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Latinas’ self-efficacy in computer science and potential factors undergirding their perspective

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Latinas’ self-efficacy in computer science and potential factors undergirding their perspective

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Content Running head: LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 1

Latinas’ Self-efficacy in Computer Science and Potential Factors Undergirding their Perspective
By
William Scott Sullivan
_____________________________________________________________________________
A Dissertation Proposal 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

August 2019

Copyright 2019 William Scott Sullivan

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 2

Tables of Contents
Abstract 7
Chapter One: Overview of the Study 8
Background of the Problem 8
Statement of the Problem 11
Purpose of the Study 13
Theoretical Framework 13
Importance of the Problem 14
Limitations and Delimitations 16
Credibility and Trustworthiness 17
Definition of Terms 17
Organization of the Study 18
Chapter Two: Review of Literature 20
Introduction 20
Masculine Culture 24
Stereotypes within the field 24
Variability within STEM 26
Hispanic cultural bias and stereotypes in STEM 27
Self-efficacy 31
Mindset 34
Intersectionality of Race, Gender, and Science Self-efficacy 35
Education 36
Course Access 37
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 3

Elective Courses 37
Early Experience 38
Chapter Three: Methodology 40
Introduction 40
Research Questions 40
Research Design and Methods 43
Sampling 43
Setting 43
Access/Entry 43
Instrumentation 44
Survey 44
Interviews 46
Observation 48
Data Collection Approach 50
Data Collection 51
Data Analysis 52
Chapter Four: Results 54
Introduction 54
Findings 55
Factors Undergirding SE of Latinas in CS 59
Role models 59
Environmental Factors 60
Early experience 60
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 4

Parent perception of computer science 62
Motivation 64
Chapter Summary 67
Chapter Five: Discussion of Findings 70
Discussion of Findings 70
Limitations 73
Implications of Practice 73
Conclusion and Future Research 75
References 77
Appendix A: IRB Approval Notice 89
Appendix B: Combo Youth & Parental Permission Form 92
Appendix C: Student Survey 96
Appendix D: Classroom Observation for Undergraduate STEM – COPUS 101
Appendix E: Observation Raw Data 105
Appendix F: Interview protocol 108
Appendix G: Student A Interview Transcript 110
Appendix H: Student B Interview Transcript 126
Appendix I: Student C Interview Transcript 142
Appendix J: Student D Interview Transcript 154
Appendix K: Student E Interview Transcript 161
Appendix L: Recruitment Script 168
Appendix M: HSLS:09 Student Questionnaire: Student Questionnaire 170

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 5

List of Tables
Table 1: Characteristics of Interviewees 51
Table 2: Student Survey: Section 2 Science Self-efficacy 55
Table 3: Descriptive Statistics 56
Table 4: Overall Self-efficacy between Hispanic and non-Hispanic students 56
Table 5: Independent Samples T-Test 56
Table 6: Mean summary table across grade-level 57
Table 7: Role Models 59
Table 8: Environmental Factors 61
Table 9: Motivation 64
Table 10: Observation protocol – Page 1 103
Table 11: Observation protocol – Page 2 104

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 6

List of Figures
Figure 1: Cheryan et al. 2017 model on Factors that influence women’s
underrepresentation in certain STEM fields 23
Figure 2: Gallup 2017: The gender gap between race/ethnicity 30
Figure 3: Gallup, 2017 Interest, confidence, and likelihood to work in CS across race. 58
Figure 4: Gallup, 2017Interested in CS by confidence in learning CS. 58
Figure 5: Observation Raw Data Page 1/3 105
Figure 6: Observation Raw Data Page 1/3 106
Figure 7: Observation Raw Data Page 1/3 107

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 7

Abstract

This study aimed at understanding the current levels of self-efficacy as well as explore the
contributing factors of high school Hispanic females currently enrolled in a computer science
(CS) course. Using a mixed method approach, the study found no statistical difference of self-
efficacy between Hispanic and non-Hispanic female students. When conducting qualitative
analysis, three emergent themes were found as potential contributing factors to their science self-
efficacy, motivational, environmental, and role models. Of the three, students’ internal
motivation resonated highest amongst respondents, specifically a pattern that was inherent of a
growth-mindset. Findings suggestions that students’ mindsets, irrespective of content area, such
as computer science, will likely influence their self-efficacy in any given subject. This appeared
to differ from the body of literature, as most previous studies focused on factors related to CS;
whereas study’s findings suggest that the preexisting growth mindset of Latinas will predispose
them to higher levels of self-efficacy in CS and likely to increase retention in the field.

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 8

Chapter One: Overview of the Study
The current study addresses the issues of underrepresented minorities (URM) in science,
technology, engineering, and mathematics (STEM), specifically looking at Latinas in computer
science (CS). Until recently, STEM has been viewed as a monolithic term with data in the
aggregate, encompassing many contentious fields of which CS has been lumped in with other
subjects such as Biology, agriculture, and chemistry. Disaggregating the data reveals CS has
been one of the fastest growing industries in the country; however, the field itself yields unequal
representation of women and minorities. This study aims to explore Latinas’ self-efficacy in CS
and the factors that influence their perspective. Using a mixed method approach, the population
of interest is Latinas currently enrolled in a CS courses at the high school level. A one-time self-
reported online survey was used to assess self-efficacy. Interviews and observations were used to
evaluate factors that influence Latinas’ self-efficacy and belief in their ability in CS.
Background of the Problem

In his first address to congress, President Trump noted that “education is the civil rights
issue of our time” and advocated for a bill to fund school choice for “African-American and
Latino Children” (2017) to increase their educational opportunity. His words not only
emphasized the inequality in our educational system, but highlighted the continuing struggle and
plight of African and Hispanic Americans, and women in our educational system. The
President’s words were reminiscent of President Obama’s 2011 State of the Union speech in
which he expounds on the need for Hispanic children’s success in school and the integral role
they will play in the future of our economy. Former President Obama then went on to recognize
the link between the importance of science as a catalyst to our nation's creativity and
competitiveness in the global economy (The White House. Office of the Press Secretary, 2015).
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 9

Then, he followed up his words with action, as he proclaimed in his 2016 State of the Union
speech: “In the coming years, we should build on that progress, by … offering every student the
hands-on computer science and math classes that make them job-ready on day one” (State of the
Union Address, 2016). His words were supported by action spearheading federal programs
focusing on increasing the overall number of quality STEM workers: specifically focusing on the
development of high quality science and math teachers, career pathways, and intervention and
mentoring support programs. Computer Science for All was the Obama administration initiative
and commitment to empower students K-12 to learn CS. The initiative calls for $4 billion in
state funding and $100 million directly to local districts to expand and support CS in K-12 by
training teachers, developing instructional materials, and building local partnerships. For
building partnerships, the initiative called for the engagement and support of local and state
leaders, as well those in the private sector, to expand their commitment to their support of CS
opportunities.
Previous research has supported Obama’s connection that in order for the United States
to maintain its economic supremacy in a globalized economy, there must be concentrated efforts
in STEM (Chen & Weko, 2009). However, the integration of Hispanic, and other minority
groups, in STEM careers and STEM education, has had a slow start. Predominantly, science
achievement has been measured quantitatively either by results on high stakes standardized
assessments, such as the Standardized Testing and Reporting (STAR), the current Smarter
Balanced Assessment Consortium (SBAC), or the number of graduate degrees awarded in STEM
fields. In California, for example, students will take the California Science Test (CAST) in
grades five, eight, and once in high school, which is based on the California Next Generation
Science Standards (NGSS) as part of the California Assessment of Student Performance and
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 10

Progress (CAASPP). The CAASPP is aligned to the Common Core State Standards which were
adopted in 2010 to support 21
st
century skills and knowledge needed to be successful in college
or in the workforce after high school, irrespective of where students live. Regardless of the
measure, science achievement has historically been used to evaluate student learning, teacher
performance, and policy effectiveness. Despite federal initiatives, support, and new instruments
of measurement, gender and race disparities continue to persist at the college and professional
levels in certain STEM fields (National Science Foundation, 2017). Traditionally, policies have
been exclusively concerned on one end of the STEM pipeline--focusing on outcomes such as
increasing the number of female, Black, or Hispanic graduates, or raising test scores. However,
the stagnate results indicate, and mounting research affirms, that in order to create equality in the
STEM fields at all levels, the impetus should be on the other end of the pipeline and should
pressurize an influx of URMs at the onset.
Today, more than ever, social-emotional well-being is being explored to improve
educational outcomes. Previous research has shown that to improve educational outcomes,
awareness of the role between student achievement and noncognitive factors such as attitudes,
behavior, and various other strategies must increase (Farrington et al., 2012). Amongst the
various noncognitive factors, lies Bandura’s concept of self-efficacy, or the belief that one has
about the success on a particular task or in a particular problem. The link has been well
established between students’ academic achievement and self-efficacy (Britner & Pajares, 2006;
Pajares, 1996, 2003; Usher & Pajares, 2008). This study builds upon current findings in which
gender equity in certain STEM fields, such as biology, chemistry, and math have been achieved,
but points out that female, Blacks, and Hispanics continue to be present in small numbers in
computer science, engineering, and physics. The focus of the dissertation, then, is to explore the
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 11

perceived self-efficacy within computer science courses at the high school level of Latinas (the
group with the widest gap in STEM), and to explore the impact cultural biases and stereotypes
have on the formation of their perception. Understanding the perspective and factors that
influence URMs’ decision to enter the STEM pipeline is crucial to increasing their overall
representation in underrepresented science fields.
Statement of the Problem

The Civil Rights Act of 1964 required, for the first time, a national survey to report on
Equality of Education Opportunity. This landmark report, which became colloquially known as
the Coleman report, was the first nation-wide survey that examined the disparities in
achievement and opportunities between racial groups and highlighted the inequalities that
existed in the school milieu that created these gaps. Major findings suggest that student success
is not only determined by a student’s own cultural background, but to a less extent, to the
cultural background of other students in school. Although there is much scholarly debate about
the validity and accuracy of the findings in the report, due in large part to improper methodology
and analysis, the report, nevertheless, was a stimulus for much needed change and sparked the
discussion between students’ culture and educational outcome.
The 1960s also ushered in the beginning of an era of decline in average test scores on the
Scholastic Aptitude Test (SAT) and highlighted the need for an accurate assessment of all
students’ performance, not just college-bound students. The demand was met with the first
National Assessment for Educational Progress (NAEP) assessment, more commonly known as
the Nation’s report card, given in 1969. Not only did it provide an academic benchmark for the
nation, it also disaggregated the data by gender, race, and various other subgroups. For the first
time in the nation’s history, achievement between subgroups were quantifiable. Although testing
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 12

was done prior to NAEP, it was never done on a national scale, nor did these tests initially
encompass all students equally or include information on race. During the 1970s and the first
half of the 1980s, the Hispanic-white achievement gap narrowed; however, within the last
twenty years between 1995-2015, the achievement gap between minority and non-minority
groups have stagnated (Kena et al, 2016).
Suggested causes for the narrowing of the gap during the 1970s and first half of the
1980s have been linked to many factors: socioeconomics (Grissmer, Kirby, Berends, &
Willamson, 1994; Hedges & Nowell, 1998; Berliner, 2006), culture (Cole & Espinoza, 2008;
Jones, Castellanos, & Cole, 2002; Reardon & Galindo, 2009), school conditions (Orfield, 2005;
Grissmer, Flanagan, and Willamson, 1998), and practices (Palardy, 2008; Campbell, Hombo, &
Mazzeo, 2000). Lee (2002) highlights the fact that the suggested causes of narrowing
racial/ethnic achievement gaps in the past cannot be attributed to a single source, but rather, to
the interplay of multiple factors that were specific to the era. Hence, he opines the need to
restructure the framework to analyze causes for the achievement gap through a multilevel,
multidisciplinary approach. During the 1990s, these trends stabilized in the basic skills area and
grew marginally at the higher skills area (Lee, 2002). Overall, between 1990 and 2015 there has
been no statistical narrowing of the Hispanic-white achievement gap (Hemphill et al, 2011; Kena
et al, 2016). It was during this time period in the 1990s, that major federal legislation passed the
No Child Left Behind (NCLB) Act to curtail the racial disparities in achievement between
minority and non-minority students in K-12 public schools. According to Reardon’s (2013)
analysis, there appears to be no statistical narrowing of achievement gaps, on average, that can
be attributed to NCLB. His analysis delineates the impact of NCLB varying by state; where
largest impact was in states that had minorities segregated and in states that had the largest
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 13

achievement gaps prior to the implementation of NCLB. Although narrowing of achievement
gaps in certain states can be associated to NCLB, the rate in which these gaps are narrowing are
negligible at best. NCLB’s focus was to “ensure that all children have a fair, equal, and
significant opportunity to obtain a high-quality education;” however, empirical findings suggest
this endeavor has been a failure on average, and that achievement gaps between minority and
non-minority students have been static, if not widening, for certain groups in the last twenty
years (Kena et al, 2016; Reardon, 2013). The persistence of the low achievement rates of
Hispanics have lingering effects beyond the K-12 classroom. Each year, roughly 300,000 high
school Hispanic students graduate; however, only 60,000 will complete a degree (Fry, 2004).
Purpose of the Study
Theoretical Framework
The study will focus on the perception Latinas have on their science self-efficacy within
the computer science courses at the high school level. The study will utilize social cognitive
theory to examine their perspective as it relates to the social context of their current and past
environments within academia. It has been well documented that self-efficacy can play an
integral part in learning and persistence (Usher & Pajares, 2008), and must be considered as a
crucial nexus for improving student outcomes in science and other related fields. As such, this
dissertation will explore the relationship between the most up to date literature on Latinas in
STEM and their science self-efficacy within the high school years. Elaborating on social
cognitive theory, the focus on science self-efficacy will explore factors that influence the
development of Latinas’ beliefs in their abilities in CS.
Bandura theorized four critical sources of self-efficacy: mastery experiences, verbal
persuasion, peer comparison, and physiological factors (Bandura, 1994; Pajares, 1996). Mastery
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 14

experiences occur when individuals themselves experience success or achievement in their
endeavors. Verbal persuasion results from the implicit and explicit communications of others
such as peers or teachers. Peer comparison is when individuals vicariously compare themselves
to others to measure their likelihood of success. Lastly, physiological factors such as mental
health, emotional wellbeing, and anxiety can influence individuals' beliefs in themselves. Salient
of the four theories presented by Bandura is the one on self-mastery, in which individual success
has the greatest impact on one’s self-efficacy. Applied to science, a student’s self-efficacy, or a
belief in their ability to succeed in science tasks (Britner & Pajares, 2006), influence their
science achievement, and their emotional, cognitive, and behavioral engagement in science
classes (Lau & Roeser, 2002).
Importance of the Problem

As the population of Hispanic groups continues to rise in the United States (U.S. Census
Bureau 2010), to projected population levels by 2050, the opportunity and achievement gaps that
persist between Hispanic and non-Hispanic groups become magnified. According to Chapa and
De La Rosas (2006), despite the rise in Hispanic populations, there is not likely to be a
significant increase in enrolled Hispanic students in higher education, especially in STEM
majors. Currently, Hispanics eighteen to twenty-four are less likely to say they are currently
enrolled in school (twenty-four percent) than all young adults eighteen to twenty-four (forty-two
percent) (Lopez, 2009). Overall, Latinos have the lowest education attainment level of any
group in the U.S. (Kena et al, 2016). Although the overall number of students that enroll in
STEM courses has increased, the Hispanic population disproportionately have high attrition rates
in STEM majors (Oakes, 1990; Young, 2005) and subsequent low completion rates (Chen &
Weko, 2009; Herrera & Hurtado, 2011). The disparate low-achievement rates for Hispanic
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 15

students in K-12 public schools engenders the low enrollment and attainment rates in higher
education, specifically in the fields of STEM (Ashby, 2006; Eamon, 2005). Eamon (2005)
highlights the importance of math and science performance at the elementary and middle school
level to influence the performance and interest of students in STEM courses as well as pursuing
a career in the STEM field and thus pressurizing the proverbial STEM pipeline. Of all the
predictors for enrolling in a STEM major, students’ self-efficacy has been shown to be the
highest (Post-Kammer and Smith, 1986; Post-Kammer, 1985; Betz & Hackett, 1981). The
Cheryan, Ziegler, Montoya, and Jiang (2017) meta-analysis of the most commonly cited factors
explaining gender disparities in STEM participation reveals the variability of women in STEM
fields and how their representation in computer science, engineering, and physics continues to
exhibit an inequitable gender-gap compared to progress in biology, chemistry, and mathematics.
The purpose of this study is to describe how self-efficacy is created in Hispanic female students
that are enrolled in high school computer science course at an urban high school and what
potentially may have greater influence in creating this perspective amongst Latinas.
The study will build upon the most recent findings in regards to women and Hispanics in
STEM and make recommendations for further research to decrease the gender-gap and race-gap
in certain STEM fields. Although the study is not generalizable, its implications are far-reaching.
The goal, then, of the study is to increase awareness of the factors that may persist and that
reproduce the paucity of females, and other URMs in STEM, and to explore the complexity of
how these factors relate specifically to Latinas' ability to perceive their science self-efficacy in
computer science. Identifying plausible factors that inhibit Latinas from entering the STEM
pipeline requires understanding their perspective prior to entering the pipeline.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 16

Limitations and Delimitations

As a self-identified white male, high school Biology teacher, student, and parent, I
recognize my subjectivity in conducting the investigation, and the myopic perspective my
subjective lens brings to the inquiry. The research bias, however, does provide positive insight
being close to the focus of analysis in this study and issues related to the study. Over a decade of
day-to-day interactions with Latina students in various science courses and levels, has allowed
me to witness firsthand many students' low and high science self-efficacy. The negative impact
of my personal bias can result in impulsive, narcissistic conclusions that I may feel strongly
about and that make sense to my understanding of the research questions as they exist in my
own fixed paradigm, but may not be necessarily accurate.
Furthermore, sampling participants were limited to my own school site, thus data findings
are not generalizable. Though participants were limited to Latinas at a specific high school, and
interview findings are specific to the selected representatives, their narratives are meant to be
reflective of all Latinas’ experience in CS in high school. The results cannot be generalized
beyond the experiences of the students in this convenience sample since it is unknown to what
extent their perspectives apply to students with different characteristics such as age, gender,
socioeconomic status, and location. The study did not incorporate member checking (Creswell,
2014), and findings of emergent themes gleaned from the data set, were not validated by
respondents. Lastly, due to limited time constraints and the nature of the dissertation, the breadth
of interviews were confined to four, 30-minute, interviews, with no follow-up. Observations
were limited to three, one-hour, classroom visits, and surveys were given using convenient
sampling at my own school site. As a result, the study did not spend extensive time further
delving into the depth of the respondents' science self-efficacy and limits their account for more
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 17

accurate and valid findings. The questionnaire utilized from HSLS:09 did not differentiate
science self-efficacy by specific science subgroups. Prior research has shown the variability of
students’ beliefs of their abilities when it comes to different science courses and the convince
and self-efficacy varies with each field in science. Future research exploring science self-
efficacy would require the development of specialized measurement instruments, especially
within each subfield in science.
Credibility and Trustworthiness.

