aligned with the Research Questions.
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critical support components to ensure educationally disadvantaged participants in MSP are
successful. Both the literature and the key support components in MSP were the basis for
creating the quantitative portion of this study. The survey instrument contained questions that
investigated MESA teachers’ perceptions of which evidence based resources were most effective
in supporting educationally disadvantaged students in STEM. The researcher analyzed the
responses and crafted semi-structured interview and focus group questions to delve deeper into
understanding exactly why teachers felt that certain supports are more effective.

Table 13
Survey Items per Research Question
Survey
Question
Number

Survey Item
3: The activities in the MESA program motivate the students to persist in STEM.
11: MESA has helped my students find other peers with similar goals in STEM.
13: The MESA program provides opportunities for students to be exposed to careers in
STEM.
15: MESA has provided professional development opportunities that I would otherwise
never have been exposed to.
17: The MESA program shows me how to get the resources I need to teach my courses
effectively.
18: MESA provides opportunities for students to visit universities/colleges to learn
about STEM majors.
Note. Results expressed as the average of teacher responses made on a 5-point scale (1=Strongly Disagree,
2=Disagree 3=Neutral, 4=Agree, and 5=Strongly Agree).

The overall results for Research Question 3 were (M= 4.06, SD=.48). The data indicated
that the majority of MESA teachers surveyed agreed that the resources provided by MSP
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supported educationally disadvantaged students to persist in STEM activities and courses at the
middle school level.

Table 14

Total Mean for Research Question Three

Computation N Mean Std. Deviation
(SQ3 + SQ11 + SQ13 + SQ15 + SQ17 + SQ18) / 6 25 4.0600 .48084

Based upon the results for individual questions, SQ3, SQ15 and SQ18 received the
highest mean scores at 4.24. This indicates that the hands-on MESA activities, teacher
professional development, and visitations to colleges and universities are key resources to
prepare and support educationally disadvantaged students in STEM. According to SQ3, the
advisors believe that the MESA activities highly motivate students to persist in STEM.
Teacher 1 stated, “They offer a STEM research, like where they go to Catalina and they get to be
scientists and learn about what's special about Catalina and different science skills, marine and
what not.” When students participate in STEM-based activities in real world situations such as
the Catalina event, it provides relevance to what they will need to complete meaningful tasks that
can affect others in the world. Corresponding to the high mean score for SQ15, Teacher 4
responded during the interview,
During our once a month PD workshops, all the teachers/advisors engage in an activity
that we can take directly back to our site. We are directly involved with the activities and
they allow me to experience the activity on my own before I present it to my students.
By experiencing the activity, I find my misconceptions and know how to provide probing
questions to the students.
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With the monthly support and guidance of the USC MESA directors, the teachers feel
more confident in ensuring the students will be able to understand the engineering process and
apply it to the hands-on activities when they have the time to explore STEM-based concepts
during a protected time. The MESA advisors also believe that the supplies and materials
provided to them during the once a month meetings help connect the students to the hands-on
STEM activities quickly. Teacher 4 added,
I think MESA, here at least, they give us a lot of opportunity to take supplies that are
helpful for a variety of different experiments so they let us first hand grab what we think
our kids would be interested in. It's a lot, they let us take a lot of stuff to run those
experiments and get our kids interested in the engineering design process activities.
The goal for the MESA program is to provide access to educationally disadvantaged students
with as few barriers as possible. Having the monthly professional development meetings and
making the materials readily available streamlines the support and improves accessibility.

Table 15
Research Question Three: Mean for Each Teacher Survey Question
SQ N Mean Std. Deviation
3 25 4.24 .523
11 25 3.84 .800
13 25 4.08 .909
15 25 4.24 .723
17 27 3.67 1.000
18 25 4.24 .663

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Table 16
Reliability Statistics for Research Question Three
11

Reliability Statistics
Cronbach's Alpha N of Items
.660 6
Note. A reliability coefficient of .70 or higher is considered acceptable.

Research Question Four
How do teachers perceive the effectiveness of the MESA program in increasing the persistence of
educationally disadvantaged students in STEM activities and courses?
MESA’s overall mission statement is to serve and increase the engagement of
educationally disadvantaged students in STEM. MESA does this by providing more than
academic services. In order to pursue and graduate with degrees in science, technology,
engineering and mathematics the MSP also provides mentoring, social and early exposure to
STEM experiences. Based on the Wilder Research Report (Schultz & Mueller, 2006), common
key features in effective STEM outreach programs include academic support, social networking
and social support, early intervention, exposure to and guidance in navigating college, long-term
support, and financial assistance. Research question four investigated whether the MESA
teachers/advisors perceived that these supports influenced educationally disadvantaged students
decision to persist in STEM courses and activities throughout middle school and into their high
school years.

11
This table is provided to show the Survey Questions were closely aligned with the Research Questions.
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Table 17

Survey Items per Research Question

Survey
Question
Number

Survey Questions
14: The MESA program is essential for educationally disadvantaged populations to
succeed in a STEM workforce.
16: Without the MESA program, my students would have difficulty competing with
their Southern California peers in STEM.
Note. Results expressed as the average of teacher responses made on a 5-point scale (1=Strongly Disagree,
2=Disagree 3=Neutral, 4=Agree, and 5=Strongly Agree).

The overall results for research question four were (M= 4.04, SD=.76). This signifies
that MESA middle school teachers/advisors perceived that comprehensively, MSP is effectively
influencing educationally disadvantaged students to persist in STEM. Given that the majority of
the middle school MESA program is offered during lunch and afterschool, the teachers/advisors
perceived that this type of program works well with sparking and maintaining students’ interest
in STEM, and hopefully continuing with the program. Teacher 5 stated,
When I had students coming in asking me to be an advisor, because there are about 150
students at our campus who are part of MESA and really passionate about it, and they
were distraught that their club was going to be disbanded, and they wanted to continue it.
Teacher 5 expressed, “They like the camaraderie.” When asked if she believed the
MESA program helped educationally disadvantage students to persist in STEM, Teacher 5
further expressed
Students who are ACTIVE participants in MESA seem to be more confident in their
abilities to solve problems and persevere. They don’t give up as easily and seem to be
okay with trying, potentially making mistakes, and then trying again.
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The overall responses from the teacher survey and interviews indicated that the teachers
perceived the MSP to be effective towards educationally disadvantaged students in persisting
towards STEM, particularly in cultivating their interests through hands-on STEM activities.

Table 18
Total Mean for Research Question Four
Computation N Mean Std. Deviation
(SQ14 + SQ16) / 2 25 4.0400 .76267

Table 18 shows the results for each teacher survey question that helped answer Research
Question 4. SQ14 and SQ16 had relatively the same mean score and the highest alpha
coefficient reliability (Cronbach’s Alpha = .860) amongst the other research questions,
indicating that the questions were closely related to Research Question 4. SQ14 and SQ16 asked
the teacher participants if MSP is essential for educationally disadvantaged students to be
successful when and competing with their advantaged peers in STEM.

Table 19
Research Question Four: Mean for Each Teacher Survey Question
SQ N Mean Std. Deviation
14 25 4.00 .866
16 25 4.08 .759

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Table 20
Reliability Statistics for Research Question Four
12

Reliability Statistics
Cronbach's Alpha N of Items
.860 2
Note. A reliability coefficient of .70 or higher is considered acceptable.

Ancillary Findings
During the focus group and individual interviews, the participants provided additional
information that contributed towards gaining a more precise understanding about how the MESA
program supported educationally disadvantaged students to improve their interest in STEM, yet
was not the central focus of the four research questions. Participants shared their opinions about
the current resources available for both the MESA advisors and the MESA students, as well as
their perceptions about the possible barriers in maximizing the program’s effectiveness in
increasing the persistence of educationally disadvantaged students in STEM courses and
activities. The following themes emerged based on the participant response results: Alignment
of the Next Generation Science Standards (NGSS) to the MSP curriculum, the impact of funding
on the MSP, program marketing for key stakeholders, advisor support and retention rate,
participation requirements, and competing against other after-school programs for recruiting new
students. Table 20 exhibits these emerging themes, number of responses for each theme, and a
sample participant response.