The study attempts to address concerns to both internal and external validity by ensuring
transparency with data collection and analysis. Internal validity deals with the question of how
research findings match reality. To ensure the trustworthiness, and uphold internal validity, the
study triangulated the data from across interviews and an observation to confirm the emerging
findings. Respondents received an explanation of the purpose, boundaries, and methods of the
inquiry. Informed consent was given after ensuring participants' confidentiality.
In terms of external validity, and to the extent findings apply across different settings and
times, a thick description of a robust database was provided in order to allow others to make
informed decisions. There was adequate engagement data collection, such that the data became
saturated. Audit trails have been detailed in the previous section. It is important to note the bias
nature of the analyses, given my position as a ninth-grade science teacher, working in the same
location in which the study was conducted.
Definition of Terms

Attribution theory - belief that people try to find explanations for what happens to them and
that these explanations then shape their reactions
Fixed mindset - the belief that intelligence cannot be developed (Dweck & Yeager, 2019)
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 18

Growth mindset - the belief that intelligence can be developed, for example, through
personal effort, good learning strategies, and lots of mentoring, and
support from others (Dweck & Yeager,2019)
Hispanic or Latinx - Hispanic or Latinos are defined as being from Cuban, Mexican, Puerto
Rican, South or Central American, or other Spanish cultures (U.S. Census
Bureau, 2010).
Self-efficacy – The belief in one’s capabilities to organize and execute the course of
action required to manage prospective situations” (Bandura, 1995, p. 2)
Science self-efficacy –affects a students’ belief in ability to succeed in a task, course, activities,
or future aspirations within science related fields (Britner & Pajares, 2006)
Underrepresented Minorities - This category comprises three racial or ethnic minority groups
(blacks, Hispanics, and American Indians or Alaska Natives) whose
representation in S&E education or employment is smaller than their
representation in the U.S. population. (NSF, 2017)
Organization of the Study

Chapter one provides an overview of the study, providing brief background information,
definition of terms, limitations and delimitations, statement of the problem and research
questions. Chapter two delves deeper into the background and explores relevant literature to date
establishing what is already known about women and Latinas in STEM and the need for the
study. The chapter goes on to delineate Bandura’s social cognitive theory, specifically focusing
on self-efficacy beliefs as the theoretical framework for the study. Chapter three describes how
the study will be conducted, with whom, and why those choices were made. Specifically
describing our methodology design, instrumentation, sampling, and planned data collection and
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 19

analysis method to answer the research questions. Chapter four links the results of the study to
research questions with a detailed outline of the analysis process. Chapter five will discuss
research findings, limitations from the study that were not noted prior, implications for future
research and practice, and concluding remarks.

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 20

Chapter Two: Literature Review
Introduction
STEM drives the Nation’s innovation, global competitiveness, and ultimately improves
the quality of life; however, despite the exponential growth of STEM careers in the past few
decades, United States businesses voice concerns over the supply and availability of STEM
workers and the disproportionality of the types of workers in these fields (Langdon, Mckittrick,
Beede, Khan, & Doms, 2011). Previous research has suggested that, in order for the United
States to maintain its economic supremacy in a globalized economy, there must be a
concentrated effort on STEM (Augustine, 2005; Chen, 2009) and an integration of women,
Hispanics, African Americans and other underrepresented subgroups (Gandara, 2015; Landivar,
2013; Miller & Horrigan, 2014) to strengthen the overall STEM pipeline and ensure well-
qualified workers in the future. The 2012 Report from the President’s Council of Advisors on
Science and Technology foreshadowed a deficit of one million engineers and scientists if trends
were to continue (Olson, 2012). Still, the integration of Hispanics (and other minority groups) in
STEM careers and STEM education has had a slow start. As the population of Hispanic groups
continues to rise in the United States (Humes, Jones, & Ramirez, 2010), to projected levels by
2050, the opportunity and achievement gaps that persist between Hispanic and non-Hispanic
groups become magnified. At 54 million, Hispanics are the largest minority group in the country,
and Latinas are one in five of our country’s overall population and projected to be one third by
2060 (Colby & Ortman, 2015). Despite their growing numbers, their concentration in STEM
hasn’t proportionally kept up with their growing representation in the workforce (Landivar,
2013).
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 21

The discourse around STEM, from its obfuscated definition, to factors that buttress the
proverbial STEM pipeline, to the disparities within STEM, vacillate within the research. This has
led some studies to view STEM using a much broader lens and include a wider range of
professions, whereas other studies may view the definition parsimoniously (Noonan, 2017);
suffice it to say, findings are subjected to the circumscribed working definition of STEM by the
researchers. The ambiguity in the name STEM has led to a lack of consensus about what
qualifies as STEM work (Langdon et al., 2011; Landivar, 2013) compared to non-STEM work
and questions the validity of previous research findings. In 2011, the Standard Occupational
Classification Policy Committee (SOCPC) identified three occupational domains: (1) science,
engineering, mathematics, and information technology occupations; (2) science-and-
engineering-related occupations; and (3) non-science and engineering occupations; which clearly
defined the boundaries of what is and is not STEM (Landivar, 2013).
Despite the ambiguity of previous studies which lacked a clear definition of STEM, what
has been clear throughout the body of research is that while women in today’s society continue
to make strides in all other fields of our country’s economy, there still persists a habitual inequity
of women in STEM. In 2017, the Office of the Chief Economist (OCE) released a series of
reports around STEM and the workforce expounding on women in STEM. The reports found
that in 2011, there were 7.2 million STEM workers accounting for 6 percent of the workforce
(Landivar, 2013), by 2015, there were 8.6 million workers comprising 5.7 percent of the
workforce (Noonan, 2017). Even though the STEM field has been the fastest growing field in the
labor market (Langdon et al., 2011), and women filled 47 percent of all U.S. jobs in 2015, they
comprised only 24 percent of STEM jobs and Latinas made up only three percent of that
(Noonan, 2017). Despite women’s increasing numbers within certain fields, there has been an
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 22

uneven overall growth in women’s representation in STEM, and they remain significantly
underrepresented in engineering and computer occupations, which make up 80 percent of all
STEM employment. Since 1990, women’s representation in engineering stunted, and during the
same decade, computer occupation growth began a steady decline (Landivar, 2013; National
Science Foundation, 2017). Similar disparities are seen when viewing the racial demographic
breakdown, with 71% of STEM workers being non-Hispanic White, to only seven percent
Hispanic with the concentration varying by STEM field. Latinas, as a group, have improved their
wage earnings over the last decade more than any other women’s group. In 2011, Latinas earned
56 cents for every dollar earned by their White non-Hispanic male counters, and seven cents
lower than their Hispanic male counterparts (National Women's Law Center, 2015). In 2018, the
gap had closed to 80 cents, with the median annual pay for women holding a full-time, year-
round job at $41,554, while for men, the median annual pay was at $51,640--an annual gender
wage gap difference of $10,086 (U.S. Census Bureau, 2017). Combined, the wage gap between
genders is estimated to be a net loss of $900 billion dollars (U.S. Census Bureau, 2017). In 2004,
Latinas earned 70 cents for every dollar earned by all other women, but by 2014 that gap was
reduced to Latinas earning 78 cents for every dollar earned by all other women (Gandara, 2015).
In terms of Latinas in STEM, the gender wage gap was even wider, with women with STEM
degrees earning $7, 500 less than the average earned by all other women in a STEM field as of
2010 (Gandara, 2015). Historically, there has been an underrepresentation of women, Blacks,
and Hispanics in the STEM workforce (Landivar, 2013); however, the paucity of these groups
are not unique to the labor market and reflect the low numbers of those majoring and persisting
in college (Griffith, 2010). Although the level of college graduation rates for Latinas has risen
faster than any other subgroup, it is still marginally lower than that of white women. In 2008,
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 23

college graduation rates were at 31.3 percent for Latinas, significantly lower than white women’s
graduation rate of 45.8 percent. These stagnate numbers in certain STEM careers are mirrored in
the education domain; more than half the STEM bachelor’s degrees earned by women are in
biology, chemistry, and mathematics, yet less than 20% are in computer science, engineering,
and physics (Cheryan, Ziegler, Montoya, & Jiang, 2017; National Science Foundation, 2017).
Although women now earn 37% of all bachelor’s degrees in STEM, disaggregating the data
reveals the disproportionality of the concentration of women across the field. Yet within the
body of literature, STEM has been codified and viewed with a wide monolithic lens (Ehrlinger &
Dunning, 2003; Park, Young, Troisi, & Pinkus, 2011) or myopically through one specific field
(Cheryan, Plaut, Davies, & Steele, 2009; Good, Rattan, & Dweck, 2012). Cheryan, Ziegler,
Jiang, and Montoya’s 2017 meta-analysis on women in STEM disaggregated the most recent and
relevant research findings and introduced a three-tiered model, opening the doors for future

Figure 1. Cheryan et al. 2017 model on factors that influence women’s underrepresentation in certain STEM fields
researchers by identifying what specific parts of STEM is in greater need, highlighting potential
factors engendering the disparities in numbers, and making recommendations to close the gender
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 24

gap. The three-tiered model outlines factors undergirding the gender gaps that lead to lower
participation in computer science, engineering, physics, chemistry, and mathematics than in
Biology: (a) masculine cultures, (b) insufficient early experience, (c) self-efficacy. The above
model will be used as a framework for the remainder of the chapter emphasizing the relationship
of Latinas in CS and the cultural norms that underpin their representation in the field.
Masculine Culture

Using the model presented above, the first section of this literature review will discuss
the masculine culture surrounding women and Hispanic women in STEM specifically
stereotypes within the field, negative stereotypes, role models, and perceived bias. As noted in
the study, the masculine culture within STEM is about belonging and structure over explicitly
about power.
Stereotypes within the field

In general, women in U.S. culture are stereotypically perceived to have lower abilities in
mathematics and science (Dar-Nimrod & Heine, 2006). The over-representation of males in the
STEM fields has reinforced cultural stereotypes and has led to a male-dominated culture which
engenders a hostile environment for women (White, Altschuld, & Lee, 2006). These stereotypes
are not limited to the workforce but transcend into the academic setting. In a 2012 randomized
double-blind study, 127 leading science faculty members at top-ranked universities were asked
to rate application materials of a fictitious student randomly assigned a male or female name for
a laboratory manager position (Moss-Racusin, Dovidio, Brescoll, Graham, & Handelsman,
2012). The gender of the participants in the study did not affect the response. The study
revealed both male and female faculty members rating the male applicant as significantly more
competent and hirable than the woman, despite having identical application material. Faculty
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 25

also selected a higher starting salary and more career mentoring for the male applicant. Findings
included mediation analyses that showed that female students were less likely to be hired
because they were viewed as less competent. The study found that pre-existing subtle bias
against women was associated with less support for female students, suggesting that intervention
focused on the pre-existing bias of faculty may resolve further discrimination. Women’s fears of
encountering gender bias and discrimination in male dominated fields may influence their
likelihood of expressing interest in those fields and reduce their sense of belonging in STEM
(Ahlqvist, London, & Rosenthal, 2013). In turn, the cultural environment in the work and school
of STEM fields can become hostile, uninviting, and an isolating milieu. Data from the annual
National Survey on Drug Use and Health collected from 2004-2006 yielded a 2007 report from
the Substance Abuse and Mental Health Services which revealed that scientists and engineers are
least likely to experience clinical depression, with 4.3% in the engineering-architecture fields
reporting having one major depressive episode in the past year and those in the life-physical
science category similarly reporting only 4.4%. Notably, the report also highlighted gender
differences in frequency of depression within those categories. For example, 7.2% of women in
the life-physical-social science category reported a major depressive episode within the past year
compared to only 2.3% of males. In the engineering-architecture–surveyors fields, men reported
3.3%, while women reported 11.1 %. Of all scientific disciplines, mathematics and computer
science are the fields with the highest overall reporting of a depressive episode, with men
reporting 6.2% and women reporting 10.4%. It’s worth mentioning that the above-mentioned
gender gap of depressive episodes in the STEM fields is mirrored by the nationally reported
gender gap (WHO, 2001). Without exploring the underpinnings of why exactly there exists a gap
in the number of women who experience stress compared to men, and irrespective of underlying
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 26

cause, according to the World Health Organization (WHO), women are more likely to seek out
help from, and disclose mental health problems to, their primary care physician; whereas men
are more likely to seek specialist mental health care. In terms of diagnosis, there persists a
gender bias when treating psychological disorders, with women being more likely than men to
be diagnosed with depression even when experiencing identical symptoms. Depression accounts
for 41.9% neuropsychiatric disorders for women, compared to 29.3% for men. Women in the
STEM workplace and academia reported negative outcomes as a result of a masculine
culture including lower job satisfaction and productivity (Settles, O’Connor, & Yap, 2016). For
STEM undergraduates, lower psychological well-being and mental health (i.e. greater instances
of depression) have been shown to be caused by a perceived negative culture (i.e. hostile and
isolating) in the STEM major. All of the aforementioned outcomes are symptomatic of a
masculine culture within STEM, which ultimately undermines the self-efficacy and numbers of
females within the STEM pipeline.
These stereotypes about women’s abilities in mathematics and science result in self-
fulfilling prophecies known as “stereotype threats” (Steele, Spencer, & Aronson, 2002). Any
failure may be chalked up to gender inabilities, further supporting negative stereotype threats.
Proportionally, women are more likely to experience stereotype threat when underrepresented in
fields such as computer science, engineering, and physics (Cheryan et al., 2017)
Variability within STEM

Tinto (1997) study aimed to understand why URMs leave secondary institutes and the
STEM pipeline. In short, he perceived that in order for URMs to persist, they have to adapt to
the dominant hegemony of the institution. A woman’s decision to go into STEM is influenced by
the micro and macro level factors in the larger environmental and structural institutions;
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 27

understanding both are key to explain why some STEM fields are more gender-balanced than
others (Cheryan et al., 2017)
In line with the development of the masculine culture of STEM are the expectancy and
biases of our parents every child must endure. As our first teachers, parents’ biases, disposition,
and understanding about the world establish a child’s viewpoint about how they see the world,
more specifically how they see themselves in STEM or without STEM. A longitudinal study by
Thomas and Skunk (2017) looked at ways parents’ and teachers’ expectancy for success
influences third and fifth-grade expectancy for success and achievement in science. Results
showed that teachers’ expectancy in science does not significantly predict fifth-grade science
achievement; however, parents’ expectancy does. The study further determined that children’s
science self-efficacy significantly influence their science achievement scores; however, this was
a far weaker influence than the direct effect of parents’ expectancy. The interplay between the
cultural stereotypes of a minoritized student in a white male dominated field, coupled with the
cultural stereotypes about gender roles from parents, puts women, and more specifically Latinas,
at a disadvantage; limiting the likelihood of them going into a field such as CS.
Hispanic Cultural Bias and Stereotypes in STEM
The common belief from the literature shows women have had low numbers in STEM do
either to the desire to bear children or lack of exposure early on to mathematics and science
courses not because of discrimination (Ceci & Williams, 2011; Ceci, Williams, & Barnett, 2009;
Moss-Racusin et al., 2012).
In 1976 Malcolm, Hall, and Brown released the now famous report that spotlighted the
bias that exists in the workforce. Similar findings more recently have documented that gender
bias plays an important role in women’s decision to go into STEM. Math skills identical, both
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 28

men and women were twice as likely to hire a man for a job that required math (Reuben,
Sapienza, & Zingales, 2014). Another study found that male scientists at top-ranked universities
hired fewer female graduate and post-docs (Sheltzer & Smith, 2014) echoing the findings of
Moss-Racusin, Dovidio, Brescoll, Grahm, and Handelsman (2012). Most recently, these findings
along with the mounting body of gender bias research noted four distinct patterns (Williams,
Phillips, Calello, & Hall, 2014):
1. Prove-it-again – women often have to demonstrate more evidence of their
competency than men. (Eagly & Mladinic, 1994). – (Latinas: 64.5%)
2. The tightrope – women often feel the need to balance between either being seen
too feminine to be competent or too masculine to be likable (Cuddy, Fiske, &
Glick, 2004).
3. The maternal wall – maternal wall bias makes the assumption that women lose
their work commitment and competence after they have children (Correll, Benard,
& Paik, 2007; Cuddy et al., 2004)
4. Tug-of-war – gender bias amongst women elicits conflict between them, with
women who experience discrimination early on distancing themselves from other
women (Derks, Ellemers, van Laar, & de Groot, 2011).
The STEM fields provide a fertile breeding ground for bias culture against women,
namely because of the lack of representation and the perspective that science is seen as
meritocratic (Castilla & Benard, 2010). In a recent study, sixty women of color that were
scientists were interviewed, and all identified one or more of the aforementioned gender bias
patterns (Williams et al., 2014). Their study not only documented gender bias patterns but
disaggregated their findings by racial subgroups, identifying 64.5% of Latinas experienced
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 29

prove-it-again bias (second to Black women) with successes attributed to luck and mistakes
magnified and frequently recalled. Latinas were also noted in the study to risk being criticized as
“angry” or “emotional” when being assertive, with 60% of Latinas surveyed noting backlash.
Latina scientists are more likely than any other subgroup to report being expected by either
students or colleagues to do the bulk of office housework (i.e. make coffee), administrative
work, and emotional work (i.e. helping students with their emotional needs). As a result, Latinas
in the STEM field felt immense pressure to succeed; to make sure everything they did was
inscrutable to overcome the “Mexicans are lazy” stereotype. These stereotypes along with the
perception of what competent STEM workers or instructors look like, leave women of color
feeling that they have to prove themselves over and over again (Williams et al., 2014).
The cultural stereotypes are too familiar for many Latinas, however, the stereotypes
neither begin, nor end, in the workplace or at school; for many, they are reinforced at home.
Many, if not most, Latinas feel the immense pressure from their families to have children. This
was found to be especially true amongst Mexican Americans, as one Latina biochemist stated,
“Every good Mexican woman has kids in their 20s.” So it follows that they shouldn’t have
careers (Williams et al., 2014), which is supported by earlier findings on the value motherhood
holds in the Mexican culture (Stanley, 2006). In the same study, a Latina bioengineer stated the
importance of family, as she states “achieving for something higher, at least in my case, it was
seen as a waste of time. ‘why are you pursuing graduate school when you should be working?’
or ‘why are you pursuing graduate school when you have a husband to take care of?’”
Other Latina scientists in the same study also noted a similar maternal wall bias, stating
that Hispanic mothers are expected, and even obligated, to be the caregiver of the family. The
maternal wall stereotypes are a double-edged sword that working mothers of color have to
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 30

endure, but worse still, the absence of a child leads to the assumption that women should work
all the time because they have no lives outside of work. In the study, Latinas, more than any
other subgroup, reported this stereotype. One Latina quoted her boss as saying, “Oh, since you
don’t have children, can you please do this evening thing since you don’t have a family to go
home to?” (Williams et al., 2014).
As a group, Latinas begin school significantly behind other females, and without
adequate resources to support their educational development, they are never able to catch up to
their peers academically. Latinas graduate from high school at lower rates than any other major
subgroup; more than one in five have not completed high school by age 29. Latinas are also the
least likely of all women to complete a college degree, at just 19 percent compared to nearly 44
percent of white women (Gandara, 2015). When they do graduate, few end up going into STEM
and even fewer go into CS. A Gallup survey in 2016, see Figure 2, found the variability in CS
Figure 2 Gallup (2017) report findings showing disparities CS interest of males and females across ethnicity
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 31

across race. The study underscored the severe gender gap amongst Latinas and other URMs.
The cultural biases and stereotypes, the wage-gap, the biological and psycho-emotional
differences amongst gender are all barriers that inhibit and reproduce disparities in the
representation of URMs in CS and other STEM fields.
Self-efficacy

Self-efficacy is the estimations individuals carry about their capacity to organize and
execute action needed to be successful at a particular task. Individuals’ beliefs in themselves
contribute to: (a) goal-setting, (b) persistence, and (c) resiliency (Bandura, 1993, 1994). Sources
of self-efficacy hypothesized by Bandura stem from (a) enactive mastery experiences, (b)
vicarious experiences, (c) verbal persuasions, and (d) physiological and affective states (Bandura,
1997). The most powerful source being the mastery experience and interpreting the results from
one’s own past successes in a related task or field (Bandura, 1997). Self-efficacy beliefs are
formed only when experienced events have been evaluated and competency has been self-
assessed based on the results of those events. When individuals interpret their efforts to be a
success, their confidence level rises towards successfully accomplishing a similar task in the
future; however, when individuals deem their efforts to be a failure, their confidence level lowers
to succeed at a similar task in the future. The resulting behavior is demonstrated as individuals
are less likely to focus effort on a task they perceived to have failed in the past or avoidance of
the task altogether. In short, this is an efficient and safe way individuals can allocate their efforts
and time; i.e. “Why try, if I know I’m going to fail” or, “It’s okay that I failed, I didn’t try.”
In addition, individuals build their self-efficacy by means of vicarious experiences by
interpreting the results of other people's efforts and results. Here, role models can play an integral
lynchpin towards the development of individuals’ self-efficacy so long as they can relate to the
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 32

role model (Bandura, 1994, 1997; Usher & Pajares, 2006). Observing a classmate achieve
success at a challenging math problem, for example, ostensibly may increase the belief in other
students that they can do it too. Undergraduate Women and Underrepresented Minorities (URM)
are more likely to persist in STEM majors with a higher number of female and URMs (Griffith,
2010). Although some studies have shown success in using female role models to bolster
participation in STEM, simply increasing the number of female roles is not a panacea. Although
studies have found that having a female role model is important, it does not always relate to
increased interest (Cheryan, Drury, & Vichayapai, 2013). Although some studies have found that
the lack of a female role model may contribute to the gender disparity in certain STEM fields,
and Cheryan, Ziegler, Montoya, and Jiang (2017) model includes, with the caveat that further
investigation is needed to validate whether the lack of female roles alone and/or the lack of
relatable role models contribute to the underrepresentation patterns in female STEM
participation.
The third and fourth sources of self-efficacy are informed by our emotional and
physiological states; i.e. stress, anxiety, fatigue. Feelings of stress, anxiety, and fatigue toward a
task can work together or individually to negatively undermine our competence of successfully
completing a task. Increasing physical and mental well-being and reducing the emotional and
physical factors that undermine these sources can strengthen self-efficacy (Usher & Pajares,
2006). Although the literature has examined numerous sources of self-efficacy, the results have
been inconsistent (Usher & Pajares, 2006); however, as noted previously, mastery experience is
largely believed to be the most influential (Bandura, 1997). For example, Klassen (2004)
explored the efficacy belief of 270 South Asian immigrants and Anglo Canadian non-immigrant
students. Findings suggest that ethnicity was predictive of self-efficacy of how immigrant
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 33

students in 7
th
grade interpret the sources of their self-efficacy in mathematics; however, no other
research to date has reported similar findings (Usher & Pajares, 2006). Researchers have
indicated that the effects these sources of self-efficacy have, is a function of gender (Zeldin &
Pajares, 2000) and ability level (Hampton, 1998), however, race or ethnicity has been sparsely
explored (Usher & Pajares, 2006). In terms of the academic setting, self-efficacy in students
provides the motivating factor and is associated to students’ persistence and academic success
(Pajares, 2003). Students who believe in themselves academically, tend to show greater interest
in academic work, set higher goals and put forth greater effort (Bandura, 1997; Pajares, 1996).
Past studies have shown higher self-efficacy show a greater tendency for individuals to expend
more effort on a task, and show persistence, and resiliency in their educational pursuits compared
to those students with lower self-efficacy (Betz, 2004; Betz & Hackett, 1983). Self-efficacy is a
key deciding factor in our motivation. For example, when students achieve personal success, or
demonstrate extra effort as they vicariously witness the success of their peers, or when they are
persuaded by positive verbal and nonverbal gestures from parents, teachers, and/or peers,
students’ self-efficacy is undergirded and enhanced (Schunk, 2012; Usher & Pajares, 2006,
2008). Consequently, the reverse holds true for students with low self-efficacy, negatively
impacting their choices, motivation, resiliency, and results in purposefully avoiding tasks they
perceive might result in failure. A study by Usher and Pajares (2006) hypothesized sources of
self-efficacy on the academics and self-regulatory beliefs of 263 entering middle school students
and measured if these sources were consistent across gender, reading ability, race/ethnicity. Self-
efficacy has also been found to be a strong predictor of college majors and career choices
(Hackett, 1995).
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 34

Examining self-efficacy in science, at various levels on the STEM pipeline, has shown
mixed results depending on academic level and subject matter. For example, in a study in 2010,
among high school and undergraduate students (Cheryan, Plaut, Handron, & Hudson, 2010),
women reported lower self-efficacy in computer science compared to their male counterparts
(Irani, 2004). There were similar findings in undergraduate engineering programs (Huang &
Brainard, 2001) and in mathematics (Sax, 1994); however, other studies have found female self-
efficacy equal (Concannon & Barrow, 2009), and in some cases even higher (Jones, Ruff, &
Paretti, 2013), than males. Similar findings were noted at the high school level, with female
students having the same level of science self-efficacy as male students (Else-Quest, Mineo, &
Higgins, 2013), whereas other studies found females had lower science self-efficacy than males
(Ehrlinger & Dunning, 2003). In an international study across 50 countries, when the gender gap
was controlled in science self-efficacy, the disparities to pursue a science career, such as
computer science, did not change. This would suggest that self-efficacy alone is not enough to
encourage women to enter the STEM pipeline.
Mindset

After studying the behavior of thousands of children, Dr. Carol S. Dweck coined the
terms fixed mindset and growth mindset. Similarly to self-efficacy, these mindsets describe the
underlying beliefs people have about learning and intelligence. When students believe they can
get smarter, they understand that effort makes them stronger, so they put in extra time and effort,
which leads to higher achievement. Her work built on Martin Seligman’s concept of learned
helplessness. This, coupled with attribution theory, formed the foundation of Dweck’s work on
mindset. In 1978, her work showed that, depending on the perceived source of failure, some
children collapsed helplessly, while others demonstrated resilience in the face of challenges. She
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 35

proposed that mindsets create meaning systems, which organize our goals, beliefs, attributions,
helplessness, and behavior (Dweck & Yeager, 2019). Later, her work added the concept of
effort beliefs, which also coincide with self-efficacy. Dweck defines effort belief in one of two
ways: it can be viewed as a positive thing that helps grow your ability, or as a negative thing that
demonstrates deficiencies in ability (Dweck & Yeager, 2019).
Current research findings from a nationally represented sample of ninth graders
demonstrated the correlation between mindsets and grades (West, Buckley, Krachman, &
Bookman, 2018; Yeager, et al. 2018). Their findings showed that having a growth mindset can
engender resilience in the face of challenges and suggested that a growth mindset forms the core
of a wide-reaching meaning system; however, no previous research has studied the potential
relationship between Latinas, or any other URMs, in CS and the implications of having a growth
versus a fixed mindset. This study’s findings, suggest that a growth mindset may be a factor in
the self-efficacy demonstrated by some of the participants.
Intersectionality of Race, Gender, and Science Self-efficacy
Erikson (1968) describes how boys and girls might developmentally interpret and value
their experiences differently as they seek to find and comprehend their identity. Boys, for
example, typically put more stock in their accumulated accomplishments. Academically, this
means that boys are likely to value successes and failures with academic tasks and activities by
obtaining good grades. For girls, however, the successful development of relationships plays an
integral role in their sense of identity. This may hint at the underlying cause of why female self-
efficacy may be influenced so much by the vicarious experiences and “relational efficacy”
(Zeldin & Pajares, 2000) of teachers, parents, and other adults. This suggests that boys and girls
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 36

inherently have different sources for developing their self-efficacy and that these sources have a
different impact on students as they develop, depending on gender.
Zeldin and Pajares (2000) did a qualitative study where they analyzed the personal
narratives of fifteen academically successful women who excelled at mathematics, science, and
technology. During interviews, these women were asked to describe who and what influenced
their career paths. Findings discovered that vicarious experience and social persuasion greatly
influenced women’s confidence in their abilities. Notably, the researchers also discovered what
they coined as “relational efficacy” to be an influential factor in shaping their beliefs. That is,
women relayed the beliefs that others had in them.
In terms of race, Hispanic students report lower science self-efficacy than their White
counterparts (Lofgran, Smith, & Whiting, 2015). However, a study of more than 7,000
engineering students across 21 universities revealed Latino women’s STEM self-efficacy did not
differ from White men (Litzler et al., 2014). As the Cheryan et al. 2017 meta-analysis noted,
further studies evidence is needed to fully validate and understand the role self-efficacy plays in
determining underrepresentation of URMS in STEM.
Education

Lastly, Cheryan et al 2017 meta-analysis found that insufficient pre-college experience in
CS compared to such fields as Biology or Chemistry contributed to the gender disparity in the
STEM field. The study highlighted three sources that factored into the insufficiency. First was a
few course offerings in certain STEM fields like CS compared to others like Biology. Second,
students have the freedom to opt out of taking some STEM courses than others. Lastly noted, was
the gender gaps in early experience in some STEM fields.

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 37

Course Access

Biology, Chemistry, and mathematics are more likely to be offered compared to other
subjects such as CS, engineering, or Physics. Moreover, these subjects are more likely to be
required as part of the high school graduation requirement; whereas, CS is likely to be an elective
student could opt out of taking. Students that live in states with higher math and science
requirements will have more students taking these course, and consequently increasing the
likelihood of majoring in STEM (Federman, 2007). A Gallup poll in 2016 conducted a
comprehensive review of the factors influencing the current perception of CS in the U.S. and
found that three out of four principals reported that their school does not provide access to CS
programs (Google & Gallup, 2016). The study found that Latino students from poorer
neighborhoods had less access to CS compared to White students. Cheryan et al 2017 meta-
analysis concluded fewer course offerings and access to CS predicts the gender gap in the STEM
pipeline. Their findings coincided with parent perceptions about the major reason why
URMs don’t go into CS (Hinton, 2016). In the nationally represented survey, half the parents
surveyed believed that the reasons why Latinos and other URMs don’t go into CS were due to
external factors such as a lack of opportunity to learn CS, lack of exposure to CS, or a lack of
role models.
Elective Course

When the opportunity to take a CS exists at a high school, often these courses are not part
of the graduation requirement, allowing students the freedom to opt out of taking the elective
course. In a nationally represented survey of K-12 students, more boys than girls reported having
learned CS, and Latino students were less likely to report having learned CS compared to White
and Black students (Google & Gallup, 2015). The Cheryan et al 2017 meta-analysis concluded
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 38

that fields with the most freedom to choose courses in high school are fields with greatest gender
disparities in college. The more freedom students have to opt out of certain STEM courses like
CS, compared to Biology, may contribute to current patterns of representation in STEM fields.
Having more variability in STEM course requirements may provide girls and URMS the
opportunity to be exposed to the field and experience it for themselves rather than rely on
stereotypes and other people’s perceptions
Early Experience

The previous two factors mentioned that the availability of CS courses, and the freedom
to opt out of those courses, contribute to unequal experiences in CS and other STEM fields. In
addition, the research has shown a discrepancy in the types of pre-college extracurricular
activities boys and girls participate in. For example, it was found that boys were more likely than
girls to choose a science fair project related to CS (Greenfield, 1995). In introductory CS courses
at the college level, men were at an advantage because they enter with more prior experience than
their female classmates (Sackrowitz, Parelius, Sackrowitz, & Parelius, 1996). Early and frequent
exposure is key to address the confidence of URMS in CS; however, the Cheryan et al 2017
model noted that exposure is not enough to break down barriers that inhibit equality in CS.
Although increasing the number of CS programs and course requirements may increase the
opportunity for URMs to experience what the field truly is first hand, access alone is limiting.
Increasing the enrollment of females and other URMs in CS may not produce the intended results
if these students continue to believe in the stereotypes of the broader field and perceive CS as a
masculine field. Rather, a direct, conscious, and concerted effort is needed to counteract the
masculine culture of the field, providing URMs a sense of belonging and undergirding their
science self-efficacy in CS. The impact of early CS experience on Latinas and other URMS’
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 39

science self-efficacy was noted in a Cheryan et al 2017 meta-analysis. However, this aspect was
excluded from their model of potential factors that contribute to the current pattern of variability
in STEM fields. As mentioned in the study, there appeared to be conflicting evidence
questioning the impact early experience has on the persistence in CS.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 40

Chapter Three: Methodology

The previous chapter discussed the body of literature as it relates to Latinas’ science
self-efficacy in high school, factors influencing its development and sustainment, and current
research. The current chapter will circumscribe the methods used in the study to explore the
research questions in the context of the literature reviewed. The introduction will bridge the
literature review findings and theoretical framework to the relevance of the research questions,
specifically exploring how Latina students in CS perceive their science self-efficacy and
possible factors that impact it. Subsequently, the chapter will outline descriptions of the dataset,
explanation of variables, and analytic strategy.
Introduction