12
This table is provided to show the Survey Questions were closely aligned with the Research Questions.
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Table 21
Ancillary Emerging Themes
Emerging
Themes
Number of
Participant
Responses Sample Participant Response
Funding
Impacts
MESA
7 “They used to have a 2-week residential program where the kids
actually stayed here at USC and stayed overnight and did all these
STEM activities. This year what they did, because of the money
issue, the kids had to come everyday. They didn't get a chance to stay
on campus. It was a commuter program this year.” (Teacher 1)
Marketing for
Stakeholders
6 “The kids who get invited know about it, but I don't think there's this
widespread understanding of what is it. Why would I want to do it?
I send out letters of invitation to the students. They said, "It's the
first time I was invited to do something, so that's why I did it.”
Without really even knowing.” (Teacher 3)
Advisor
Support and
Retention
11 “I'm not really sure what my role is and where I'm supposed to go
because it's a brand new start to the school year. The students know
more about the program than I do. It's a little bit of a frustration.”
(Teacher 4)
Site-based
Club
Requirements
Conflict with
MESA
Requirements
5 “One of the other MESA advisors here mentioned we have a
requirement that a student needs to be passing all their subjects
before they go for any after-school activities. She said she actually
takes failing students into MESA because it tends to support the
other work if they can work with their hands after school.” (Teacher
4)

Funding Impacts MESA
During the focus group interview, several teacher participants explained how the MESA
program depends upon funding from STEM-related organizations and grant programs to provide
field trip opportunities and up-to-date, hands-on activities for the MESA students. Advisors
modify/expand their program based on the money available for that particular school year.
Teacher 2 shared, “For this specific program, they pay for an entire school program at our school
and so they have a budget for them.” Teacher 2 also stated, “This last year, they had extra
funding so they were able to pay for it this year the same as well.” Several teacher participants
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expressed their concerns about the lack of, or inconsistencies in funding. Teacher 2 added, “If in
the future it becomes a problem or an issue then there's potentially no MESA. I think that's one
of the issues along with funding for the school in general.” Teacher 1 expressed her frustrations
with activities and field trips that were traditionally in place, but are no longer available or
effective due to spending cuts.
It's hard just because we're unable to provide some of the robotics. I know last year after
I left, they were unable to purchase a new robotics kit, and they said, the students that I
spoke with this year said that it was really hard to work with just because it was older and
the screen was not working properly. (Teacher 1)
In regards to field trip opportunities, Teacher 1 replied,
They used to have a 2-week residential program where the kids actually stayed here at
USC and stayed overnight and did all these STEM activities. This year, what they did,
because of the money issue, the kids had to come everyday. They didn't get a chance to
stay on campus. It was a commuter program this year.
The teacher advisors know that funding can be modified at any given time, so they adjust
accordingly based on what is provided.
Marketing MESA to Stakeholders
According to the survey data results for Research Question 3, MESA advisors agreed that
MSP impacts educationally disadvantaged students’ decision to persist in STEM-based courses
and activities. However, advisors believe that marketing is key to educating stakeholders about
the benefits of the MESA program. Teacher 3 stated,
Marketing, like that's huge, it's like grass roots. We do it in the schools and the people in
the schools know about it. The kids who get invited know about it but I don't think
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there's this widespread understanding of what is it. Why would I want to do it? When I
send out invitation letters to our target students, they said, ‘It's the first time I was invited
to do something, so that's why I did it,’ without really even knowing.
Advisors also noted that the parents of the MESA students have reservations about
particular activities. Teacher 2 explained,
For example, the summer camp and the Catalina study trip? I have noticed that a lot of
parents and families, they don't want their child to go. It takes a lot of convincing. I will
be there, staff will be there, here's my cell phone number, but even then, I've noticed that,
at least in my community, they are very distrustful of letting their child, especially girls,
go to these events, even a Saturday fieldtrip. They're very apprehensive and they'd rather
they just stay home.
The researcher probed to gain further insight about the parents’ understanding of the
benefits of MESA by stating, “So the family component may be a barrier.” Teacher 2
responded, “Yes. Regardless of the opportunities that you provide.” MESA advisors also
commented about the misconceptions about MSP among teachers outside the math and sciences.
Teacher 1 stated,
And I had one teacher who is a language arts 8th grade teacher and she was new to our
school. She wanted to get involved in after-school clubs. She spent 20 minutes at a
MESA meeting, said it wasn't for her, and left. She said she was too overwhelmed, but it
doesn't really matter. If the teacher is committed, then the subject matter, at least at our
school, doesn't matter what you teach.
The researcher further clarified by asking if it is a requirement for MESA advisors to be
knowledgeable in STEM-based content. Teacher 1 explained, “It's a lot more about mentoring
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the kids and guiding them than it is about actually knowing the math and science sometimes.
But if you don't know the math and sciences, and that's not why you chose to do it, it can be very
intimidating because you feel like you have to know it all. It's kind of a teacher mentality to
think you have to know it all.
New Advisor Support and Advisor Retention
During the focus group interview, the researcher asked all participants to introduce
themselves and share how they became a MESA advisor. A common theme among the
participant responses was their lack of knowledge initially about the responsibilities of the
advisor role and how to manage the program at their site.
• . . . with me, nobody mentored me. Even though she's still on campus. It's literally,
‘Figure it out.’ And that's how we've done it. That's the one thing I wish teachers
were more in mentoring. Okay, I want to pass you the reins and let me show you
what works for me. I just had to figure it out, so that made it hard. The beginning
was really rough. (Teacher 2)
• I looked up the program and saw some of their missions and their values and I really
agreed with it and aligned with it and I've always wanted to become a MESA advisor.
It's my first year experiencing it, so hopefully I'll have some support from the staff
here. (Teacher 4)
Advisor participants also shared how they managed to configure the MESA program to
make it work with their school. Since each school has its own unique factors such as location,
space availability, staffing, student population, funding, climate and club criteria, advisors must
make decisions that best fit their particular site.
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• Okay, so each site has it's own barriers and challenges or unique population and
composition that if you're a teacher you have to figure out how to make it work so
that it maximizes what the program has to offer and what it looks like at your site.”
(Teacher 2) Teacher 2 added, “And so you don't quit after a semester.
• Schools also have various sized programs, like some schools will have 25 kids, some
schools will have 100 kids. You don't really know what you're walking into as a new
advisor sometimes. (Teacher 3)
Advisors also provided an explanation as to the reason why approximately one-third of
the study participants are new to the position. The majority of the new advisors inherited the role
due to the previous teacher stepping down from the position, or the position was vacant.
• I am a new teacher to the school and my department chair informed me about this
program. I found out that they were about to disband the program because they
couldn't find an advisor. (Teacher 4)
• I left, personally, at the beginning of last year because I went to Australia to do
research. So that was my reasoning for leaving. When I came back, the previous
advisor that was in place was no longer doing it, and it was more not because of
anything with USC, but the school itself wasn't being supportive. (Teacher 3)
School Site Requirements Conflict with MESA
Although the MSP does not mandate that educationally disadvantaged students who wish
to participate in the program maintain a minimum grade point average (GPA), some advisors
shared that their school site required all students to meet the expected GPA in order to be eligible
to join any club. During the individual interview with Teacher 4, the researcher asked a
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clarifying question as to whether MESA required students to maintain a passing GPA in order to
stay active in the club. Teacher 4 responded,
Apparently it's a judgment call at each school. At mine, it's a requirement. At my school,
not MESA, my school, if they’re going to be in any after school activity including sports
or MESA, any other clubs or the prom they have to have all passing grades.
A fellow MESA advisor changed the requirement at her school site by allowing
struggling students to join the program. Teacher 4 explained the other advisor’s system for
recruitment, “She said she actually takes failing students into MESA because it tends to support
the other work if they can work with their hands after school.” He explained the benefits of
removing the GPA requirement, “. . . particularly if we get students who are marginalized from
purely abstract type thought it would be very good for that.” The previous school year, Teacher
4 saw a shift in mindset at his school in regards to how MESA can help struggling students.
I know talking to the STEM coordinator last year, I had a student failing my Introduction
to Engineering Drawing and he wanted to push to get him into MESA. He thought he
would respond better to that than the more academic setting.
Teacher 4 further explained why this model has more flexibility for the targeted student
population, “Deciding to include GPA as a requirement should be the advisor’s judgment call on
how to best work with their students so that they are successful. Without the GPA, it’s kind of a
persistence model.”
Reflection
The reflection portion of this study aims to analyze whether the MESA program is
effectively supporting educationally disadvantaged middle school students to persist and improve
engagement in STEM. The body of literature reviewed revealed that STEM outreach programs
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such as MESA serve to compensate for the inadequacies that the education system has placed,
and aim to find ways to promote and maintain students’ interests and achievement in academic
and social success (Schultz & Mueller, 2006). Research indicated that underrepresented students
significantly benefit from attending an outreach program, especially improving their access
towards college (Gándara & Bial, 2001; Macy, 2000; Vargas, 2004). Table 21 shows a
comparison between the researcher’s conceptual framework, the suggested components of an
effective STEM program, and the key features of the MESA program.