Chapter 2 reviewed current research on female students’ sources of underrepresentation
within the STEM pipeline, specifically, self-efficacy, male-dominated cultural factors, and lack
of educational availability. In addition, chapter 2 reviewed Bandura’s self-efficacy theoretical
framework as a lens as it applied to this dissertation. Self-efficacy is the estimations individuals
carry about their capacity to organize and execute action needed to be successful at a particular
task. Individuals’ beliefs in themselves contribute to: (a), the types of goals they set, (b), their
persistence, and (c), their resiliency (Bandura, 1993, 1994). Sources of self-efficacy
hypothesized by Bandura stem from (a), enactive mastery experiences, (b), vicarious experiences
(c), verbal persuasions, and (d), physiological and affective states (Bandura, 1997). The most
powerful source being the mastery experiences as they are interpreted from one’s successes or
failures in a related task or field (Bandura, 1997).
Predominantly, previous research has tended to lean heavily on quantitative means of
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 41

exploring women’s and/or Hispanics’ underrepresentation in STEM; however, when qualitative
explorations did arise at the secondary level, often these studies focused through the lens of the
science teachers’ perceptions. Although there has been much explored in terms of the scarcity of
women and minorities in the STEM fields, the purpose of this study is to build upon our current
understanding of the recent disaggregated findings, and explore in-depth how Latinas perceive
their science self-efficacy in CS and what potentially may influence their perception.
This study used a mixed method approach to cast a wider net on Latinas’ science self-
efficacy in CS, then delve deeper with five student surveyors–three from Advanced Placement
(AP) CS, and two from a mandatory ninth-grade tech class. This study utilized the questionnaire
from the High School Longitudinal Study of 2009 (HSLS:09) (Duprey et al., 2009) (see
Appendix P) to quantitatively measure students’ self-efficacy in science.
Research Questions

1. How do high school Latinas in an urban public high school perceive their science
self-efficacy in computer science?
2. What factors influence the science self-efficacy perception of Latinas in computer
science?
This study used surveys and in-depth semi-structured interviews with a mixed methods
approach to accurately answer the research questions. The mixed method approach provides a
combination of qualitative and quantitative data that delineate a more robust understanding of
female Hispanic students’ science self-efficacy (Creswell, 2014). More specifically, the study
uses an intermethod mixing approach, which uses information from two (or more) data
collection methods (Johnson & Christenson, 2015). As Johnson and Christenson state, the
benefit of using a mixed method approach “is like putting together several flawed fishing
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 42

nets…to construct a ‘new,’ stronger net” despite the limitations of each inquiry method (2015).
Given their persistent underrepresentation in STEM and the urgency to fill careers in these
fields, and prior research; a comprehensive understanding of the barriers that limit females is
much needed. Using an explanatory sequential mixed method approach to investigate, students
were given a standardized Likert survey at the end of first-semester to measure their perceived
science self-efficacy. This quantitative inquiry was used to establish perceived levels of science
self-efficacy and address the related research question. Analysis of the initial survey allowed the
researchers to build on the data and explore qualitatively with in-depth interviews, and
observations, to investigate the sources of Latina students’ perceived science self-efficacy.
Qualitative research allows for the exploration and understanding of an individual’s or
group’s perspective (Creswell (2014). The exploratory process typical of qualitative research
allows for an inductive approach to develop general emergent themes throughout the data
collection and the analysis process and contributes to the body of literature by providing a more
robust understanding of Hispanic female students’ perspectives on their self-efficacy in science
and the factors that influence their perception. As Agees (2009) states, qualitative inquiry
“involves asking the kinds of questions that focus on the why and how of human interaction” (p.
438). This is directly aligned with our research questions in trying to understand how Latina
students develop their science self-efficacy in CS. Interviews provide the most data-rich source
to capture students’ self-efficacy perspective and examine the research questions. The paucity of
qualitative research exploring female Hispanic students’ self-efficacy at the high school level
makes this research critical to understanding the factors that maintain a gender gap in STEM
majors and careers. The STEM gap has overwhelmingly been looked at through a quantitative
lens; and when looked at qualitatively, the research tends to focus on teachers’, rather than
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 43

students’, perspectives. The study used a mixed method approach to explore the mechanism
behind Latina students’ science self-efficacy in CS.
Research Design and Methods
Sampling
At the start of the 2018-2019 school year, the CS teachers were approached about
participation in the study. The focus of analysis of the study were explained and any questions
with regards to the study and privacy were acknowledged at this time. Nonrandom sampling
techniques were used to select and focus our unit of analysis on female Hispanic students in
computer science. Snowball sampling was used to select participants for the quantitative phase of
the study, whereas homogenous purposive sampling was used to ensure a high sampling pool
with characteristics of interest and to elicit a high response rate for the quantitative phase.
Purposive sampling method allows the researcher to specify the characteristic of the population
of interest and focus on individuals that have those characteristics (Johnson and Christenson,
2015).
Setting
The initial phase of the study was conducted in both computer science classrooms,
surveying all course levels at SHHS. Whereas the observation was conducted in Ms.O’s
classroom at SHHS during a selected period of the day, for approximately one-hour. A total of
five interviews were conducted on campus, after school, using the school libraries private
workrooms. To account for any biases, observations and interviews were conducted outside my
own pool of students.
Access/Entry

The study was conducted at my own school site, Sierra Hills High School (SHHS)
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 44

(pseudonym), which allowed me access to colleagues and a sample population of students. Initial
contact was made with participating teachers to conduct the investigation in their CS classes
pending Institutional Review Board (IRB) approval (see Appendix A). SHHS has two computer
science teachers. For the quantitative phase, all CS students from both teachers were surveyed
with selection for qualitative phase being sampled from both instructors. Prior to the quantitative
phase, I reviewed the purpose of the study, letters of consent, and confidentiality with both
instructors. Volunteers that agreed to participate were given a permission letter of consent (see
Appendix B) that outlined the intent of the study–to understand Latinas’ perspective on their
science self-efficacy in CS. Volunteers had one week to return signed letters of consent to their
participating teacher, which were collected at the end of the week. A total of five students were
selected for the second phase of the research representing both instructors.
Instrumentation

Survey
The preliminary investigation used an abridged version of HSLS:09 (Duprey et al., 2009)
(see Appendix) to establish self-reported levels of science self-efficacy in CS courses at SHHS.
Surveys are an excellent means of gathering individuals or societal knowledge, feelings, values,
preferences, and behavior (Fink, 2013). In the Fall of the 2018-2019 school year, participating
students had access to the digital survey, available on qualtrics, which included questions
divided into three categories: student background, science self-efficacy in CS, and perceived
utilization of CS (see Appendix C). Prior to administering the actual survey, a pilot test of the
survey was conducted to ensure the clarity of the language. As Fink (2013) supports: “A pilot
test is a tryout…self-administered questionnaires depend heavily on the clarity of their language
and pilot testing quickly reveals whether people understand the directions you have provided and
if they can answer the survey questions” (p. 7). Moreover, pilot testing is likely to ensure a
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 45

higher response rate, to maintain the focus of the survey and to ensure that information collected
is what we need to address research question number one. To ensure a high response rate,
questionnaires were completed online during students’ respective CS class. Participating
teachers provided a link to the qualtrics survey and were asked to assign the survey to students
on their google classroom webpage. Participants were reminded of the anonymity of their
responses to the survey, and their participation in the study, and that their identity would be held
confidential in accordance with the IRB regulations. The survey also used a Likert scale to rate
their responses from “Strongly Agree” to “Strongly Disagree.” The self-administered online
survey was given only once in the Fall of 2018 to all groups of students meeting the
aforementioned criteria: Latinas enrolled in a CS at SHHS.
The study utilized the questionnaire from the HSLS:09 (Duprey et al., 2009) to
quantitatively measure students’ self-efficacy in science. The longitudinal study was the fifth in a
series conducted by the National Center for Education Statistics (NCES); and starting in 2009, it
followed the experiences of 21,000 ninth-grade students, from across 944 different schools
across the United States, through high school, postsecondary education, and beyond. The NCES
established the Secondary Longitudinal Studies Program aimed at the study of the educational,
vocational, and personal development of students at various stages in their educational careers
and to explore the personal, familial, social-cultural, and institutional systems that may affect
that development. In sum, the five studies provide key insight relevant to this study as it
describes students’ experiences in secondary, postsecondary, and beyond from the last five
decades, 1970s, 1980s, 1990s, 2000s, and 2010s–and posit underlying correlates of educational
success in the United States. This study utilizes the most up to date, follow up information from
2018, which is based on the HSLS:09 base year. The fifth iteration of the study utilized a survey
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 46

focused on STEM education, which this study borrows. The study gathered general background
information from participants such as demographics, previous school experience, current school
experiences, with an emphasis on math, science, home experience, and future postsecondary life
and educational expectations. HSLS:09 is a generalizable study in which students are the
primary unit of analysis, with a nationally representative sample of schools, and in which
parents, science and math teachers, school counselors and administrators also completed surveys.
Four questionnaire items were used by HSLS:09 to assess students’ science self-efficacy;
students were asked to rate how confident they felt in their ability to do an excellent job on tests,
to understand the most difficult material presented in the textbook, to master the skills being
taught, and to do an excellent job on assignments in their science course. Using these questions
as a template, this study built upon HSLS:09 to accurately evaluate Latinas’ perceived level of
science self-efficacy in CS, and CS utilization. In order to measure self-efficacy, this study
asked students to rate statements such as: I am confident I can do a good job on the assignments
in this computer science class, or I am confident I can do a good job on test in this computer
science class. In total, seven statements were used to assess Latinas’ level of science self-
efficacy. CS utilization was measured by asking respondents to consider such statements as: I
think the computer science course will be useful to my career or I think the computer science
course will be useful for college. In total three statements were used to determine students’
perception of the utilization of CS.
Interviews

The best approach to address the research question was the semi-structured procedure,
which utilizes an interview protocol guide (see Appendix G). The guide was developed to
evaluate underlying cultural themes related to participants and their perspective toward computer
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 47

science. Semi-structured interviews were conducted one-on-one, face-to-face, and in-person with
a small selection of Latinas from the sample student population. An advantage to this type of
method allows participants to provide historical information, clarifying statements, and follow-
up statements. The semi-structured process allows researchers to control the line of questioning.
However, as noted by Creswell (2014), some of the limitations to this methodology process
include: information being filtered through the views of the interviewees, information is
provided in a designated place rather than the natural field setting, the researcher’s presence may
bias responses, and not all people are equally articulate or perceptive to the information
provided. Although using closed-ended questioning makes it easier to score and code, the
limitation with this design is that it limits respondents to a preset response and fails to give them
an opportunity to state their respective position in their own words (Fink, 2013). In addition,
constructing closed-ended questions has the limitation of all respondents not interpret the same
questions the same way. Potential weaknesses using a guided approach to interviews is that
salient topics may be inadvertently omitted. In addition, the flexibility with this interview
approach may result in different responses, and consequently reducing the comparability of
responses (Johnson & Christenson, 2015). To address these limitations, the interviews were
semi-structured to guide the process, but still allow respondents the freedom to discuss and share
their perspective.
This section discusses key components of the interview guide, as well as its advantages
and disadvantages. A semi-structured interview process approach (Patton, 1987) was chosen
because the outline using this method ensured for a more comprehensive data rich collection and
allows for a systematic interview process with each respondent (Johnson & Christensen, 2015).
According to Patton (1987), this approach does lend itself to flexibility in the sequencing and
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 48

wording of questions, which can result in greatly differentiated responses, and therefore, reduce
the comparability of those responses. However, the protocol structure allowed for a deeper
exploration of students’ meaning and understanding as each interviewee gave their own
perspective. In trying to understand students’ perspective for our research question, it was
important to ask students deeper questions about how they would describe their previous
experience with CS. When opportunities arose during an interview, to make a stronger
connection to the research question, a more detailed line of questioning lent itself to exploring a
respondent’s deeper meaning and perspective on the topic. Specifically, it allowed for exploring
key concepts such as their experiences with role models or the lack thereof, and their perspective
of what makes for a quality instructor. There are several components of semi-structured
procedure, of which the interview protocol guide and questions are key. The purpose of an
interview protocol guide is to facilitate interviews, and in general, maintain the focus of the
interview to ensure relevant data is gathered to address the research question. In order to elicit a
useful response, “the key to getting good data from interviewing is to ask good questions” (p.95).
The interview questions were linked to the research question and built upon the survey
questionnaire. Questions were open-ended, non-leading, and inductive overall.
Observation

In order to take accurate, firsthand account of participants’ day-to-day experience in CS,
observation of Latinas in their natural setting provided the best means to capture the data. As
stated by Patton (1987), the purpose of observation is to describe the people, program, and
processes thoroughly and accurately. The strength of this approach is that the data is collected in
the field where the action is taking place, allowing the evaluator to better understand the context
and the environment. In addition, this method allows for the researcher to record firsthand
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 49

experience, along with the participant, as the events occur. As Creswell (2014) notes, the
shortcomings of this method, include the fact that the researcher may be seen as intrusive, and
may not be adept at attending and observing skills.
The focus of this study was the perception of female Hispanic students’ self-efficacy in
science, therefore, observations were conducted as a nonparticipant using an observation
protocol (see Appendix E) exploring how their self-efficacy is defined and reinforced in the
classroom. Utilizing the protocol, the visit focused on three main foci, the physical space, and
the social and educational experience. An observation protocol was created (see Appendix F) to
focus the data collection and ensure the overall research question is addressed and the main areas
of focus are kept in mind. The first focal point spotlights students physical space within the
observed classroom including proximity to the teacher, a relative location within the classroom,
and distance to students that are frequently off task. The physical space may provide insight into
the sociocultural challenges Latinas have in science classes relative to research question two. A
drawing of the classroom (see Appendix F) was created to ascertain participant’s physical
relation in the CS classroom. The second focal point looks more at the interactions between
Latina-Latina, Latina-Latino, Latina-Non-Latina/o peers, and Latina-teacher. Observing the
social interaction with peers, both of the same ethnicity and genders, but also the teacher-student
interaction has been shown to play a major factor in the development of students’ academic self-
concept (Kim & Sax, 2014). The correlation between academic self-concept is directly related to
student achievement and persistence in STEM. Lastly, educational quality, which has been
suggested to be the largest factor impacting students’ self-efficacy was evaluated using the
observation protocol. Looking at students’ level of engagement, types of questioning, and length
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 50

of time on activities, the quality of experience was ascertained and followed up with interview
questions.
Data Collection Approach

All females currently enrolled in a CS course at SHHS during the fall semester of the
2018-2019 school year were eligible to participate in the survey. Based on current student
enrollment, roughly 160 responded to the survey across all sections of CS from both instructors.
For comparison purposes, the survey was given irrespective of grade-level, race/ethnicity, or CS
course.
Interviewees were purposively chosen to represent the various subpopulation of Latinas,
specifically having a representative from different grade-levels as well as from different CS
classes. Participants for this phase was selected from both instructors. Interviews were conducted
after in the library workrooms.
A one-hour observation was taken as a complete non-participating observer in Ms. O’s
fifth-period AP CS class. Observations were conducted overtly, with full disclosure of the
purpose of the study with participating teacher exclusively and were narrowly focused on
Interviewees; specifically, Interviewee-Teacher dynamic, Interviewee—physical environment,
and interviewee-social environment. A sketch of the classroom was composed including
reference to Ms. O, Interviewee A, Interviewee B, and Interviewee C locations. Over the course
of the observation, I positioned myself equidistant from all Interviewees as to better record
descriptive field notes. Detailed notes were taken during observations with a time stamp included
roughly every fifteen minutes. Table 1 below summarizes the characteristics of all participants
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 51

for the qualitative phase.

Data Collection

Data collection occurred in two parts. For the quantitative phase, respondents were
exclusively Latinas. The sample size was determined based on the research site demographics
and the current number of enrolled Latinas in CS at SHHS. Currently, there are two CS
instructors at the site, each teaching five computer science classes. Ms. O teaches one section of
AP CS, one section of hypertext markup language (HTML) class, and three sections of a tech
class. Mr. S teaches all five periods of the tech class. AP CS and the HTML classes are both
year-long, elective classes, whereas the tech class is a mandatory semester-long class that all
ninth-graders are required to take. Based on the class roster, approximately 160 female students
were surveyed.
Interviewees for the qualitative phase were selected across both instructors’ classes. The
sample size was determined, in consideration with, and under the advisement of the dissertation
committee, to be adequate in addressing the research questions for this study. Five students were
selected in total; three from Ms. O’s AP CS class and two from one of Mr. S’s Tech classes. The
interviews were recorded on personal iPhone voice memo app and then uploaded and transcribed
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 52

on www.Rev.com. In order to ensure confidentiality, participants’ names were not recorded.
Instead, subjects for the qualitative phase were designated student A-F. Observation was
conducted in Ms. O’s AP CS class.
Data Analysis
As Maxwell (2013) suggest, data analysis started immediately following data collection
rather than in summation. Each phase of the study, both quantitative and qualitative databases,
were analyzed separately. To accurately measure students’ science self-efficacy in CS and
address research question one, results of the qualtrics survey were exported into a data analyzing
program called Jasp. A descriptive and regression analysis test was run to quantitatively establish
Latinas’ science self-efficacy in CS, and their perceived level of CS utilization. For comparison
purposes, Hispanic and non-Hispanic results from the survey were also assessed.
Interviews and the observation were used to address research question two and discover
potential factors influencing Latinas’ science self-efficacy in CS. After each interview which
was audio recorded, the initial interpretation was jotted down and subsequently transferred to
data. First impressions and general feelings about the respective interviews were noted, but
categories or emergent themes were not gleaned at this stage of data analysis. During the
nascent stage of data analysis, a day after participants completed interviews, audio files were
listened to as used as the first opportunity to develop categories and establish emergent themes.
Following this initial stage of analysis, interviews were transcribed a using NVivo software. The
data was analyzed and codified into categories and subsequently developed into broader themes
during second round coding. Maxwell (2013) distinguishes between organizational categories
and substantive (theoretical) categories, and suggests using the latter rather than the former.
Whereas organizational categories may reflect a researcher’s paradigm, the benefit of using
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 53

substantive categories is that it utilizes the data collected to glean categories reflective of the
participants’ beliefs and capture the data beyond the conceived organizational categories of the
researcher (Maxwell, 2013). This study used substantive categories to develop emergent themes
and capture participants’ own words and concepts.
Similarly, immediately following the observation, initial impressions were jotted down.
First impressions and raw data collected from the observation and used to shape the categories
and emergent themes in the overall analysis process. Special attention was paid to the potential
environmental factors that may be influencing the participants’ science self-efficacy in the class,
such as demographics, physical environment, perceived teacher quality, as well as social factors.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 54

Chapter Four: Results
Introduction
This chapter presents the findings based on the data collected from student surveys,
interviews, and observation. The focus of this study was to explore a deeper understanding of the
self-efficacy of high school Latinas, and the factors that contribute to their perception. The
research questions used to explore this topic are:
1. How do high school Latinas in an urban public high school perceive their science
self-efficacy in computer science?
2. What factors influence the science self-efficacy perception of Latinas in computer
science?
A one-time online self-administered survey was used to quantitatively address the first
research question and determine students’ perceived level of science self-efficacy. Qualitatively,
observation and interviews were used to examine the second research question and explore
potential factors underlying the development of Latinas’ science self-efficacy. Results of the
survey indicated that Latina students had a lower level of confidence in their science self-
efficacy in CS when compared to non-Hispanic participants. Results of the interviews and
observations suggest a distinction in level of self-efficacy between students in the mandatory
ninth-grade tech class and those students that are in AP CS. Sources of self-efficacy appear
consistent with literary findings; however, three key findings were noted: 1) there appears to be a
relationship between a growth mindset to the level of self -efficacy in CS 2), being a Latina in a
male-dominated field such as CS brings added pressure to students to prove their competency to
parents, 3) male role-models appeared to have an equal or greater impact than female role
models on the development of participants’ self-efficacy in CS.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 55

Findings

Examining self-efficacy in science at various levels on the STEM pipeline has had mixed
results depending on academic level and subject matter. Studies at various levels reported
women having a lower self-efficacy in computer science compared to their male counterparts;
whereas other studies find their levels to be the same. The scope of this study was focused on
high school Latinas’ science self-efficacy in CS. To address research question one, and ascertain
how surveys were given to females currently enrolled in a CS class irrespective of ethnicity or
grade-level. Table 2 below outlines the seven survey statements.

Of the 157 total respondents, 129 (82%) identified themselves as Hispanic; the remaining
28 (18%) were non-Hispanic. The vast majority of surveyees, 139, were from the ninth-grade
Tech class, and the remaining students were split across the AP CS and HTML class. The ninth-
grade Tech class is a mandatory semester-long course; whereas, the AP CS and HTML classes
are electives. The compulsory versus elective nature of CS courses at SHHS explain the skewed
representation. Seven statements, 2.1-2.7 were used to assess self-efficacy perception in CS. The
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 56

descriptive statistics in table 3 below break down the results of the self-efficacy questions by
Hispanic = 1, and non-Hispanic = 0. Table 4 below summarizes the means of respondents
revealing that Latinas in high school have, overall, had a slightly lower science self-efficacy in
CS compared to non-Hispanics. On the seven self-efficacy statements, Hispanics had a mean
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 57

score of 3.57; whereas non-Hispanics had a mean score of 3.66 a mean difference of only
0.086. An independent t-test analysis indicated the difference amongst the responses is not
statistically significant as shown in table 5. The p value for all statements were over the
acceptable 0.05.
Therefore, we fail to reject the null hypothesis that Hispanics and non-Hispanics show
any statistical difference. If we disaggregate the data by grade-level, and just look at the overall
mean for each statement, we can see that seniors in AP CS had a higher confidence compared
with ninth-graders in the Tech class. The below table summarizes the results per each statement.

Students in the Tech class are exclusively ninth-graders; whereas most of the students in AP CS
were seniors. In terms of race, the results of our study were inconsistent with a nationally
represented survey conducted by Gallup in 2016. Figure 3 was taken from the results of the 2016
Gallup survey for comparison purposes and shows that Hispanic students were less confident
than Black and White students in their ability to learn CS.

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 58

What is interesting to note from Figure 3, is that Hispanics showed the highest level of interest to
learn CS compared to other groups measured, but had the least confidence to learn CS. Although
the Gallup survey did not desegregate the data by race and gender, it did measure them
separately. Figure 4 below compares male versus females’ level of confidence in CS.
Figure 4. (Gallup, 2016) Confidence to learn CS across CS.
Figure 3. (Gallup, 2016) Confidence to learn CS across gender.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 59

Factors undergirding SE of Latinas in CS

Interviews and an observation were used to address research question two and explore
potential factors that may be undergirding current demographic patterns in CS. Using NVivo 12,
the five interview transcripts were coded into three emigrant nodes during first round coding
process: role models, environmental factors, and motivational factors. Subsequently, these nodes
were then broken down further into more narrow themes.
Role Models

Based on the body of research, one recommendation that was frequently reported called
to increase the overall number of female role models in STEM. Adding more female CS
instructors is a step in the right direction, but as noted by Cheryan et al. 2017, what is likely to
have more of an impact is finding quality instructors that are relatable. Examining table 7 below
shows that students A-C, the ones taking AP CS, all had experiences with a role model. Students
D and E, from the mandatory tech class, reported not having a single role model in relation to
CS. Analyzing the disaggregated data also reveals that there were higher instances of
participants reporting a male role model influencing their motivation to persist in CS. Student A
shared the influence her middle school STEM teacher had on her: “He's motivating me more.
He's showing me how not just men could be in the course. He's not just saying, 'Oh no, you can't
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 60

do this [CS], or something. He's actually helping me to be more into the course.” Student A
highlighted him as her inspiration and role model for continuing in the STEM pipeline. She
explicitly recalled his words of encouragement, validation, and support. This was similar to the
role model student C referenced during her interview, as she recalled an experience with her
father. When asked about a particular moment her role model inspired her, she recounted:
I guess it would be when my dad works on the computers, he tries to find a way...We had a
computer, and he was trying to connect it to the TV, and he was looking for a lot of stuff, and
then after a while, he figured out what cables to use and what to get so that we could just put
something on the computer and then it would appear on the TV. I don't know, I just really liked
that because I'm like, ‘Oh, that's really cool.’ In contrast to the explicit sentiments student A
referenced with her middle school instructor, student C talked about the implicit experience she
had with her father. Although nothing was explicitly stated about student C going into STEM,
watching her dad fix the computer had a significant impact on her persistence in the STEM
pipeline. None of the remaining participants noted a role model, but student B did acknowledge
that having a role model would have made a difference. As she states “I think it would because it
would have helped me gain more confidence in the career because nobody in my entire family
knows about computers.”
Environmental Factors
early experience.
The category of environmental factors was mentioned most frequently amongst
respondents as seen in table 8 below. The category included such things as a classroom
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 61

environment, parent perception about CS, early exposure opportunities, and stereotypes.
Although two respondents actually recalled an opportunity to be involved in a CS-related STEM
course, student A was the only one that took the course. As she recounts her experience early
on, “Like I said, middle school, when we were building the computer, the monitor, it was so fun.
It was great, it was like, ‘Oh my gosh, these pieces go here. Oh my gosh, this helps this do this.’”
Both students A and student E discussed the significant impact of being exposed to CS early.
When student E was asked her perception about reasons why CS is a male-dominated field, she
referenced back to an early opportunity to take CS. As she states:
I think 'cause like we're not really exposed to it, or like ... 'cause I remember in
elementary it was only boys who wanted to do it 'cause they never really gave us a brief
understanding of what it was. So I think if they would have told us more about it and
kind of gave us a little demo or presentation about it, we would probably do it because I
enjoy it.
Only one out of the five interviewees noted experience prior to taking their current CS course,
which was consistent with previous research that found insufficient early exposure as a factor in
women’s likelihood to go into CS, (Cheryan et al. 2017). Moreover, the findings were validated
by a 2016 Gallup study which found that teachers think “a lack of exposure is a major reason
why women and racial and ethnic minorities are underrepresented in CS fields” (p. 4).
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 62

parent perception of computer science.

Previous research has found that when students are encouraged by either a parent or
teacher, they are three times more likely to be interested in CS (Gallup 2017). The findings
underscore the significant impact parent and teacher perception has on students’ representation
and interest in the field. Parent perception reflected cultural stereotypes about gender roles and
influenced the prospective students towards CS. For example, when referring to her parents’
perspective of gender roles, student A states, “men should be in computing and stuff and women
should be in dancing or something.” Similar gender stereotypes from parents were discussed by
student B, when she talked about how her parents “mostly a lot of males on TV, like designing
programs ... "Oh, why are you wasting time on that [computer science], when you could be
focusing on going into a different major, like going into nursing.” Student D exclaimed her
parents haven’t explicitly stated their dismay towards her in a CS course but believed they would
be "Oh, girls should clean and boys should do the more mainly stuff and take out the trash."
Student E had a similar experience with her siblings in Mexico, stating “Oh, that's a man's job,"
like to go outside and go to like a working field where it's ... like working on cars. Like that's a
man's job. Like women can't do that.” The cultural beliefs of the parents, as well as other family
members, reinforce perceived stereotypes about CS, and consequently, interest in the field. Not
only did the study reveal the stereotype beliefs of family members, but two of the respondents
discussed hearing explicitly discouraging remarks questioning their decision to go into CS.
Student A recounts her mom second-guessing her decision to take a CS class: "‘You're in
computing?’ She's like, ‘Are you sure you could do that class?’” Similarly, student B recalled
when she told her mom about taking AP CS, and her mom said, "Oh, you're going to do that, but
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 63

you're just wasting time." Although the two students acknowledged how their parent’s comment
hurt, they discussed how they used their words as motivation.
All five of the students discussed the positive and supportive influence the classroom
environment has had. This theme included teacher quality and support, classroom demographics,
tutors, and peer support. Those students in the more advanced AP CS acknowledged the impact
walking into a predominately male classroom had on their self-efficacy; however, in the
introductory tech class where the demographics are more balanced, student D and E stated the
class demographics was inconsequential. Student B described the experience as “intimidating,”
and student C described being “scared.” During the observation, student A took the lead as she
grabbed the marker and started facilitating the direction of the group asking questions about their
project. Members of the group were both Asian females and appeared supportive as they
collaborated with student A. Similarly, during the observation, student B worked collaboratively
with her male partners. The interaction appeared respectful and supportive as students discussed
their projects. There was no noticeable difference between the interaction between groups.
Throughout the lesson, the instructor walked around constantly and made her way to each group
to answer questions and provide clarifying instructions. The college tutor assigned to class
walked around with the instructor and worked one-on-one with groups. The supportive and
respectful interaction within the groups matched what interviewees described. Due to the
supportive classroom environment of her peers, the instructor, and the tutor, student B reflects on
how her self-efficacy started to change even though she was initially intimidated. As she
recounts, “it changed a little bit towards the middle because they were not as intimidating
anymore, because we were all on the same level of learning the coding. So it was not that
stressful anymore.”
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 64

Motivation

Of all the three emergent themes, motivation was cited most frequently, with a total of 55
comments referencing sources of motivation including family, societal beliefs, and individual
perspective. This theme was the only one that was mentioned by all five interviewees. In
looking at table 9 below, you can see that students A, B, and C, had a higher overall number of
motivational sources; whereas students in the mandatory tech class had fewer sources of
motivation. All respondents acknowledged societal factor as an influencing source to their
motivation. Multiple participants talked about in spite of CS being a male-dominated field, and
how they saw that as a challenge. For example, Student A recalls “ It didn't impact me. It was
like, why aren't there more girls here, because that means we have to step it up as girls. We have
to be more involved in computers. We have to show how we could be here in this class and pass
it and be successful in computing.” This echoed the words of student C:
In a way, it made me want to take it more because I feel like girls should go more into it.
I know it is a male-dominated field and I want to go into engineering, which is also male
dominated, so it makes me want to take it because I think girls can do as much as men.
Student B discussed and identified societal barriers such as cultural stereotypes, expectation,
societal perception of women in computers, and a lack of relatable role models. However,
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 65

despite these barriers, her self-efficacy has helped her overcome the challenges. As student B
proclaims, “I'm kind of hesitant at the same time, but I still strive to go forward because even
though it's mostly males, a female could still do it.” Although all students acknowledged the
impact cultural and societal obstacles play on their self-efficacy and persistence in CS, all three
interviewees in AP CS voiced strong confidence and high science self-efficacy; they believe in
their abilities and are willing to move forward in the STEM pipeline.
Other factors that influence student motivation are the support and belief of teachers and
family members. The finding has been substantiated by previous research which highlighted the
significance behind having a relatable instructor that was often been interpreted as a solution to
URMs in CS by increasing the number of female or women of color teaching CS classes. To the
contrary, one key finding from the study found that male instructors acted as key motivational
pillars for some and provided a higher level of motivation than a female instructor. Student B
discussed the influence of her male teacher on her science self-efficacy as previously mentioned.
In addition, student C had previously mentioned the impact her father had on her motivation to
develop an interest in CS when she discussed the implicit motivational actions of her father
fixing computers at home. As mentioned previously, the support and motivation those nearest to
a student can play a significant impact on their likelihood to continue along the STEM pipeline.
These actions can be explicitly expressed as in the case of student B or implicitly as in the case
of student C viewing her father; nevertheless, these findings underscore and validate the role
males can play in motivating females and other URMs to entering the field.
Of the three sources of motivation, the highest source came from individuals themselves
and their mindset. All five participants made reference to the role their own motivation played on
their self-efficacy with the highest number reported from students in the AP CS class. All
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 66

students showed evidence of a high self-efficacy in the course, supported by their own
motivation to succeed. This was evident as student A reflects on her self-talks, she states
“should I even be in this or should I just go take other courses, try out something else.
And I'm like, what do I see myself in, in a few years? And then I'm like, I see myself in
computers.” She went on to explain a source of her self-motivation and confidence in the course:
“I just need to get more of a hang of it.” Student B mentioned a similar source: “It doesn't matter
for me if I'm confident or not because I know I'll improve. Because when I improve I feel like I'll
gain that confidence to do more.” Their responses emphasized a key finding: both responses
exhibited a growth mindset in their belief that even when the work gets difficult, they just need
to keep practicing and that their effort will help them get better. A growth mindset may be
independent of the course, but incorporating growth mindset practices in the CS classroom may
play a significant role in the motivational and self-efficacy of Latinas and other URMs in CS.
The confidence and high self-efficacy of students A-C were substantiated during the
observations as they actively took the lead during their group projects. They displayed
confidence as each of them interacted with both male and female peers. They displayed
leadership skills as they guided the group through their project.
The other respondents in the AP course had similar perceptions of their motivation. For
example, student B states, “even though it's mostly males, a female could still do it,” and student
C opines “I feel she [her CS teacher] has influenced it but then again, it's also part of me...I
myself am interested in that. I've always been interested in tech stuff.” Both students from the
introductory Tech class mentioned their perception of boys’ interest in the class as a reason why
they’re able to learn the material quickly. On the other hand, students in AP CS had a stronger
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 67

response frequency to this theme, and not only discussed their personal interest as an intrinsic
motivating factor, but also felt they had more to prove. Student A talked about the need to
“prove that women could be in engineering, [or] in any type of field that involves computers,
[or] maybe mechanics,” and expressed her belief that “women could be part of any field; not just
because they're a woman, can they not be in computers.” This was similar to student B, who
talked about her fear and hesitation being in a male-dominated classroom, but found motivation
in her individual success. She states “Yeah, kind of, knowing that I could actually do it just like
the males, kind of motivates me.” Student C also mentioned that she had something to prove,
when she talked about how because the CS field is seen as a male-dominated field, motivated her
more to succeed and prove that girls can make it in the field just well as a man.
Although student B displayed a high science self-efficacy in the class, she did discuss a
negative side-effect of being a Latina in a male-dominated field. One key finding from this
study, expressed by student B, was the added pressure she felt to succeed in the class. As her
parents’ only daughter, student B discussed feeling pressure to prove her ability and competency
to her parents who weren’t supportive of her taking CS classes. Her parents would like her to go
into a field that is more traditional for females, such as nursing or teaching. Previous research
has talked about the pressure URMs experience in the CS field; however, this has never been
explored with the focus on the pressure students feel from family members.
Chapter Summary

The Gallup survey of 2016, showed a demand for CS, but it also denoted the disparity in
confidence to learn CS across gender and race. Research question one of this study looked at
quantifying the science self-efficacy of Latinas in CS at the high school level. Results indicated
no statistical difference in confidence levels between Hispanic and non-Hispanic female students
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 68

in CS at SHHS. Table 6 showed that across grade-level, science self-efficacy increased the more
experience students had with CS. All respondents enrolled in AP CS were seniors; whereas,
those enrolled in the Tech class were ninth-graders. The difference in confidence level may have
been expected based on the course requirement structure at SHHS, which affords seniors an
early exposure to CS in ninth grade. Since all students are required to take the Tech in ninth-
grade, respondents are representing students across a spectrum of interest and motivation
towards CS. This is likely different from the representative sample of students in AP CS. Since
AP CS is an elective course, all respondents would likely have a higher interest and motivational
level to learn CS compared to those in the Tech course. Consequently, students in AP CS would
likely rate their level of confidence and self-efficacy higher than those that are forced to take CS
in the Tech class. The disproportionality of self-efficacy in CS was apparent during the
observation and interviews phase of the study.
Research question two looked at investigating the circumstances around the development
of a Latinas’ science self-efficacy in CS. Previous research has quantitatively explored internal
and external factors related to the development of a student’s confidence level in CS. This
study’s findings were consistent with previous research; however, one salient point was the
growth mindset of students in AP CS. Students in AP CS demonstrated a propensity towards a
growth mindset. This may explain the unequal confidence levels on the survey and the higher
rating of their self-efficacy overall. Signs of a growth mindset were seen in the respondents
enrolled in AP CS–students A-C. To date, studies tend to focus heavily on external factors, such
as parent perception of CS, role models, classroom environment, and teacher quality, and when
exploring the internal variables, the literature has focused on how the external factors about CS
may influence a person's motivation to stay in the field. The research findings in this study
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 69

suggest that fostering a growth mindset in the CS classroom, especially in the early grades where
the exposure is compulsory, may be a preliminary condition to allow for the development and
sustainment of a student’s self-efficacy.