Table 22
Comparison of Support among Framework, Literature, and MESA
Conceptual
Framework
Research-Based Features of
Effective Programs
MESA Schools Program
(MSP)
Academic
Support
• Prepare students
academically
• Intervene early
• Help students navigate the
college admissions process
• Provide comprehensive,
long-term support
• Individual Academic Plans
• Study skills training
• MESA day Academies
• MESA periods
Motivational
Support
• Provide comprehensive,
long-term support
• Incentive awards
Social
Support
• Involve and encourage
parents/family.
• N/A
Networking
Support
• Balance academic support
with social support
• Provide financial assistance
• Career and college
exploration
• Teacher professional
development opportunities

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Academic Support
The research suggested that underrepresented minorities are effectively supported
academically through early intervention, assistance with navigating the admissions process, and
comprehensive long-term support (Gándara & Bial, 2001; Schultz & Mueller, 2006; Swail et al.,
2012).
MESA provides early intervention through the implementation at the middle school level. The
purpose is to generate interest and build confidence by preparing ED students to persist in STEM
courses in high school. MESA also offers academic plans to monitor student progress, study
skills development, enrichment activities, allocated times for MESA periods, and college
enrollment support.
Research showed that when educationally disadvantaged students are exposed to hands-
on, STEM-based activities outside of their regular class period, it increases their likelihood to
pursue and persist in STEM courses and activities in the high school (President’s Council of
Advisors on Science and Technology, PCAST, 2010). The fact that MESA starts the program in
middle school is better than not having one at all. Middle school is a prime time to build
students’ confidence and instill positive experiences in science and math so that when they enter
high school, they are more likely to continue taking STEM courses (PCAST, 2010).
Although MESA encourages schools to dedicate a math and/or science period to support
educationally disadvantaged students by implementing the suggested strategies concurrently with
the California state standards-based curriculum, very few sites implement the program at this
capacity. This causes a trickle effect on how well MESA advisors/teachers can support students.
If the students are part of MESA during lunch or after school, the advisor may not necessarily be
the student's math or science teacher. Therefore, it would be difficult for the advisor to monitor
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students’ progress in their science or math courses. Additionally, the frequency for meeting is
not on a daily basis, which lessens the amount of time students learn, practice, and acquire
necessary skills to be successful in STEM courses and activities. Lastly, MESA advisors voiced
that is not enough time during lunch or after school for students to accomplish the hands-on
activities they learned from their professional development workshops. Teacher 3 stated,
Well, we've got a lot of activities that require a good bit of time, at least more than one
day at a time. It would be good if we had more bite sized activities. When we meet for
an hour a week, we can start and finish that in that time.
Motivational Support
Research suggested that educationally disadvantaged students need motivational support
to persist in STEM fields (PCAST, 2010). Key components of successful STEM programs,
which target motivational support include comprehensive long-term support throughout students’
educational careers (Cabrera & La Nasa, 2001; Swail et al., 2012). To address the motivational
challenges that students face, MESA provides incentive awards through competitions at the
secondary level.
In order to support a comprehensive long-term system most MESA schools’ programs are
housed at universities with connections to faculty members to expose and motivate students to
persist through the pipeline. Competitions are held at the designated university to increase
students’ exposure to the college campus. Additionally, MESA advisors learn through their
professional development training how to integrate a multitude of study skills needed for STEM
within the hands-on activities. Teacher 3 expressed,
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Many of the students re-enroll in MESA because they begin to understand the benefits
from what they are learning through the hands-on activities, and skills needed to succeed
in their math and science courses. Their success makes them feel like they’re leaders.
However, it is necessary for the students to remain in the program for a length of time in order to
begin understanding the connections and to develop the self-motivation to persist.
Social Support
According to research, educationally disadvantaged students need academic support as
well as strong social support from their peers and parents (Cabrera & La Nasa, 2001). When
parents are educated about the importance and benefits of college, and the students’ peers share
the similar educational goals, they are more likely to progress into postsecondary education
(Corwin et al., 2005; Perna, 2002). STEM outreach programs that provide a strong social
network support allow for educationally disadvantaged students to motivate and influence each
other to persist in STEM (Cabrera & La Nasa, 2001).
Based on the quantitative and qualitative data gathered, MESA encouraged the site
programs to integrate social interactions and events between peers and advisors; however, a
systematic format to address social barriers to improve networking is not consistently
implemented at all MSP sites. Advisors realize that the social aspect needs to be strengthened.
Since the lunch and after-school programs do not meet on a daily basis, building that
camaraderie is a slower process. Teacher 4 explained that in their last workshop, the advisors
started addressing new ways to increase the social component.
In our exercise tonight, we were trying to improve the retention rate. One of the other
advisors in my group suggested things like recognizing birthdays and having more
awards, etc. In order to improve the camaraderie of the group, improving the social
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aspect of it. That was something I really hadn't considered. Sounds like a good idea.
(Teacher 4)
This quote reveals that some school sites are slower in building the social component, and some
of the advisors are struggling with balancing both the social and academic portions within their
club meeting time.
Network Support
By providing a strong social support system, research indicated that it builds a healthy
foundation for a strong network within the STEM community (Corwin et al., 2005; Perna, 2002).
Literature also suggested that a built-in network allows for educationally disadvantaged students
to feel supported, encourages accountability, and exposes them to a broader selection of STEM
opportunities (Cabrera & La Nasa, 2001). MESA helps to connect students to peers with similar
interests in college and STEM careers through field trips and events, as well as educators with
common professional goals and values. Professional development is offered to support MESA
teachers to collaborate and learn new techniques to teach math and science that will spark middle
school students’ interest in STEM activities and courses.
According to both the survey and participant interview responses, networking is strong
among the advisors. The USC MESA coordinators plan during the summer to create the advisor
meeting schedule and conference dates throughout the year. However, the advisor positions are
strictly voluntary. MESA funds teacher release days, field trips, competitions, events, and
supplies for hands-on activities, but there is no additional compensation for teacher time. During
the focus group interview, the researcher asked the participants why they decided to become
MESA advisors given that there is no monetary compensation. Several advisors responded that
they looked up the program, reviewed MESA’s missions and values and believed that it aligned
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with their professional values. They also saw that there was a gap between the needs of
educationally disadvantaged students and what public education has to offer for support.
Networking amongst students and parents at other MESA schools is limited to MESA
day academies, which give students a chance to meet and compete with like-minded students.
Networking opportunities are only offered one time in the fall and spring semesters.
Additionally, space is limited to a total of 25 MESA teams and is offered on a first-come first-
serve basis. Some MESA school sites that are located nearby will coordinate on their own to
allow for their students to network and collaborate on the MESA projects, activities and
competitions.
Funding Support
Based on the participant responses during the interview sessions, MESA advisors
discussed how funding affects the extent of how comprehensive the support can be in the areas
of academics, student motivation, social development, and building a larger network. The
researcher found that the site funding support is correlated to the number of students
participating in the program. Programs that can assist a larger variety of students will receive
more funding. Since MESA targets educationally disadvantaged students who have an interest in
STEM, the criteria significantly lessens the amount of students who fit and would benefit from
this type of program. Students who have an initial interest in STEM will more likely persist.
Teacher 2 supported this statement by asserting, “A lot of my kids that are into math and science,
those are the ones that really stick into the program. They find the passion in it.” Therefore,
even though all students can benefit from the skills learned in the MESA program, not all
students have a desire to participate in science and math activities and courses.