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 70

Chapter Five: Discussion of Findings

As the population of the United States continues to diversify, and our economic
dependency on STEM grows, ensuring equal access, and equal representation in all fields of the
STEM pipeline, is essential to the progress of our nation. Data from the most recent Gallup
(2018) survey on CS trends in the U.S., has empirically shown the gender, race gap in the field,
but has also shown the perceived need, and overwhelming demand, of students, parents, and
teachers to have more or better access to CS programs. Previous research has discussed the
urgency and the need to develop pathways for URM groups and subgroups. Large scale federal
aide initiatives, such as CS for all, have been mobilized; however, current research findings have
suggested there is a need for careful consideration of the underlying factors inhibiting access to
certain STEM fields. This study focused specifically on exploring factors that contribute to the
underrepresentation of Latinas in the CS field, and more narrowly, on what prevents this
subgroup from entering the field pre-college. The study quantitatively measured the self-efficacy
of Latinas in a CS class at the high school level, as well as, explored sources influencing their
science self-efficacy in CS.

Discussion of Findings

The findings overall were consistent with previous data and current research in the field;
however, three key findings emerged from the study:
● Latinas currently enrolled in AP CS showed evidence of a growth mindset
● Latinas currently enrolled in AP CS felt immense pressure to succeed and prove
their competency in the field in the absence of familial support.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 71

● Male role models appeared to have an equal or even greater impact on influencing
Latinas to go into CS.
The theoretical framework looked at the research question through a social-cognitive
learning theory lens, focusing on self-efficacy, which assumes mastery experience in the field as
its greatest source. In analyzing the interview data, it became apparent students in AP CS were
all talking from a growth-mindset. The current model used in this study was adopted from the
Cheryan et al. (2017) meta-analysis which outlined three factors that contribute to the
underrepresentation of women in certain STEM fields The scope of this model presented is
specific to a given field. Although the model is transferable to any given field, such as CS, it
presupposes that the factors contributing to women’s underrepresentation are exclusive to the
field. A growth mindset, as noted in the literature review, begins to be established even before a
child enters a classroom, let alone a CS classroom. Growth mindset is the belief that through
effort and determination a person can become better at something (Dweck, 2007); whereas, self-
efficacy is the belief and confidence one has in their ability to learn and produce desired
outcomes (Bandura, 1997). A study from the University of Chicago Consortium on Chicago
School Research (CCCR) found four important beliefs that make up academic mindset, a sense
of belonging, self-efficacy, purpose, and growth mindset. Both self-efficacy and growth mindset
have been found to be influencers on a child’s academic perseverance and tenacity. The two
conceptual frameworks are different from one another; however, they are closely interdependent
(Farrington, Roderrick Allensworth, Nagaoka, Seneca, Johnson, & Beechum, 2012).
A striking similarity begins to emerge when comparing the sources of mindset to the
Cheryan et al. (2017) factors that undermine the representation of women in certain STEM
fields. Stereotypes, bias beliefs, and praise from a role model are mirrored in their representation
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 72

in both models. Women with a fixed mindset and who are bombarded with the male culture
stereotypes about math and CS being fields that require innate abilities are less likely to choose
those fields, which results in their low representation. This would suggest that sources of self-
efficacy is not specific to CS or a particular field and can be influenced even before a child
enters the classroom. Simply praising a child’s ability or intelligence dissuade a child from
having a growth mindset as research has shown. Instead of praise from parents, teachers, and
other students that focus on being smart or not at a subject or field, reinforces a fixed-mindset.
Minoritized students entering into these underrepresented fields with pre-existing stereotypes
about the field itself; however, as the research suggests, they also have pre-existing beliefs about
their own abilities that predispose them to develop handicapped science self-efficacy in the field.
In addition, previous initiatives looked at bolstering the number of women in the field by
increasing the number of female role models and instructors; however, as Cheryan et al. (2017)
revealed, simply increasing the number of female role models in the field is not enough and not
likely to produce the intended outcome. Rather, the focus, as they recommend in the study,
should be on having instructors or role models that are more relatable to URMs. Consistent with
those findings, few women made reference to female role models in this study, and those that did
mention a role model, discussed the significant impact male teachers and fathers had on
influencing their science self-efficacy in CS. As student B discussed, having a male teacher tell
her she was good at computers, validated her confidence in the field more than if it had come
from a woman. She perceived him as the expert, and when the expert in the field told her she
was good, it had more of an impact. The finding suggests that males can be key figures as role
models as equally as females in the development of female students’ science self-efficacy.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 73

The body of literature has discussed several stereotypes experienced by Latinas and other
URMs in male-dominated fields. This included feeling added pressure to prove their competency
more than men do in the workforce. However, this pressure to prove their competency goes
beyond the workforce, and as this study’s findings suggest, it is also associated with cultural and
family beliefs. Student B talked about how taking classes in a male-dominated field like CS, and
not having that parent support, adds more pressure on her to succeed in order to prove her
competency and to show her parents that she can be as successful as any male.
Limitations

Using purposive sampling, we are not able to generalize our results to our population
(Johnson & Christenson, 2015). The study used respondents from my own site as participants in
the study. Although measures were taken to not select any student that may have any prior
relationship with me, such as student-teacher, the study could not account for the possibility that
respondents may have had a sibling or best friend in my class. Moreover, for the quantitative
phase of the study, close-ended questions were used for the Likert scale survey. Although using
close-ended questioning makes scoring and coding easier, this design limits respondents to a
preset response and fails to give them an opportunity to state their respective position in their
own words (Fink, 2013). Lastly, as a white male, high school teacher conducting research and
interviewing Latina students, I acknowledge the potential influence and bias of my own
upbringing. Students may have answered differently as they perceived me as an authority figure
despite reassuring them of the confidentiality of their responses.
Implications of Practice

Though the study is not generalizable, its findings have wide-reaching implications in the
STEM field. As we move towards a more inclusive workforce, understanding the factors that
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 74

reproduce gender and racial disparities in certain STEM fields becomes essential towards the
progress and success of creating a more racial and gender-balanced STEM pipeline.
Understanding the historical, cultural, and environmental factors that undergird Latinas’ mindset
and subsequent science self-efficacy in CS, is a nascent step to a more equitable CS field. These
steps can then be applied to other URMs in other fields. The Cheryan et al. (2017) meta-analysis
found the underrepresentation of minoritized students in CS as attributable to poor recruitment
efforts, rather than practices that fail to retain students in the field. The attrition rate for women
in the field of CS is comparable to biology (Ceci, Ginther, Kahn, & Williams, 2014). This was
supported by the research findings in this study, in particular, the message student E gave when
she talked about a missed early opportunity to take a tech class. She recalled missing a key
opportunity to take a STEM course in elementary school because of the lack of knowledge about
what it is. The findings suggest that it’s not enough to create equitable opportunities to engage in
CS learning for Latinas, but specifically targeting URMs and females, requires thoughtful
consideration about how to relate the field to them early on. Meaningful recruitment processes
must consider the target audience and not cast a wide uniform net in the hopes of getting a
represented sample of the population. Elaborating on what CS is, and the opportunities available
irrespective of race or gender, will empower women and URMs to make informed decisions.
Without educating students on what CS is and is not, students are left with a
preconceived, myopic predilection of the field based on stereotypes and the assumptions of how
others view the milieu. These predilections about the field, coupled with pre-existing beliefs
about one’s own abilities, that may, or may not, be supported by the home environment, coalesce
to a tenuous situation for Latinas in the CS field. As a result, Latinas and other URMs continue
to be left behind, reproducing the inequality in certain STEM fields. Previous research
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 75

emphasizes the urgency of understanding the barriers that inhibit women from first entering the
STEM pipeline in a particular field as the direct way to increase their numbers in that field. This
study explored possible barriers inhibiting Latinas from entering the CS field. Findings from the
study were aligned to current research conclusions. However, this study found that Latinas
taking a CS course felt added pressure to succeed as a means to prove to their non-supportive
family that a female could succeed in the field. As student B said, “I felt pressured because I'm
the only child in the family so I feel like pressures on me even though they're not so concerned
with it [CS success], I still feel pressured to do good.” Although not previously mentioned in the
literature, the unspoken source of pressure Latinas face connects to the Cheryan et al. (2017)
warnings. Their caveat hastens the influx of females and other URMs into the CS field without
careful consideration of the culture females and other URMs are likely to experience in the field.
As they mention, increasing the number of females in the CS field can potentially exacerbate the
disparities by merely reproducing the hegemony of the field. Meaningful dialogue must be had
about the male-dominated field in order to shift the paradigm of CS. Stereotypes, biases,
prejudices, and cultural opinions and beliefs must be heard and addressed and not be simply
assumed that these things will address themselves. Quality instructors that know the curriculum,
and are relatable to the student population, must be able to have an authentic conversation about
the field itself, but more importantly, about what it is like to be a minority in the CS field.
Conclusion and Future Research

Future studies must explore the correlation between Latinas and other URMs in CS and
their growth-mindset. This study’s findings suggest a potential relationship between a
minoritized students’ mindset and likelihood to enter into CS. Building on this finding, new
studies may explore other underrepresented STEM fields, such as physics or engineering and the
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 76

correlation between minoritized students’ mindset and self-efficacy or likelihood to persist in the
field. In addition, future research must explore the impact male, versus female, role models have
on science self-efficacy. As previously mentioned, role models play a major factor in the
development of a person’s self-efficacy; the research finding in this study implicates that male
role models can impact the development of a female’s science self-efficacy in CS as equally as,
if not more strongly than, a female role model. The recent Gallup survey in 2018 gave clarifying
recommendations, which this study substantiated, including ensuring equal access to CS
regardless of income, race, gender, or neighborhood. Continued efforts need to be made to
pressure structural change on educational policy, making CS mandatory for all high school
graduates nationally. As student E noted, she never would have known she liked coding had she
not been forced to take the mandatory semester-long tech class in ninth-grade. Certain
universities, such as Harvey Mudd and Carnegie Mellon, have actually started to make these
structural changes in their CS programs. For example, in 2002, Carnegie Mellon attempted to
address the gender gap in its CS department by changing its policy and requiring prior CS
experience for admissions to the major. This change yielded a drastic rise in the representation of
females in the program from less than 10% to 40% (Margolis & Fisher, 2002).
As seen in the Gallup recommendation and also in this study, early access to CS is
fundamental; however, limiting it is in and of itself. This should be coupled with quality
instructors who are cognizant of the socio-cultural climate of the field. Previous research has
focused on the pre-existing stereotypes that are associated with a male-dominated field;
however, no research to date has explored the pre-existing stereotypes that shape an individual’s
beliefs in their abilities to go into a male-dominated field like CS. Future studies need to explore
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 77

the link between the mindset of women and other URMs and their representation in certain
STEM fields.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 78

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Appendix A
IRB Approval Notice

University of Southern California Institutional Review Board
1640 Marengo Street, Suite 700
Los Angeles, California 90033-9269
Telephone: (323) 442-0114
Fax: (323) 224-8389
Email: irb@usc.edu

Date: Nov 19, 2018, 08:14am
Action Taken: Approve
Principal William Sullivan,
Investigator: ROSSIER SCHOOL OF EDUCATION
Faculty Frederick Freking
Advisor: ROSSIER SCHOOL OF EDUCATION
Co-
Investigator(s):
Project Title: Latina's SE in CS and their Factors
Study ID: UP-18-00710
Funding No Funding
Types:

This study has been determined to qualify for the USC Human Research Protection
Program Flexibility Policy. If there are modifications that increase risk to subjects or if the
funding status of this research is to change, you are required to submit an amendment to
the IRB for review and approval.

The University Park Institutional Review Board (UPIRB) designee determined that your project
qualifies for exemption from IRB review under the USC Human Research Protection Program
Flexibility Policy. The study was approved on 11/19/2018 and is not subject to 45 CFR 46
regulations, including informed consent requirements or further IRB review.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 90

If there are modifications that increase risk to subjects or if the funding status of this
research is to change, you are required to submit an amendment to the IRB for review and
approval.

Consent and recruitment documents for studies which are determined to qualify for USC’s flex-
exempt policy may not be stamped valid at the discretion of the IRB. If this is the case, the IRB
Administrator will not review the recruitment and consent documents uploaded, nor will the
documents be stamped valid. It is the researchers responsibility to make sure the support
documents are consistent with the study practices as stated in the application, and the document
follows the principles of the Belmont Report, which requires all potential participants to be
informed of the research study, their rights as a participant, confidentiality of their data, etc. If
not, please utilize the template Information Sheet For Exempt Research on the UPIRB and revise
the template to be specific to your study.

USC follows the Principles of the Belmont Report, which requires potential participants to be
informed of the research study (rights, procedures, confidentiality of their data, etc.). Therefore
a template Parental Permission/Youth Assent document is attached and should be revised to be
study specific.

Minor revisions have been made to the application (sections 6d, 24, 25.2, 26.2, 26.5, 27.2 &
40.1) by the IRB Analyst. The researchers are reminded that the support documents
(recruitment, parental permission/assent) must be consistent with the application.

**Per USC Policy, someone may not collect data about people he or she oversees in a
professional capacity. Please ensure that someone on the study (represented in 2.1, with
the required human subjects certification) is able to serve as an independent data
collector. Further, data must be stripped of any identifying information before being
provided to people who have the supervisory relationship in order to protect the
confidentiality of the participant responses.**

**Note: Data stored on a cloud service must comply with USC policy**

Because your research involves regular interaction with minors, you or your faculty
advisor [if you are a student] are:

1. A mandated reporter under state law required to report to state authorities if you become
aware of child abuse. Click here for more information about mandated reporters.
2. Covered under USC’s protecting minors policy, and must register your research with the
Office of Equity and Diversity and complete training. Click here to register and take the training.

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 91

“Assent” means a child’s affirmative agreement to participate in research. Researchers are
reminded that mere failure to object should not, absent affirmative agreement, be
construed as assent
Please check with all participating sites to make sure you have their permission to conduct
research prior to beginning your study.

You are responsible for ensuring that your project complies with all federal, state, local and
institutional standards. Please check with all participating sites to make sure you have their
permission (including IRB/ethics board approval, if applicable) to conduct research prior to
beginning your study.

All submissions, including new applications, contingency responses, amendments and
continuing reviews are reviewed in the order received.
Combo Youth Assent & Parental Permission Form, dated 08-01-2018.doc
Attachments: Guidance for Recruitment Tool.doc
Updated IRB Contact Information.doc

Social-behavioral health-related interventions or health-outcome studies must register with
clinicaltrials.gov or other International Community of Medical Journal Editors (ICMJE)
approved registries in order to be published in an ICJME journal. The ICMJE will not accept
studies for publication unless the studies are registered prior to enrollment, despite the fact that
these studies are not applicable “clinical trials” as defined by the Food and Drug
Administration (FDA). For support with registration, go to www.clinicaltrials.gov or contact
Jean Chan ( jeanbcha@usc.edu, 323-442-2825).

This is an auto-generated email. Please do not respond directly to this message using the "reply"
address. A response sent in this manner cannot be answered. If you have further questions,
please contact iStar Support at (323) 276-2238 or istar@usc.edu.

The contents of this email are confidential and intended for the specified recipients only. If you
have received this email in error, please notify istar@usc.edu and delete this message.

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 92

Appendix B
Combo Youth & Parental Permission Form
University of Southern California
Rossier School of Education
3470 Trousdale Pkwy, Los Angeles, CA 90089

YOUTH ASSENT-PARENTAL PERMISSION FOR NON-MEDICAL RESEARCH
This form will also serve as the “Youth Assent” and “Consent/Permission form for the
Youth to Participate in Research.” In this case, “You” refers to “your child.”

Latina’s self-efficacy in computer science and Potential Factors undergirding perspective

You are invited to participate in a research study conducted by Principal Investigator William S.
Sullivan, doctoral candidate under the advisement of Dr. Fredrick Freking, from the University
of Southern California. Your participation is voluntary. You should read the information below,
and ask questions about anything you do not understand before deciding whether to
participate.

Please take as much time as you need to read the consent form. Your child will also be asked
his/her permission. Your child can decline to participate, even if you agree to allow
participation. You and/or your child may also decide to discuss it with your family or friends.
You can keep this form.

PURPOSE OF THE STUDY
The research study aims to understand the reasons why women, specifically Latinas, are not
going into the field of computer science (CS). The study will explore how women in high school
computer science view their confidence level in the class and the reasons why Latinas view
their ability that way.

STUDY PROCEDURES
If you agree to participate, you will be asked to take part in an:
Individual Interviews:
A one-time, face-to-face, interview which should take approximately 45-minutes to complete
afterschool in the library. Interview will be audio recorded, without any names. Exact dates
will be arranged based on your availability.

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 93

Observation
Observed twice during two separate whole computer science class periods. Observations will not
in any way interfere with your classwork and will not impact your grade.

POTENTIAL RISKS AND DISCOMFORTS
There are no potential risks to your participation; however, you may feel uncomfortable
answering some of the questions. You do not have to answer any question you don’t want to.

POTENTIAL BENEFITS TO PARTICIPANTS AND/OR TO SOCIETY
There are no anticipated benefits to your participation. We hope that this study will help
researchers learn more about why women are so few in computer science and what society can
do early on to increase the number of women and Latinas in CS. This research may help advance
knowledge in the field and improve the equity of women in science; however, there is no direct
benefit to you for participating in this study.

CONFIDENTIALITY
We will keep your records for this study confidential as far as permitted by law. However, if we
are required to do so by law, we will disclose confidential information about you. 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.

As a USC employee, the researcher is required to report any known or suspected abuse or
neglect relating to children to USC’s Department of Public Safety (DPS) and the Department of
Children and Family Services (DCFS)

The audio recordings will be stored on a password protected recording device and held in a
secure location, accessible only to the principle investigator. No names will recorded, and
respondents will be identified as Student A, Student B, etc. No identifiable code book will be kept
to ensure the confidentiality of participants. Audio recordings will be transcribed and the will be
destroyed immediately. The data will be stored on a password protected computer for three
years after the study has been completed and then destroyed. Please note the participants
have the option to review recordings and/or transcripts.

PARTICIPATION AND WITHDRAWAL
Your participation is voluntary. Your refusal to participate will involve no penalty or loss of
benefits to which you are otherwise entitled. You may withdraw your consent at any time and
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 94

discontinue participation without penalty. You are not waiving any legal claims, rights or
remedies because of your participation in this research study.

ALTERNATIVES TO PARTICIPATION
If you don’t want to participate in this study, you will be asked to practice coding for fifteen-
minutes online. Please note, your grade will not be affected if you decide not to participate.

INVESTIGATOR’S CONTACT INFORMATION
If you have any questions or concerns about the research, please contact

William Sullivan

Sierra Vista High School
3600 N Frazier St
Baldwin Park Ca, 91706
Wssullivan176@bpusd.net or (626) 960-7741 x 2416

RIGHTS OF RESEARCH PARTICIPANT – IRB CONTACT INFORMATION
If you have questions, concerns, complaints about your rights as a research participant or the
research in general and are unable to contact the research team, or if you want to talk to
someone independent of the research team, please contact the University of Southern
California Institutional Review Board, 1640 Marengo Street, Suite 700, Los Angeles, CA 90033-
9269. Phone (323) 442-0114 or email irb@usc.edu.

SIGNATURE OF PARENT(S)/LEGALLY AUTHORIZED REPRESENTATIVE

I have read the information provided above. I have been given a chance to ask questions. My
questions have been answered to my satisfaction, and I agree to allow my child participate in this
study. I have been given a copy of this form.

AUDIO/VIDEO/PHOTOGRAPHS
(If this is not applicable to your study and/or if participants do not have a choice of being
audio/video-recorded or photographed, delete this section.)

□ I agree to be audio/video-recorded /photographed (remove the media not being used)

□ I do not want to be audio/video-taped/photographed (remove the media not being used)
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 95

Name of Participant

Name of Parent/Legally Authorized Representative (1)

Signature of Parent/Legally Authorized Representative (1) Date

SIGNATURE OF INVESTIGATOR

I have explained the research to the participant and his/her parent(s)/Legally Authorized
Representative, and answered all of their questions. I believe that the parent(s) understand the
information described in this document and freely consents to participate.

Name of Person Obtaining Consent

Signature of Person Obtaining Consent Date

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 96

Appendix C
Student Survey
Purpose: The purpose of this questionnaire is to assess how often you do the following in
regards to your computer science course. There is no right or wrong answers. This is not a test
and your answers will not impact your grade for the course in anyway. YOUR OPINION IS
WHAT IS WANTED.

Directions: The survey itself is composed of sixteen questions, which are broken down into
three sections: Background, Science self-efficacy, and Science Utilization. The survey is not
timed, please answer all questions as honestly as possible; however, you do not have to any
questions you do not feel comfortable answering.

Science Self efficacy Survey for high school students

Start of Block: Background

Q1.1 What is your student ID number

Q1.2 Gender at birth? o
Male (1)
o Female (2)

Q1.3 Are you Hispanic or (Latina/Latino)?
o Yes (1)
o No (2)

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 97

Display This Question:
If Are you Hispanic or (Latina/Latino)? = Yes

Q1.4 Are you..
o Mexican, Mexican-American, or Chicano (1) o Cuban (2) o Dominican (3) o Puerto
Rican (4) o Central American such as Guatemalan, Salvadoran, Nicaraguan, Costa Rican,
Panamanian, or Honduran (5)
o South American such as Colombian, Argentinian, or Peruvian (6) o Other Hispanic or
Latino/Latina (7)

Q1.5 What is the primary language spoken at home
o English (1) o Spanish (2) o
Another language (3) o English and Spanish
equally (4)
o English and another language equally (5)

Q1.6 What grade are you currently enrolled in for the 2018-2019 school year?
o 9th grade (1)
o 10th grade (2) o 11th grade (3) o 12th grade (4)

End of Block: Background

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 98

Start of Block: Science Self Efficacy
Q2.1 I know I can understand the most difficult material presented in this subject
o Never (1) o Sometimes (2) o About half the time (3) o
Most of the time (4)
o Always (5)

Q2.2 I know I can master the skills being taught in this subject.
o Never (1) o Sometimes (2) o About half the time (3) o Most of the time (4)
o Always (5)

Q2.3 I am confident I can do a good job on the assignments in this computer science
class.
o Never (1) o Sometimes (2) o About half the time (3) o Most of the time (4)
o Always (5)

Q2.4 I am confident I can do a good job on test in this computer science class
o Never (1) o Sometimes (2) o About half the time (3) o
Most of the time (4)
o Always (5)

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 99

Q2.5 I am confident I will receive an excellent grade in this computer science class
o Never (1) o Sometimes (2) o About half the time (3) o Most
of the time (4) o Always (5)

Q2.6 I am confident of understanding the most complex material presented by the instructor in this
computer science class o Never (1) o Sometimes (2) o About half the time (3) o
Most of the time (4) o Always (5)

Q2.7 I am confident of understanding the basic concepts taught in this computer science course
o Never (1) o Sometimes (2) o About half the time (3) o Most of the time
(4) o Always (5)

End of Block: Science Self Efficacy

Start of Block: Computer Science Utilization

Q3.1 I think the computer science course will be useful for everyday life
o Extremely useful (1) o Moderately useful (2) o Slightly
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 100

useful (3) o Neither useful nor useless (4) o Slightly useless
(5) o Moderately useless (6)
o Extremely useless (7)

Q3.2 I think the computer science course will be useful for college
o Extremely useful (1) o Moderately useful (2)
oSlightly useful (3) o Neither useful nor useless (4) o
Slightly useless (5) o Moderately useless (6)
o Extremely useless (7)

Q3.3 I think the computer science course will be useful to my career
o Extremely useful (1) o Moderately useful (2) o
Slightly useful (3) o Neither useful nor useless (4) o
Slightly useless (5) o Moderately useless (6) o Extremely
useless (7)

End of Block: Computer Science Utilization

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 101

Appendix D
Classroom Observation for Undergraduate STEM – COPUS

Classroom Observation Protocol for Undergraduate STEM – COPUS
This protocol allows observers, after a short 1.5 hour training period, to reliably characterize how
faculty and students are spending their time in the STEM classroom.
1
For further information, see:
www.cwsei.ubc.ca/resources/COPUS.htm
Smith MK, Jones FHM, Gilbert SL, and Wieman CE. 2013. The Classroom Observation Protocol
for Undergraduate STEM (COPUS): a
New Instrument to Characterize University STEM Classroom Practices. CBE-Life Sciences Education,
Vol 12(4), pp. 618-627

Observation codes
1. Students are Doing
L Listening to instructor/taking notes, etc.
Ind Individual thinking/problem solving. Only mark when an instructor explicitly asks students to
think about a clicker question or another question/problem on their own.
CG Discuss clicker question in groups of 2 or more students
WG Working in groups on worksheet activity
OG Other assigned group activity, such as responding to instructor question
AnQ Student answering a question posed by the instructor with rest of
class listening SQ Student asks question
WC Engaged in whole class discussion by offering explanations, opinion, judgment, etc. to whole class,
often facilitated by instructor
Prd Making a prediction about the outcome of demo or experiment
SP Presentation by student(s)
TQ Test or quiz
W Waiting (instructor late, working on fixing AV problems, instructor otherwise occupied, etc.)
O Other – explain in comments

1
This protocol was adapted from: Hora MT, Oleson A, Ferrare JJ. Teaching Dimensions Observation Protocol (TDOP) User's
Manual. Madison: Wisconsin Center for Education Research, University of Wisconsin–Madison; 2013.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 102

2. Instructor is Doing
Lec Lecturing (presenting content, deriving mathematical results, presenting a problem solution, etc.)
RtW Real-time writing on board, doc. projector, etc. (often checked off along with Lec)
FUp Follow-up/feedback on clicker question or activity to entire class
PQ Posing non-clicker question to students (non-rhetorical)
CQ Asking a clicker question (mark the entire time the instructor is using a clicker question, not just
when first asked) AnQ Listening to and answering student questions with entire class listening
MG Moving through class guiding ongoing student work during active learning task
1o1 One-on-one extended discussion with one or a few individuals, not paying attention to the rest of
the class (can be along with MG or AnQ)
D/V Showing or conducting a demo, experiment, simulation, video, or animation
Adm Administration (assign homework, return tests, etc.)
W Waiting when there is an opportunity for an instructor to be interacting with or
observing/listening to student or group activities and the instructor is not doing so O
Other – explain in comments

3. Student Engagement (optional)
L Small fraction (10-20%) obviously
engaged.
M Substantial fractions both clearly
engaged and clearly not engaged.
H Large fraction of students (80+%)
clearly engaged in class activity or
listening to instructor.
Student engagement alternatives:
(1) Just mark when engagement is obviously high or
obviously low.
(2) Count “N” students near you (~10) and assess how
many appear engaged at every 2 minute interval. Enter
value for all engaged instead of L/M/H. NOTE what your
value of N was.
Suggestions regarding codes and comments:
• Clarify code choices with comments.
• Consider indicating your confidence regarding coding, especially when you aren’t sure about
choice of codes.
HOW TO USE OBSERVATION MATRIX: Put a check under all codes that happen anytime in
each 2 minute time period (check multiple codes where appropriate). If no codes fit, choose “O”
(other) and explain in comments. Put in comments when you feel something extra should be
noted or explained.
Date: Class: Instructor:
No. students Observer Name:

Classroom arranged how?

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 103

1
.
L-Listening; Ind-Individual thinking; CG-Clicker Q discussion; WG-Worksheet group work; OG-
Other group work; AnQ-Answer Q; SQ-Student Q; WC-Whole class discuss; Prd- Predicting; SP-
Student present; TQ-Test/quiz; W-Waiting; O-Other Lec-Lecturing; RtW-
Writing; FUp-Follow-up; PQ-Pose Q; CQ-Clicker Q; AnQ-Answer Q; MG-Moving/Guiding;
1o1-One-on-one; D/V-Demo+; Adm-Admin; W-Waiting; O-Other For each 2 minute interval,

Table 10
Observation Protocol Raw Data - Page 1

check columns to show what’s happening in each category (or draw vertical line to indicate
continuation of activity). OK to check multiple columns.

1. L-Listening; Ind-Individual thinking; CG-Clicker Q discussion; WG-Worksheet group work;
OG-Other group work; AnQ-Answer Q; SQ-Student Q; WC-Whole class discuss; Prd-
Predicting; SP-Student present; TQ-Test/quiz; W-Waiting; O-Other
2. Lec-Lecturing; RtW-Writing; FUp-Follow-up; PQ-Pose Q; CQ-Clicker Q; AnQ-Answer Q;
MG-Moving/Guiding; 1o1-One-on-one; D/V-Demo+; Adm-Admin; W-Waiting; O-Other
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 104

For each 2 minute interval, check columns to show what’s happening in each category (or draw
vertical line to indicate continuation of activity). OK to check multiple columns.

Table 11
Observation Protocol Raw Data – Page 2

Further comments:
Smith MK, Jones FHM, Gilbert SL, and Wieman CE. 2013. The Classroom Observation
Protocol for Undergraduate STEM (COPUS): a New Instrument to Characterize University STEM
Classroom Practices. CBE-Life Sciences Education Vol 12(4), pp. 618-627
A protocol sheet in Excel format is available at: www.cwsei.ubc.ca/resources/COPUS.htm.

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 105

Appendix E
Observation Raw Data

Figure 5. Observation Raw Data Page 1/3

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 106

Figure 6. Observation Raw Data Page 2/3

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 107

Figure 7. Observation Raw Data Page 3/
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 108

Appendix F
Interview protocol
Principal Investigator: William Sullivan
Student: A
Title of the Study: Latina’s self-efficacy in computer science and potential factors undergirding
their perspective
Purpose: Introduction to study, gather background information, describe evidence demonstrating
self-efficacy, describe factors that shape self-efficacy for student.

Background information Name?
Grade?

Family/Cultural Influence Where
were you born?
Where were your parents born? Mother? Father? What
primary language did you first learn to speak?
What language is most often spoken in the home?

School Attended
Why are you taking this course?
How long have you been taking computer science courses?

Do you:
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 109

1. Please describe your past and present experience in computer science classes?
2. What experiences contributed to taking computer science courses in high school?
3. How are you been encouraged by others to take computer science? If so, whom and
how?
4. Computer science is typically seen as a male dominated field of study, as a woman have
you ever seen it that way?
a. If so explain
b. How’s this influenced your interest or motivation in the class?
5. How would you describe your feelings and beliefs about your ability to do well in
computer science?
6. What do you think creates or contributes to creating your feelings and beliefs in
computer science?
7. How confident are you that you can understand the most difficult concepts and skills
presented in this course?
8. Tell me one memorable story that would really help me understand how you arrived at
your feelings/belief in computer science?
9. Why do you think so few women are in computer science?
10. Why do you think so few Latinas or underrepresented minorities (URMS) are in
computer science?
11. What do you think could be done to increase the amount of women and other URMs in
CS?
12. Would you say your confidence in computer science was influenced by others? a. If so,
explain?
13. How will your experience in this course, influence your decision about taking future CS
classes?
a. At high school level
b. At the college level
c. Career level

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 110

Appendix G
Student A Interview Transcript
Interviewer: All right. So we are here today conducting our first interview. So first of all I'd like
to say thank you again for taking the time to participate in this interview. The
interview should go approximately maybe 30, 45 minutes in length, depending on
how the questions go. But again, like I said, if you have any questions yourself,
please feel free to stop me and clarify, or ask me to repeat a question. So I want to
open up by asking a little bit about your background. Can you just talk about
where you were born?
Student A: I was born in Pittsburgh, Pennsylvania.
Interviewer: Pittsburgh, Pennsylvania. Okay. What about your parents?
Student A: They were born in Mexico, Michoacán.
Interviewer: Both mom and dad?
Student A: My dad, I forgot where.
Interviewer: But he was from Mexico as well?
Student A: Yeah.
Interviewer: Okay. And what was the ... So, right now, what's the primary language that you
speak at home?
Student A: Spanish.
Interviewer: Yeah.
Student A: Mm-hmm (affirmative).
Interviewer: Do you have any other siblings?
Student A: Yeah, have a older brother that's going to turn 18, and a younger brother that's in
sixth grade.
Interviewer: Oh, okay. So three of you?
Student A: Yeah.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 111

Interviewer: Okay. So can you talk a little bit about why you're taking this computer science
course?
Student A: I'm taking this computer science course because I'm very interested in technology.
It started in middle school, because I was taking drama, but then they offered me a
stem class.
Interviewer: Okay.
Student A: And so I was like, oh, what is it about? And then I asked them, and then this
sounded interesting. So I switched classes. And then I started the course, and then I
really liked it.
Interviewer: Do you remember what the course was? Was it a-
Student A: It was photography and computers. We learned about computers and we built it,
and the rams and stuff.
Interviewer: Oh really?
Student A: Yeah.
Interviewer: Wow.
Student A: And photography and video at the same time.
Interviewer: Was that just a one semester class?
Student A: No.
Interviewer: Or was it for the whole year?
Student A: Yeah, I took it for two years.
Interviewer: Oh, you did. So I was going to ask you ... That was my next question. So, in
middle school you took about two years?
Student A: Yeah, I took two years.
Interviewer: and then what about here in high school? Did you take anything prior to the AP
class that you're in right now?
Student A: Well, no. I took tech in freshman year.
Interviewer: Yeah.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 112

Student A: But I didn't know what type of things. They didn't really have freshmen courses for
tech, I didn't really see any. So I took drafting.
Interviewer: Okay.
Student A: And then that got me interested in engineering and stuff.
Interviewer: Yeah.
Student A: And then, yeah.
Interviewer: And then you had mentioned that you had this teacher before ... That class was
more tech, right? You said she was out though for most of the year?
Student A: Yeah, she was ... We had a sub most of the year.
Interviewer: Okay. Well, I mean we already talked about number one when asking you to
describe your past and present experiences in the computer science class. Let's talk
about two. So what experiences do you think both in and out of school do you
think might have contributed to you taking computer science courses?
Student A: Well, maybe outside because I would get on the phone and be like, oh, how does
this work?
Interviewer: Yeah.
Student A: How? And then maybe ... Yeah that, and then those past experiences, like I said,
the stem course.
Interviewer: Yeah.
Student A: That really helped me get more into it.
Interviewer: Yeah.
Student A: And be more interested in it.
Interviewer: Was that middle school when you took that stem course, was that your first
experience with sort of tech?
Student A: Yeah, more of a ... Yeah.
Interviewer: So it was very hands on-
Student A: Yeah.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 113