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Summary
Chapter four reviewed the findings, analysis, and interpretation of the data collected for
this study. Data collected at the USC-MESA program assisted the researcher to answer the four
guiding research questions for this study. The researcher compared this study’s framework, the
body of literature, and supports in place under the MESA program to determine whether there is
alignment with the research-based features of an effective STEM outreach program. It was
decided that MESA is stronger in supporting educationally disadvantaged students in the areas of
academics and networking, whereas a more systematic approach is needed to enhance the social
support. Although the advisors agreed that the students are motivated in the STEM activities and
events, the researcher was not able to directly measure student motivation. Through
triangulation, the researcher determined that following recurring themes indicate barriers to
ensuring that the MESA program is effectively supporting educationally disadvantaged students
in increasing engagement and encourage persistence in the STEM pipeline.
1. Funding – Since 2002, MESA funding has decreased 55% (MESA, 2016). This has
affected the comprehensiveness of the support provided in all areas.
2. Marketing – Although MESA has been a longstanding program since 1970, stakeholders
such as teachers, parents, and students do not fully understand what the program has to
offer. This hinders the number of students recruited.
3. Advisor Support and Retention – Site-based mentorship for new advisors is needed to
ensure they are successful in implementing and maintaining the program. Although the
USC-MESA coordinators support advisors by visiting the school sites, there are an
insufficient number of personnel to provide on-going, consistent mentoring for all
advisors.
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4. Site-Based Participation Requirements – Some school sites require students to maintain a
passing GPA in order to participate. The students targeted for the MESA program are
already disadvantaged due to failing grades and lack of support from their environment.
Grade requirements create an additional barrier that keeps the students from the vital
support needed to remain competitive with their peers in STEM.
Chapter Five will summarize the findings, discuss the implications, and suggest
additional research for how the MESA program can implement the missing components of the
research-based features of effective programs to build a successful program that will allow all
educationally disadvantaged students to persist through the STEM pipeline.

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CHAPTER FIVE: DISCUSSION
Chapter Five is an overview of the study, and includes a summary of the significant
findings from Chapter Four. In addition, this chapter presents a discussion of future implications
to the STEM field, and concludes with recommendations for areas requiring further studies as it
relates to answering the research questions that examine the effectiveness of increasing
educationally disadvantaged students’ interest in STEM.
Overview of the Study
Background
The meta-body of literature concluded that America’s position in science, technology,
engineering and mathematics (STEM) is at a steady decline when compared to rising global
nations such as Finland, China and India (National Academy of Sciences, 2007). Possible
reasons for the decrease points to a lack of underrepresented minority and female representation
in STEM education and the STEM workforce. Although the U.S. Census Bureau predicts that
educationally disadvantaged subgroups, such as Hispanics, will increase to become the majority
by 2050, their presence in STEM jobs does not reflect their numbers proportionally (Museus et
al., 2011). Moreover, females have increased their representation in the workforce now that
families require dual incomes to survive, yet they have difficulty competing with their male
counterparts, particularly in the STEM field (Espinosa, 2011). Both educationally disadvantaged
populations and females are susceptible to falling through the cracks along the educational path
towards earning a STEM degree and entering the field. Researchers refer to this as the leaky
pipeline model, where the number of females and underrepresented minorities lessens as they
move from elementary and secondary education to higher education and STEM occupations
(Clark Blickenstaff, 2005; Cannady et al., 2014; Metcalf, 2010). Past study results attributed the
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loss at each juncture to students’ lack of interest at the elementary level, limited access and
positive exposure to more complex math and science courses at the middle and high school
levels, and the indecisiveness to commit or “declare” a STEM major during the first year of
undergraduate school (Adelman, 2006; Berryman, 1983; Bonus-Harnmarth, 2000; Cannady et
al., 2014; Hilton & Lee, 1988; Maltese & Tai, 2011; McKnight, 1987; Oakes, 1990; Strayhorn,
2011).
In hopes to counteract the leaky pipeline effect, the US earmarked funding to prepare,
support, and retain underrepresented populations in STEM education and the STEM field
(Gonzalez & Kuenzi, 2012). Founded in 1970, the Mathematics, Engineering, Science and
Achievement (MESA) program was one of the first organizations to establish a research-based,
long-term comprehensive support system to remove educational, social, financial, and gender-
type barriers for educationally disadvantaged students so that they have a chance to persist in
STEM. MESA counters these deficits in public education by including the following supports:
• intervention as early as middle school
• integration of study skills in high interest, hands-on activities, competitions, and field
trips
• participant exposure to college campuses and students with a declared STEM major
• teacher professional development and networking
Purpose of the Study and Research Questions
The purpose of this study is to explore the effectiveness of the MESA Schools Program
(MSP) on the retention of educationally disadvantaged middle school students in STEM
activities and courses. The intent of this study was to identify the key elements that contribute
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toward a successful STEM outreach program. The following research questions served as a
framework that guided this study:
1. How is the Mathematics, Engineering, Science, and Achievement (MESA) outreach
program preparing teachers to support educationally disadvantaged middle school
students in Science, Technology, Engineering, and Mathematics (STEM) activities and
courses?
2. How do MESA teachers perceive the impact of the MESA program in the retention of
educationally disadvantaged students in STEM activities and courses?
3. What resources are utilized in the MESA program to prepare and support educationally
disadvantaged middle school students in STEM activities and courses?
4. How do teachers perceive the effectiveness of the MESA program in increasing the
persistence of educationally disadvantaged students in STEM activities and courses?
Review of Methodology
The researcher conducted the study using an explanatory sequential mixed-methods
research design. Survey questions were disseminated to the targeted population of MESA
teacher advisor participants using SurveyMonkey
™.
Following the survey, the researcher used
the participant responses to design an interview question protocol that honed-in on particular
areas of MESA’s support program that required more intricate explanations. Once the data was
collected and processed, the researcher analyzed the results to determine the overarching themes
related to the MESA teacher advisors’ perceptions of the program’s effectiveness in preparing
and supporting educationally disadvantaged middle school students in STEM activities and
courses. The qualitative data results supported the participants beliefs through highlights of
specific examples that showed how MESA supported the students, as well as offered rich
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descriptions of the teacher advisor’s personal experiences of the ongoing support they have
provided to educationally disadvantaged students. Through triangulation, it was determined that
the MESA program contains supports for educationally disadvantaged students that were
synonymous to the body of literature as well as the framework for this study, however, there are
areas that require strengthening.
Summary of Findings
The process in exploring the guiding research questions began with a review of the body
of literature about underrepresented minorities not persisting in STEM. Then the researcher
logistically mapped out the methodology in which to conduct the study. In the analysis portion,
the data were processed to identify patterns and emerging themes from the surveys and
interviews. In this chapter, a discussion of the findings will be used to determine implications
for the future.
This study investigated whether the MESA teacher advisor participants perceived the
MESA Schools Program (MSP) as being effective in increasing the persistence of middle school
students in STEM activities and courses. Based on the survey responses, MESA advisors
perceived the program to be effective in influencing students to persist in STEM. The majority
of the survey results indicated that the advisors’ responses were categorized under the “agree”
rating of the five-point Likert scale. The participants’ interview responses offered elaboration as
to why the teacher advisors felt this way, and which support components of the MESA program
aided in its effectiveness.
The participant interviews provided the researcher with ancillary findings that would not
otherwise have been discovered using the survey instrument alone. The MESA advisor
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responses uncovered additional emerging themes that painted a clearer picture of the types of
barriers that inhibited the program from reaching its maximum potential.
This research study revealed that the strongest components of the MESA program are the
long-term academic support for both students and teachers, and MESA’s sophisticated
networking system with college, community, and STEM industry resources. Moreover, given
that MESA has endured funding cuts upwards of 55% since 2002, MESA advisors continue to
believe that the supports offered are essential to educationally disadvantaged students’ ability to
persist in STEM (MESA, 2016). Overall, the MESA program, in its entirety, is a strength for the
simple fact that its sole purpose is to understand and remove barriers that impede educationally
disadvantaged students from successfully competing with their peers nationwide and globally.
Despite the dwindling of resources, MESA continues to use innovation and collaboration to
positively influence students in STEM.
MESA Alignment to Research and Framework
According to the research, underrepresented minorities show success in persisting in
STEM when they receive ongoing academic support at the early stages of their educational
career (Gándara & Bial, 2001; Schultz & Mueller, 2006; Swail et al., 2012). Moreover, when
underrepresented minorities incorporate a network of supporters with like-minded educational
and professional goals, they are more likely to persist in their STEM courses and activities,
declare a STEM college major, and ultimately work in the STEM field (Cabrera & La Nasa,
2001; Schultz & Mueller, 2006). The MESA program strongly corroborates with both the body
of STEM literature as well as this study’s framework in the areas of academic support and
network support.
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Academic support. According to the data in this study, teacher advisors believe that the
academic support component of the MESA program contributes to its effectiveness in
encouraging educationally disadvantaged middle school students to persist in STEM. MSP
aligns with the research-based literature by providing early intervention at the middle school
level. MESA’s goal for the middle school program is to spark students’ interest in STEM by
creating positive experiences through high-interest activities, field trips, and MESA events. In
turn, the continuous exposure to a variety of non-threatening experiences in STEM improves
their confidence to persist in their science and math courses, which increases the likelihood they
will continue to pursue STEM-based activities in their high school and post-secondary years
(Cabrera & La Nasa, 2001; PCAST, 2010; Schultz & Mueller, 2006). Teachers valued the
professional development coordinated and presented by the USC-MESA directors. The
uninterrupted workshop time allowed the advisors to personally explore the hands-on activities,
process and make sense of their findings, and plan how to effectively transfer what they have
learned to their MESA students during club time.
Network support. MESA teacher advisors also perceived the program’s network
support as a vital component in effectively supporting educationally disadvantaged students in
STEM. According to the interview responses, teachers believed that the available opportunities
allowed the MESA students to investigate and experience the limitless avenues they could
pursue within the STEM field. In regards to teacher networking, USC-MESA also includes
numerous opportunities throughout the school year for advisors to exchange ideas and work in
partnership with like-minded individuals during their scheduled professional development
sessions. During the professional development sessions, the advisors shared ideas about how
they configured the MESA program at their schools in order to overcome program/site conflicts
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and meet the needs of their particular student population. Advisors appreciated the new ideas,
which helped them to re-think how they could improve upon their own program in order to meet
the needs of their unique group of students.
Program Considerations
MESA advisors viewed the current program to be highly successful in supporting
educationally disadvantaged middle students. The researcher encouraged the advisor
participants to share their opinions of how the MESA program can be even more effective in
including more students and supporting them comprehensively. Overarching themes that arose
from the findings included modifications to the current academic support, a systematic social
support component, funding impacts to several program areas, and student/teacher recruitment
and retention.
Academic support. The study results indicated that although MESA advisors believed
the program to be essential in encouraging educationally disadvantaged students to continue
pursuing STEM courses and activities, the STEM skills learned during the club sessions do not
always align and transfer to the content students are currently learning in their science and math
courses. Advisors who have MESA student participants enrolled in their science and/or math
courses are able to monitor their application to content during class time. However, the
transference for students who have non-MESA advisors as science and math teachers cannot be
guaranteed. Moreover, the frequency of the MESA club meetings are not daily, which reduces
the amount of time for students to learn and process the necessary STEM skills needed to impact
their confidence in their science and math courses. Lastly, MESA advisors expressed their
concern about the lack of time needed to complete a hands-on-activity within one club session.
Although the majority agreed that the activities learned from their monthly professional
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development are high interest and popular among the student participants, they find it
challenging to complete the entire activity in one club session. Advisors also shared that when
the activities are stretched over more than one club session, student engagement decreases. They
believed that the activities students can complete within one meeting satisfied their need for
immediate results and timely feedback.
Social support. One of the requirements for MSP is to re-enroll students in the MESA
program throughout their middle school years in order to build the camaraderie and social
cohesiveness. Teachers agreed that the long-term commitment helped create a sense of
community and peer support. However a systematic format to address social barriers to improve
networking is not consistently implemented at all MSP sites. With the largest percentage of
MESA advisor participants in the 0-2 year category, it is difficult to create the desired social
climate when the teacher advisor turnover rate is high. Advisors realize that the social aspect
needs to be strengthened. Based on the interview responses, the limited amount of time allotted
for students to meet weekly in their clubs slows down the process for incorporating activities that
help build an adequate social support system. Moreover, the once-a-week meetings limit the
balance of both academic and social components of the program in each session.
Funding impacts. The intensive funding cuts from MESA have affected all of the
essential support components in the program. In the area of academic support, the MESA
program works best as a foundational program that is embedded in all curricular areas, such as a
learning community. When the MESA program is more extensive, there are increased
opportunities for a larger portion of educationally disadvantaged students to be exposed to
STEM-based content through language arts, social studies, and other non-STEM subjects.
However, with the cuts in grant money, schools are hesitant to provide the in-kind dollars that
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would be needed to fund multiple full-time employees in order to maintain an integrated STEM
learning environment. The funding that is currently available is sufficient in maintaining a
highly effective program specifically for the students who are already inclined to persist in
STEM courses and activities.
Funding availability may also hinder the longevity of teachers holding the advisor
positions. According to the interview responses, new MESA teachers felt overwhelmed with
maintaining a healthy balance between their teaching duties and the responsibilities as a MESA
club advisor. The current MESA advisor position is strictly voluntary with no stipend available
for preparation and teaching time during club hours. Although several advisors expressed their
strong affinity to MESA’s mission of preparing and supporting educationally disadvantaged
students in STEM, they felt compelled to relinquish their positions in less than five years in order
to stay abreast in their regular assignment workload.
The reduction in MESA funding since 2002 has also impacted student networking
opportunities, field trips, and events. In order to preserve the program’s integrity, MESA
chooses to scale back, or modify traditional events and fieldtrips rather than eliminate them
completely. Field trips and events are prime opportunities for the MESA students to network
and build a support system with like-minded peers from other USC-MESA school sites. Since
limited opportunities to socialize weakens the networking-support component, some MESA
advisors have chosen to coordinate meetings and events with neighboring USC-MESA school
sites in order to boost opportunities to interact and collaborate. The partnerships formed among
MESA, local businesses, and leading STEM organizations play an important role in field trip and
event opportunities for the MESA students, and this can change year-to-year. The more
seasoned MESA advisors stressed the importance of being flexible to program changes based on
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the annual budget. These funding constraints are no different from the current issues public
schools face in preserving major components of their school-wide general program; however, the
funding resources do not match America’s push to prioritize STEM education nationwide.
Advisor and student recruitment. Under the ancillary findings, the researcher
discovered marketing as an area requiring strengthening to improve the recruitment of potential
students and advisors. The advisors explained that both the students and teachers know that
MESA is a long-standing program focused on math and science, but they do not have a clear
understanding of its purpose, goals, activities, and opportunities. The advisor participants shared
their experiences of trying to recruit non-STEM related teachers who showed interest in
becoming MESA co-advisors, but were intimidated because they did not feel their knowledge in
the sciences and math was adequate. Participants further clarified that the qualifications to be a
MESA advisor does not necessarily require teachers to be knowledgeable in math and sciences,
and the step-by-step professional development supports teachers to properly conduct the hands-
on activities. Advisors believed that the inclusion of non-STEM teachers during club meetings
conveys the message to students that STEM resonates throughout all curricular areas, and
acquiring other skills, such as research writing and learning about STEM-related literature, are as
equally important to ensuring they are well prepared to persist in the STEM field.
Advisors shared that some students joined the program because a friend encouraged them
to attend the recruitment meeting, which was also the first time they learned about the MESA
program. Advisors added that the majority of their students would have joined MESA earlier if
they knew what they know now. MESA advisors believe that the limited marketing to both
eligible students and their parents vastly decreases the potential number of recruits who would
greatly benefit from the program’s supports. STEM education has grown to be trendy in schools,
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and recently, new after school programs are advertising activities that MESA already has in
place such as robotics and coding. Advisors believed that if stakeholders are aware of what
MESA has to offer, more students will be interested in joining on their own accord.
Advisor retention. The ancillary findings also determined that the new MESA advisors
are in need of additional support through on-site coaching and mentorship to ensure the program
is implemented properly and to prevent burnout. Advisors valued the workshops, conferences,
and periodic site visits by the USC-MESA directors; however, they felt that an on-site teacher
coach or mentor would give them the ongoing, daily support they needed to maximize their
program and help them to grow as STEM leaders.
Site-based participation requirements conflict with MESA. Although MESA does
not require students to maintain a minimum grade point average (GPA) for participation, some
school sites require passing grades to participate in any club. Grade requirements create an
additional barrier that keeps educationally disadvantaged students from the vital support needed
to remain competitive with their peers in STEM. MESA advisors who are allowed to accept all
eligible participants manage the program under the persistence model, where students are
encouraged to feel successful through perseverance. During the monthly advisor workshop
meetings, teachers have discussed ways they have overcome this barrier, yet it requires
negotiation and compromise with the school site administrators, and the outcome may or may
not be favorable for the MESA program. This lack of uniformity at all USC-MESA school sites
creates an imbalance of participants, delineates from MESA’s intended mission and goals, and
allows for potential students to leak out of the STEM pipeline.

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Limitations to the Study Findings
Although the MESA advisors indicated on the survey results that they agree that the
program influences students’ motivation to continue participating and pursuing STEM activities
and courses, the study itself was not able to accurately measure student motivation. Limitations
to the research did not allow for students to participate in the study. Therefore, the data results
are only based upon the teachers’ perceptions rather than the students’ perceptions.
Conclusion of Findings
As previously mentioned, the MESA program continues to be a highly effective program
in encouraging educationally disadvantaged middle school students to persevere in STEM
education. MESA uses updated research to monitor the types of barriers students face, as well as
brainstorm innovative methods to enhance the existing support provided for their student and
teacher participants (MESA, 2016). In this study, the researcher made recommendations for how
future MESA programs can augment the effectiveness of the current support provided for certain
areas.
Increase Site-Based MESA Advisors
The study revealed that the MESA teacher advisors felt overwhelmed with the
responsibilities of implementing the MESA program while maintaining their regular teaching
duties. It is suggested that each school site recruit at least two teachers, preferably one new and
one experienced, to share the responsibilities of the MESA advisor position. Partnerships can
foster healthy dialogue about program logistics, provide immediate feedback while reflecting
about the hands-on activity lessons, and boost teacher morale. Having two MESA advisors also
supports the mentoring/coaching model for advisors who are new to the position. If teachers are
willing to commit to the position for at least two years, they can recruit a new teacher and
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mentor/coach for one school year before deciding to step down. Additionally, encouraging
STEM and non-STEM teachers to partner promotes integration of subject areas. Teachers with
expertise in non-STEM subject areas can add to the bank of essential skills by showing students
how to review and analyze STEM-based literature and write research reports using scholarly
language. Both STEM and non-STEM skills are necessary for all jobs in the STEM field.
Encourage the MESA Period Format
This study also uncovered the constraints of implementing the MESA program in a club
format. Issues that surfaced included limited time to thoroughly conduct the hands-on activities
and build the social aspect, less transference of skills learned to math and science courses if
subject teachers are not the MESA advisors, and difficulty in monitoring students’ academic
progress. Although MSP already offers the option to implement the program as a course, the
researcher recommends establishing more MESA periods rather than MESA clubs. Students
who are enrolled in a MESA STEM-based course have increased opportunities to learn the
necessary STEM skills, and can immediately apply what they have learned to their standards-
based curriculum. Moreover, students meet daily rather than weekly, which allows the teacher
advisor to incorporate more social activities into their schedule. Lastly, establishing a MESA
period fosters cohesiveness in monitoring students’ academic progress. The MESA teacher
advisors can ensure students are properly implementing the skills learned, and provide follow-up
intervention through small group instruction or one-to-one tutoring during class time or after
school.
Provide Stipends to Advisors
The academic component of the MESA program, in club format, can also be categorized
as a supplemental intervention to support educationally disadvantaged students in their math and
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science courses. Opportunities for teachers to earn supplemental pay may help reduce the
turnover rate and improve program consistency. The commonality among the teacher advisor
participants is their passion and dedication for ensuring educationally disadvantaged students are
well supported and positively encouraged to persist in STEM. They choose to go above and
beyond their regular teaching duties, regardless of the money, which is why they are MESA
advisors today. However, by providing stipends for mentoring/coaching, attendance to field trips
and events, preparation time, and during club time, reinforces the message that their efforts are
valued. Seasoned MESA advisors, who have been in the position for longer than two years,
possess valuable data about how MESA has changed over time, which supports contribute to
MESA success, and which components require modifications to better support students.
Increase Marketing of the MESA Program
During the focus group interview, the majority of MESA advisors agreed that they did
not know much about MSP until they researched the website and attended the first advisor
meetings. Advisors also shared that participant recruitment is challenging due to students’ lack
of prior knowledge about what MESA has to offer. Based on this study’s results, the researcher
recommends that MESA collaborate with school site administrators and staff to increase
advertising and marketing to key stakeholders such as administrators and teachers, parents, local
community partners, and students. The purpose for holding multiple information sessions is to
improve the knowledge base about MESA’s mission and goals, as well as dispel misconceptions,
specifically for teachers and administrators, about how the school can combine their efforts to
ensure the program is comprehensive and integrated across the curriculum. Referring back to
increasing the amount of site-based MESA advisors to a minimum of two, the additional
manpower can help inform and educate a larger pool of stakeholders.
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Limitations
Prior to conducting the study, the researcher noted the following limitations in Chapter
One:
• Time availability and distance feasibility.
• The ability to gain access to successful STEM outreach programs was limited.
• Amount of time needed to collect and analyze the data to determine commonalities of
successful STEM outreach programs.
• Self-report responses may not be indicative of true responses leading to issues of
reliability and validity of data collected.
• Small sample size and self-report responses of minorities and females participating in
STEM outreach programs could reduce the generalizability of the findings for this study.
After conducting this research study, the overarching limitation included the researcher’s
inability to access teacher advisor participants in the Los Angeles Unified School District
(LAUSD). During the researcher’s initial meetings with the USC-MESA directors, it was
identified that the LAUSD MESA middle schools program struggled the most in effectively
supporting educationally disadvantaged students in STEM activities and courses. Due to the
time frame allotted to conduct this study, the researcher was unable to complete the IRB
processes for both LAUSD and USC. However, the researcher was granted access to all USC-
MESA middle school sites in this study except for LAUSD.
There were also limitations in relation to scheduling conflicts for conducting the
interviews in a preferred amount of time, as well as the desired setting. The focus group
interview took place during lunchtime in a teacher conference room at the Natural History
Museum in Los Angeles. The room was partitioned for the researcher to conduct the focus
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group interview, however, the noise level and informal conversations among the non-participants
created distractions. The USC-MESA directors were not involved in the group interview.
However, they walked around the room talking to non-participants and prepared for the second-
half of the workshop session. The directors’ presence may have inhibited the focus group
participants’ desire to fully express their true perceptions about the effectiveness of the MESA
program. However, each participant was able to continue the interview with the researcher in a
location where they may have felt more comfortable to authentically explain their perceptions
and beliefs in uncensored detail. Moreover, the amount of time scheduled for the focus group
interview was less than one hour. For the individual interviews, scheduling conflicts resulted in
two interviews conducted over the telephone. This inhibited the researcher’s ability to use body
language as added data to inform the study.
A natural limitation to this study included possible researcher biases. Since the
researcher is the main instrument in collecting data, all qualitative research studies are threatened
with possible biases (Merriam, 2009; Patton, 2002). Interpretation of the results can vary based
upon the lens the researcher utilized. However, the researcher constantly used the “peer review”
method with two other researchers in order to check biases and maintain credibility (Miles et al.,
2014).
Extending the amount of time allotted for collecting both the quantitative and qualitative
data may also have skewed the results. The MESA teacher advisors took the survey and
participated in the interviews between the months of August and October. The researcher
speculates that the advisors’ perceptions of MESA’s effectiveness in supporting educationally
disadvantaged students could possibly change depending upon the time of school year. For new
MESA advisors who participated in this study, their responses were based on what they have
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experienced up to the date of the survey and interview. After eight months of elapsed time, the
new teachers would have spent more time with the students, and participated in more MESA
activities, which would have provided them with a better understanding of the supports they
consider effective. Moreover, teacher morale changes throughout the school year. It is quite
possible that both the new and seasoned advisors’ responses could vary based on the work-
related stresses at that given time. Collecting the advisors’ responses at multiple points
throughout the school year would have provided an even more accurate measure of their
perceptions about MESA’s effectiveness in supporting educationally disadvantaged middle
school students.
Implications for Practice
The findings in this research study carry substantial implications for future policies and
practices. The existing body of literature provided ample data to support the reasons why it is
imperative to establish a variety of STEM outreach programs at different junctures in students’
educational careers, such as middle school, high school, and postsecondary. However, there was
a lack of substantial evidence in the claim that STEM outreach programs are effective in
ensuring underrepresented minorities and females persist through the pipeline and thrive in the
STEM field (Berryman, 1983; Strayhorn, 2011). This study’s findings specifically examined
one particular long-standing STEM outreach program, MSP, to determine whether the supports
provided were effective in ensuring educationally disadvantaged students persist in STEM.
These findings fill the void in the meta-body of STEM literature by explaining which supports
are vital to influencing students to persist, and how the supports can be improved upon to
increase the number of students entering and enduring through the pipeline. Policymakers
continually face the issues of how to successfully recruit females and minorities to STEM, and
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which strategies to implement in order to retain females and minorities in STEM. Through the
MESA advisor participants’ responses, detailed explanations for low recruitment and student
participation fallout were addressed, and suggestions were made on how to improve MESA
student membership and advisor longevity.
The need to monitor and improve the effectiveness of STEM outreach programs within
the US is critical in making sure the ratio of workers in the STEM field accurately match our
nation’s ethnic representation. Excluding subgroups, such as the African American, Latino,
Native American, and women populations, will undeniably limit the amount of STEM workers
needed to meet current and future demands (Eagan et al., 2014). Globally, this study is pertinent
to ensure that US remains competitive with countries that have maximized their resources in
order to advance their position as leaders in STEM. As these countries take the lead, their
economic standing strengthens, which will place the US in an even more vulnerable state.
Recommendations for Future Study

Investigating the effectiveness of the USC-MESA program for middle school students
can be approached from various angles. This study examined MESA through the perceptions of
the program’s teacher advisors. Their daily interactions with educationally disadvantaged
middle school students provided pertinent information about the essential components they
believe is necessary to effectively prepare students to compete with their nation-wide and global
peers in the STEM field. However, experiences and perceptions from other key stakeholders
such as the current student participants, past participants, and parents of MESA students, can
yield a more comprehensive understanding of MESA’s impact on students’ persistence. Based
on the findings in this study, the following are recommendations for future research in the MESA
middle school program, as well as other STEM outreach programs:
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1. MESA has been identified for its excellence in supporting educationally disadvantaged
students since its establishment in 1970. Conducting a study to compare the current
program to the components that were in place prior to the funding cuts in 2002 can reveal
how MESA intended to implement a comprehensive support system for student success.
2. MESA offers a variety of programs that cater to its specific population. This study
investigated the MESA Schools Program (MSP), which focuses on middle and high
school education. It is recommended for future studies to investigate all MESA
programs: MESA Schools Program (MSP), MESA College Program (MCP), MESA
Community College Program (MCCP), and MESA Engineering Program (MEP), to
determine the cohesiveness and seamlessness in support when students transition from
one program to another.
3. A follow-up study should investigate a cross-comparison in program fidelity at each
MESA school site. This study can determine which program components require
modification in order to best support the site’s unique student population and school
climate, and which components should be standardized to ensure all MESA students are
well-prepared to persist in STEM and compete with their peers.
4. When our nation prioritized STEM education as urgent, the number of STEM outreach
programs increased dramatically. Future studies should compare MESA’s programs to
other STEM outreach programs to identify common supports that contribute towards the
makings of an effective program, and unique features that distinctly service students for
specific purposes and desired outcomes.

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Conclusion
This study explored the effectiveness of USC-MESA’s MSP program in encouraging
educationally disadvantaged middle school students to persist in STEM courses and activities.
The literature reviewed concluded that STEM outreach programs at the middle, high, and
postsecondary school junctures are crucial to students’ perseverance through the STEM pipeline
(Berryman, 1983; Strayhorn, 2011). Outreach programs are needed in order to ensure an ample
amount of skilled workers will be qualified to fulfill future positions in the STEM field (Capraro
et al., 2013; Tyson et al., 2007). With increased accountability measures and funding
fluctuations, it is pertinent to verify which supports are successfully meeting the need, and which
components require updating and/or modifications. MESA teacher advisors’ perceptions and
beliefs were vital in this study for examining whether the supports are meeting MESA’s intended
outcomes, and if additional barriers that were not mentioned in the literature review currently
exist. Future studies can further investigate MESA’s effectiveness by showcasing the MESA
students themselves. Providing a platform for student participants to voice their perceptions will
allow researchers to accurately measure their self-efficacy and motivation levels in relation to
their persistence in STEM. Additionally, there are so many aspects of STEM outreach programs
that still require further exploration. It is the hope that this study, as well as future studies, will
continue to move America one step closer to closing the achievement and opportunity gaps
between our underrepresented populations and the STEM field.

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191

Appendix A: Information Sheet
University of Southern California
Rossier School of Education
3470 Trousdale Pkwy, Los Angeles, CA 90089

INFORMATION/FACTS SHEET FOR EXEMPT NON-MEDICAL RESEARCH

MATHEMATICS, ENGINEERING, SCIENCE, ACHIEVEMENT (MESA) AND STUDENT
PERSISTENCE IN SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS
(STEM) ACTIVITIES AND COURSES:

THE PERCEPTIONS OF MESA TEACHER ADVISORS IN THE EFFECTIVENESS OF
INCREASING PUBLIC MIDDLE SCHOOL EDUCATIONALLY DISADVANTAGED
STUDENTS’ INTEREST IN STEM

You are invited to participate in a research study. Research studies include only people who voluntarily
choose to take part. This document explains information about this study. You should ask questions about
anything that is unclear to you.

PURPOSE OF THE STUDY
The purpose of this study will examine how effective the MESA program is in keeping students in
STEM.

PARTICIPANT INVOLVEMENT
Survey Participation: If you agree to take part in this study, you will be asked to complete an online
survey which is anticipated to take about 15 minutes. You do not have to answer any questions you do not
want to. Click “next” or “N/A” in the survey to move to the next question.

Interview Participation: If you agree to take part in this study, you will be asked to participate in a 30
minute audio-taped interview. You do not have to answer any questions you don’t want to; if you do not
want to be taped, handwritten notes will be taken.

ALTERNATIVES TO PARTICIPATION
Your alternative is to not participate. Your affiliation with MESA will not be affected whether you
participate or not in this study.

CONFIDENTIALITY
Any identifiable information obtained in connection with this study will remain confidential. Your
responses will be coded with a false name (pseudonym) and maintained separately. The audio-tapes will
be destroyed once they have been transcribed. In addition, the data will also be stored on a password
protected computer in the researcher’s office for three years after the study has been completed and then
destroyed.

The members of the research team and the University of Southern California’s Human Subjects
Protection Program (HSPP) may access the data. The HSPP reviews and monitors research studies to
protect the rights and welfare of research subjects.

When the results of the research are published or discussed in conferences, no identifiable information
will be used.
192

INVESTIGATOR CONTACT INFORMATION
Principal Investigator:
Dr. Pedro Garcia via email at pegarcia@usc.edu or phone at (805) 469-3377
Co-Investigators:
Rhonda Haramis via email at haramis@usc.edu
Jacob Jung via email at jacobjun@usc.edu
Nisha Parmar via email at npparmar@usc.edu

IRB CONTACT INFORMATION
University Park Institutional Review Board (UPIRB), 3720 South Flower Street #301, Los Angeles,
CA 90089-0702, (213) 821-5272 or upirb@usc.edu

193

Appendix B: Recruitment Letter

Dear Participant,

My name is Rhonda Haramis, and I am a doctoral candidate in the Rossier School of Education at
University of Southern California. I am conducting a research study as part of my dissertation, which
examines the effectiveness of Mathematics, Engineering, Science and Achievement (MESA) Program on
the persistence of underrepresented populations in science, technology, engineering, and mathematics
(STEM) majors. You are cordially invited to participate in the study. If you agree, you are invited to
complete an online survey that contains multiple-choice questions.
The online survey is anticipated to take no more than 15 minutes to complete. Depending on your
responses to the survey and your availability, you may be asked to interview via Skype or in-person. The
interview is voluntary, and anticipated to last approximately fifteen minutes and may be audiotaped.
Participation in this study is completely voluntary. Your identity as a participant will remain confidential
at all times during and after the study.
If you have questions or would like to participate, please contact me at haramis@usc.edu.

Thank you for your participation,

Rhonda Haramis
Doctoral Candidate - Rossier School of Education
University of Southern California

194

Appendix C: Consent Form
Consent to Participate in a Research Study

Subject’s Name: _________________________________ IRB Study #APP-16-01860

You are being asked to participate in a research study. A research study is how scientists (doctors, nurses
and other professionals) try to understand how things work and gain new knowledge. A research study
can be about how the body works, what causes disease, how to treat diseases, or what people think and
feel about certain things. Before you decide whether you will participate in this research study, the
investigator must tell you about:

(i) the purposes of the research study, the activities that will take place – these are called
procedures, and how long the research will last;
(ii) any procedures that are experimental (being tested);
(iii) any likely risks, discomforts, and benefits of the research;
(iv) any other potentially helpful procedures or treatment; and
(v) how your privacy will be maintained.

Where applicable, the investigator must also tell you about:

(i) any available payment or medical treatment if injury or harm occurs;
(ii) the possibility of unknown risks;
(iii) situations when the investigator may stop your participation;
(iv) any added costs to you;
(v) what happens if you decide to stop participating;
(vi) when you will be told about new findings that may affect your willingness to participate; and
(vii) how many people will be in the study.

If you agree to participate, you must be given a signed copy of this document and a copy of the approved
consent form for this study written in English.

You may contact Rhonda Haramis at haramis@usc.edu any time you have questions about the research or
about what to do if you are injured. You may contact the Institutional Review Board, at 323-223-2340 if
you have any questions about your rights as a research subject.

Your participation in this research is voluntary (your own choice), and you will not be penalized or lose
benefits if you refuse to participate or decide to stop.

Signing this document means that the research study, including the above information, has been described
to you orally, and that you voluntarily agree to participate.

______________________________________ ____________________
Signature of Participant Date

_____________________________________________ ______________________
Signature of Legally Authorized Representative Date

_________________________/____________________ ______________________
Printed Name/Signature of the Witness Date
195

Appendix D: MESA Survey Questionnaire

196

197

198

199

200

Appendix E: Data Collection: Interview Protocol for MESA Teachers in K-12

Introduction
Thank you for indicating a willingness to participate in this study. I greatly appreciate you taking
the time to answer some of my questions. I anticipate this interview will take about an hour. Will this time
frame work with your schedule today? Before we get started, I would like to give you a general overview
of my study and give you the chance to ask any questions you might have about participating in this
study.
I am a doctoral student in the Rossier School of Education at the University of Southern
California (USC). As part of the dissertation process, I will be conducting interviews related to my line of
inquiry. The topic of my study will focus on understanding how teachers of the MESA Program feel the
outreach program benefits the underrepresented populations. Specifically, I am interested in investigating
how teachers view participation in MESA has influenced their students’ persistence in STEM at the
secondary education level. In order for me to conduct a thorough research study, I will be talking to
teachers who are affiliated with the MESA Program to learn more about their perspectives.
During the interview process, my role is strictly limited to being the researcher. This means that I
will not be evaluating or judging the answers you provide today. For the purposes of this study, you are
the expert in the field, and I will be learning from you. Also, I would like to reassure you that none of the
data I collect will be shared with other teachers on campus or with faculty/staff within the school district.
Your answers will be kept confidential for the sake of this study. At the end of the study, I would be
happy to provide you with a copy of an executive summary of the project if you are interested.
Finally, in order to ensure I accurately capture what you share with me, I have brought a digital
recorder for this interview. May I have your permission to record our conversation? Do you have any
questions about the interview process before we get started? If you don’t have any (more) questions, may
I have your permission to begin the interview?

201

Setting the Stage
To start off with, I was hoping to learn a little more about you.
How did you learn about MESA?
When did you first become affiliated with MESA at your school district?
What course(s) and grade level(s) do you teach as part of the MESA Program?
Interview Questions (Follow up questions are listed in italics)
1. Could you please explain why you chose to partner with MESA as a teacher within your school
district?
2. Could you please describe your personal experiences of being a MESA teacher?
a. What are the expectations of being a MESA teacher?
b. Can you discuss any supplemental opportunities that are uniquely offered through
MESA?
3. How well-supported do you feel by the MESA organization with regard to instructional
strategies/professional development?
a. How often do you meet for professional development through MESA?
b. In what ways could MESA have supported you more as a classroom teacher?
4. Based on your personal knowledge, could you please describe the types of support services that
are available to students through the MESA Outreach Program?
a. In your opinion, how does MESA work?
b. How does MESA support students to learn STEM?
5. What challenges do you believe underrepresented students face in STEM?
a. How do you feel participating in MESA equips students to deal with such challenges?
b. Have you observed any differences between students who have participated in MESA as
compared to those who have not?
6. What are the strengths and weaknesses of the MESA Program?

202

7. Do you feel MESA contributes to the persistence of underrepresented students’ in STEM?
a. If interviewee responds “yes,” ask: Can you discuss the nature of which MESA support
programs/workshops are particularly beneficial?
b. If interviewee responds “no,” ask: Can you elaborate on how/why you feel MESA didn’t
adequately prepare students for STEM success?
8. In your opinion, how do underrepresented students in MESA view themselves in STEM?
9. In your ideal world, what types of academic/social/emotional supports would be included in a
successful STEM outreach program geared toward supporting underrepresented populations?
10. Some people would argue that underrepresented are less likely to graduate from STEM majors.
What are your thoughts on the issue? Do you think MESA can help keep underrepresented
students in STEM fields?
Closing and Gratitude
Do you feel there is any additional information that you would like to add to our conversation
today that I may not have covered?
The information you shared with me today will be very helpful for my research study. I would
like to thank you for participating in this interview process. I appreciate your time and willingness to
share your experiences with me. If I have a follow-up question, would I be able to contact you by email?
Thank you again for participating in my study.
Special Considerations and Probing
Transitions. I would like to transition from ______ and ask about…. (Is there anything else you
would like to add before we transition?)
We have spent some time taking about ______, now I would like to shift to talk about _____
We are going to shift gears a bit…

203

Probing Statements/Questions. You mentioned ______ , can you tell me more about that…
Then what happened…
Can you give me an example…
How did that make you feel…
Can you elaborate on that…
Do you have anything else to add?

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Asset Metadata

Creator Haramis, Rhonda Dee (author)

Core Title Mathematics, Engineering, Science, Achievement (MESA) and student persistence in science, technology, engineering, and mathematics (STEM) activities and courses: the perceptions of MESA teacher a...

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 04/20/2017

Defense Date 03/28/2017

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

Tag education,educationally disadvantaged populations,Effectiveness of STEM programs,engineering mathematics,Latino students,Latinos,Mathematics Engineering Science Achievement,Mesa,MESA advisor perceptions of STEM,MESA teacher perceptions of STEM,middle school,middle schools,OAI-PMH Harvest,science technology,STEM,STEM and funding shortages,STEM and Greater Los Angeles public schools,STEM outreach programs,STEM pipeline,STEM support programs,underrepresented minorities,USC MESA

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Garcia, Pedro E. (committee chair), Casturida, Rudy M. (committee member), Escalante, Michael (committee member)

Creator Email rharamis@gmail.com,rhonda_haramis@yahoo.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c40-364787

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