Interviewer: Type of experience. You said you had to build monitors and stuff?
Student A: Yeah, they'd make just build things, put together rams, connect cables, and I liked
the stuff we did
Interviewer: Have you been encouraged by anyone else to take computer science?
Student A: Well not really. But my teacher, the one that taught stem, he really made me feel
more towards it. He helped me to feel like I wanted to make a career out of it.
Interviewer: Yeah.
Student A: And he motivated more. He's like, oh no, you could do it, and stuff. And yeah, he
was very nice.
Interviewer: It was the same teacher for sixth and seventh grade?
Student A: Yeah.
Interviewer: Oh, very cool. So how do you think their influence will impact your decision
taking courses in college? Or do you think his experience back then influences you
to take these courses now in high school?
Student A: Yeah.
Interviewer: Do you think that will continue on?
Student A: Yeah. I feel like it. I'm looking towards a career towards computers.
Interviewer: Nice. So let me throw this at you now. So computer science is typically seen as a
male dominated field.
Student A: Mm-hmm (affirmative).
Interviewer: As a woman, have you ever seen it that way?
Student A: Not really. I feel like anyone can do anything. Men don't just have to be about
computers, women could be experts at it too. It's not just men that could be in
engineering or something. Everyone could be in it.
Interviewer: So would you say that the idea that the computer science being a male dominated
field, do you think that influences your decision or motivation in the class?
Student A: Yeah. It motivates me more to prove society or something wrong.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 114

Interviewer: Right.
Student A: That only men have to be in that field. Because it's to prove ... At the same time,
it's not motivation for that. But it's more my interest. But at the same time it's to
prove them wrong.
Interviewer: Right.
Student A: And my brother's saying, oh, why are you in the class and stuff.
Interviewer: Really?
Student A: Yeah.
Interviewer: So you hear some sort of comments from siblings then about you being in these
classes?
Student A: Sometimes. Not really, but sometimes when they want to criticize me and stuff. Or
when they feel like I can't do that.
Interviewer: Yeah.
Student A: Yeah.
Interviewer: And do you think that's kind of related to the perception that computer science is a
guy thing?
Student A: Sometimes I do. But then I'm like, maybe he's just doing it to just say something,
and then for me to get me off that path. But then I'm like, it's not going to change
my thinking.
Interviewer: Right. Because I mean, you said that ... I'm sorry, I should get closer. So you said
that you kind of used that perception, that computer science is a male dominated
field has motivation for you to sort of prove society and prove them wrong.
Student A: Yeah.
Interviewer: Can you talk just a little bit more about that though? Dig a little deeper.
Student A: What do you mean?
Interviewer: Well, what are you trying to prove wrong? I guess is what I'm-
Student A: Prove that women could be in engineering, in any type of field that involves
computers, maybe mechanics.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 115

Interviewer: Yeah.
Student A: Even though maybe it's not related. But women could be part of any field, not just
because they're woman can they not be in computers, because it's too technical. It's
more men are more smart or something. And then-
Interviewer: So you've heard those sort of stereotypes, basically.
Student A: Mm-hmm (affirmative).
Interviewer: Yeah. And for you, that doesn't stop you. It doesn't ... If anything it's a motivator.
Student A: Yeah.
Interviewer: It'll motivate you more. Okay. Great, let's move on. So let's talk about you. How
would you describe your feelings and belief about your ability to do well in
computer science?
Student A: Okay. There aren't ... Not all the time where I believe I can make it in there.
Because sometimes I'm like, oh my gosh, this is getting a little tough. But then I'm
like, you know what? Let me just research more about what we're learning and
stuff. And then maybe I'll get more of an idea. And then ... Yeah. I feel like I could
do well in that class if I research more about it. If I get more into the class. I don't
speak out too much, and I don't ask too many questions.
Interviewer: So let me clarify this, because it sounds like even though the work gets hard, you
just feel that you just need to research more.
Student A: Yeah.
Interviewer: Or just kind of ... It's there, you just got to work at it, right?
Student A: Yeah. Work on it more.
Interviewer: Do you ever question your ability to do it though? Maybe I just can't do this.
Maybe-
Student A: Yeah, I sometimes do, yeah. I'm like, can I? And then I'm like, should I even be in
this or should I just go take other courses, try out something else. And I'm like,
what do I see myself in, in a few years? And then I'm like, I see myself in
computers and stuff. In engineering or something.
Interviewer: Yeah.
Student A: That has to do with computers. I see myself in those fields.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 116

Interviewer: And is that your motivation to sort of persist forward.
Student A: Yeah.
Interviewer: And do the research and figure out.
Student A: Because I know this is what I want to do with my life and stuff.
Interviewer: Great. So what do you think creates or contributes to creating your feelings and
beliefs ... Where do those feelings come from? Your ability to do well. Because it
sounds like you have this ability that you know that you are confident in yourself
to do well in computer science. You just might need to do more research. Right?
Student A: Yeah.
Interviewer: So where does that confidence in your ability come from, you think?
Student A: Well, sometimes it comes from when my teacher told me that I could do it and
stuff. And sometimes it comes when I'm doing an easy thing, I'm like, oh this is
easy. Or when I'm like, oh, this isn't that hard. I just need to get more of a hang of
it. And then when I will contribute to it. It's just what I feel towards it.
Interviewer: So, well let me clarify. Because I think you mentioned a couple of good points.
One was that you talked about your past experience in middle school, and you kind
of hear the echo of your past teachers sort of encouraging.
Student A: Yeah. Yeah.
Interviewer: You can do this. But then I think I also heard you say that when you find success
at the easy task.
Student A: Mm-hmm (affirmative).
Interviewer: It kind of gives you confidence that you can do this.
Student A: Or when I don't understand something, but I research it and then I'm able to
understand it. And then I'm able to do good on it.
Interviewer: Yeah.
Student A: And pass.
Interviewer: You're successful at it, right? You've worked hard. And then you see the return is
that you're successful.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 117

Student A: Mm-hmm (affirmative).
Interviewer: It gives you that confidence that ... Okay.
Student A: Yeah.
Interviewer: Great. So the followup question was this, how does your perspective about your
abilities impact your decision to continue taking computer science in college? So
how does your success now in high school going to impact your decision to take
classes? Because you're a senior right now?
Student A: No, I'm a sophomore.
Interviewer: Sophomore.
Student A: Yeah.
Interviewer: Oh. So next year then, how does your perspective about your abilities in computer
science going to impact you to take anything else next year?
Student A: Well, what do you mean?
Interviewer: So, it sounds like you have a positive perspective about your ability to do well in
the class. Is that going to encourage you to try and take other classes next
semester? And if so, what does that look like?
Student A: Yeah, it does encourage me to take other classes next semester. Like JavaScript, or
HTML, or any other courses. I could do any courses that are available of
computers.
Interviewer: So you're just like, what's next?
Student A: Yeah.
Interviewer: Whatever you can get your hands on, what's next?
Speaker 3: Can I get something out of the room?
Interviewer: Huh?
Speaker 3: Can I get something out of the room?
Interviewer: Yeah, yeah, yeah.
Speaker 3: I just need some stuff here.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 118

Interviewer: Yeah. Sure.
Interviewer: So let's go a little bit deeper in the classwork itself, because we kind of already
talked about some of the easy tasks that you find success in, but then also some of
the more difficult tasks. How confident are you that you can understand the most
difficult concepts and skills in this course that you're in right now?
Student A: I'm not that confident, but I feel like with more practice, and if I ask my peers
more of what we're learning about. Of I don't get something I ask the teacher, or if
I do more research. Yeah. I'm not that confident. I'm that confident. I feel I could
do very good.
Interviewer: Do you feel that your confidence is ... Is your confidence in any way affected by
the students in the class?
Student A: No, my students are very ... I mean the students, they're not mine.
Interviewer: In the class.
Student A: But my classmates, they're very nice and stuff.
Interviewer: Are they supportive in helping, like if there's something you don't understand?
Student A: Yeah.
Interviewer: Okay. So tell me one memorable story that would really help me understand how
you arrived at your beliefs?
Student A: Like I said, middle school, when we were building the computer, the monitor, it
was so fun. It was great, it was like, "Oh my gosh, these pieces go here. Oh my
gosh, this helps this do this. Like the motherboard helps it turn on and stuff. And
you just don't need that just to make it turn on, that there are other ways to turn it
on." And it's like, "Oh you could do this with this. And then the RAM helps to do
this, and then this transports that and stuff.".
Interviewer: That seems very memorable. How big was the class? Do you remember how many
students were in there?
Student A: It was lot. No actually, yeah it was a lot, but some students would leave and then
some would come. But it ended up being a small percentage of us that stayed the
next year, the following year. It was only 18 of us that stayed into the course for
the second year. And it was only three girls. And I was like, "Why aren't more girls
here?"
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 119

Interviewer: Really.
Student A: Yeah. It was a lot of guys and some girls.
Interviewer: Can we talk ... How did that make you feel when you were in this class where
there was a lot of guys and just a few girls?
Student A: Well, it made me feel like, "Why aren't there more girls here? There should be
more. Is there really just us, or is other people not like ... Don't know about this
course."
Interviewer: And so did that make you ... I mean, how did it make you feel? Did it make you
feel uncomfortable? Did it make you ever question your ability just because there
was so few of you in the course?
Student A: No. It didn't impact me. It was like, why aren't there more girls here because that
means we have to step it up as girls. We have to be more involved in computers.
We have to show how we could be here in this class and pass it and be successful
in computing and the course and how it's not hard or complicated.
Interviewer: Was it ever, I guess, seen that way, how the boys did, how the girls did, or did you
ever talk about it with the girls in the class about how you were doing compared to
the boys in the class?
Student A: No, we were pretty fine. I was like, okay, there's more guys, but doesn't mean we
can't do good. And then was like, the guys are there, they're interested too. They
could be part of it, we're all part of it, we're all interested in the same thing.
Interviewer: And how about now? How about your class now? Do you have-
Student A: I don't think ... It's okay. It's like a good amount of girls. There's a good amount of
girls.
Interviewer: Yeah.
Student A: But it's also, there should be more girls.
Interviewer: Of the girls, is there a high population of Hispanic women in there or ...
Student A: There's only like three of us. There's Rosa and the other girl, but I don't know if
she wanted to do the survey, I don't think so.
Interviewer: And the rest of them were ....
Student A: They're like ... I don't want to say their races, so.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 120

Interviewer: That's okay. You don't ...
Student A: But yeah. There's only, let's see, 10 of us girls.
Interviewer: 10.
Student A: Like 10. Yeah, 10.
Interviewer: And of those there's only three that are Hispanic.
Student A: Yeah.
Interviewer: So, let's talk about this. What do you think can be done to improve ... Well, so let's
do this a couple of ways, so what do you think can be done to improve your
confidence in computer science? Because you had mentioned that on the most
difficult tasks you aren't that confident, so what do you think would help improve
...
Student A: I don't know. Like maybe if they ... Miss Oviedo does a good job in teaching us
stuff, but maybe a little more explanation, a little more explanation on what we're
doing and stuff. Because sometimes I get confused on, "Wait, what. What are we
doing again?" And then, "Wait, what is this?" But Miss Oviedo does a good job.
She does. But sometimes we need more of an explanation, you know. At least for
me, because it takes me a while to understand the stuff. And then I need ... Yeah.
Interviewer: So what about women. How would we encourage and increase the number of
women to come into computer science, what do you think?
Student A: I feel like they should have more courses on computing, or they should, at least
speak more about it. It's not just drama. It's not just music. There's also computing
courses and stuff. Talk more about it when they're presenting it, like the counselors
and stuff about the courses and stuff. And then just to get more ...
Interviewer: So can I ask, how do you think we can change the ... Because as I mentioned
earlier that the field of computer science is seen as a guy's field. It's where the men
go. How would we encourage then young women, sixth grade, high school, how
do we encourage them to go into these fields that's seen as by men? What do you
think we can ...
Student A: Let's see. Maybe we can encourage them more by showing them how nice ... It's
not just about men, and then maybe speaking more about it, or taking more action
in them knowing that not just men can be in computing, not only them can be
experts in it, not only them can be part of it, but that girls could be in it.
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Interviewer: And what about for like Latinas that we want to encourage Latinas to go into this
and see this as a field that they can be successful at. Any thoughts on ...
Student A: Latinas. I really don't have any thoughts on it. It's like, it's just overall women
should know more about it and should be more part of it. It's just like, yeah, I don't
know how to encourage more Latinas, but overall women should be encouraged.
Interviewer: Well, and so, one of the things that the research shows is that even though women
are low in numbers, right, I mean it's by far the minority, it's very small group that
go into computer science. Of those women that go into computer science, there's
only just a very small percent of women, of Latina women that are going into it.
The majority are white. And then there's Asian, and then you have a very small
percentage that are Latina. Any thoughts on that and why you think there's so few
Latinas that are ...
Student A: I feel like there's so few Latinas because they don't think they could it, or because
they aren't that involved with technology. They aren't that exposed to it. Because I
wasn't really exposed to technology growing up because my mom didn't allow me
to have a phone, computer. We barely had wifi. And then it was like ... I barely
knew about it. And then util I got to middle school computers, laptops, STEM.
Interviewer: So your experience with tech and computer science has been here, at school?
Student A: Yeah.
Interviewer: Do you think that there might be any cultural reasons why so few Latinas are
going into computer science? Is there anything culturally that might-
Student A: Culturally? Well also maybe because some parents don't think that's correct for
their children to be in that class, or that-
Speaker 3: Can I grab this real quick?
Interviewer: Yeah.
Interviewer: Well, actually, can we just pick up where you made that comment about how some
parents don't feel that it's correct for their daughter? Or for their son or daughter-
Student A: For their daughter.
Interviewer: For their daughter to be in that class.
Student A: I feel like some, yeah.
Interviewer: Can you say a little bit more about that?
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Student A: Because it's like, especially my mom one time. She was like, "You're in
computing?" She's like, "Are you sure you could do that class?" And I was like,
"Yeah, I'm pretty sure." I'm like, "I could do that class." I'm like, "I could be an
expert at it." I'm like, "I feel very good in that class. I feel happy in it." Then, I just
feel like it's that, maybe that Hispanic parents or something don't see their
daughters in it.
Interviewer: Yeah.
Student A: Because they may have views about men and woman, how the men should be in
computing and stuff and women should be in dancing or something.
Interviewer: Do you think that's what your mom was questioning, why you were ...
Student A: Yeah. But until I explained to her, I was like, "Oh, I love to do this," and stuff. She
was like, "Okay, then. Do what you want."
Interviewer: How has your parents' reaction been to you taking computer science?
Student A: It was good after I explained to them what I wanted to do and why I wanted to do
that and the career I wanted to pursue and what college I wanted to do for this.
How I explained to them more about it.
Interviewer: Yeah. But they never really questioned you after that, though?
Student A: No.
Interviewer: Like, after you explained it, they never-
Student A: After that, they were like, "Okay. Well, do what you wish. Do the career you like."
Interviewer: And you think a lot of Latino or Hispanic households are like that? Where sort of
parents have this traditional view, like you said,-
Student A: Yeah.
Interviewer: ... of what women and men do?
Student A: Yeah, I feel like some parents do not approve of that. You know how men go to
work and woman stay in the house?
Interviewer: Right, those old-
Student A: Yeah, those type of views.
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Interviewer: And so do you think that still might be kind of affecting why they might be more
supportive of let's say like if your brother are going into computer science?
Whereas with you, questioning why are you taking that?
Student A: Yeah.
Interviewer: All right, okay. So we kind of already talked about this one. What do you think can
be done to increase the amount of women in computer science? Did you want to
add anything? Or anything that popped into your head, just in general?
Student A: Just involve us more. Maybe talk about it more to us, maybe explain the course
more. Maybe some woman may be afraid to do it.
Interviewer: Yeah.
Student A: Or in general, man and woman could be like, "Oh, this course, how am I gonna do
in it? Should I even take it?"
Interviewer: What's interesting is that if we look at the demographics of the school, we are a
Hispanic school, right?
Student A: Yeah.
Interviewer: I think it's over 90% of our students here are Hispanic. Yet is we look at the
women in the AP class, there's only three.
Student A: Yeah.
Interviewer: So I think that's something that we definitely need to work better at. I think here is
kind of a little shocking a little bit, to see that there's only three.
Student A: Only three out of the 10 woman.
Interviewer: So you think just exposure, just talking about what it is?
Student A: Yeah. Or maybe, I don't know, me personally I like it, but I don't know how other
Latina might think about it.
Interviewer: Well we'll find out, yeah. That's what part of this research is, is just getting
information. What do you think about it and what do they think about it? And then
is it the same?
Interviewer: Let's see.
Interviewer: Do you think your confidence in computer science has been influenced by others?
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Student A: Yeah, 'cause of my teacher-
Interviewer: Your teacher?
Student A: And then-
Interviewer: Anyone else?
Student A: Let me see. Maybe some of my classmates too. Some of the guy classmates I had
were like, "Oh, you don't know this? Here, I'll help you." And then it's like, "Here,
I'll help you do this." And then it's like, "Oh, I like this environment. I like how
this feels. I like how confident I feel in this."
Interviewer: How has the environment been in those classes? Because it seems like, even early
on when you took those classes in middle school, it was the majority boys.
Student A: Yeah.
Interviewer: How would you say that their support has been for you in the class? How have
they been supportive?
Student A: They have been great.
Interviewer: Yeah?
Student A: Yeah, they have been very supportive. They never, "Oh, you're a woman, you can't
do this." Yeah, especially since my teacher was a guy,-
Interviewer: Yeah.
Student A: It was like, "Oh, I can do this." Yeah.
Interviewer: So you had the support. Do you think that made a difference?
Student A: Yeah. I feel like that made a lot of difference. If I didn't feel very confident in this
course, I probably wouldn't have ever done it again.
Interviewer: But do you think the fact that the teacher in middle school was a man, and gave
you that support, and told you that you could do it, do you think that made a big
difference? Had he been a woman,-
Student A: Yeah. Yeah, it's like, "Oh, he's motivating me more. He's showing me how not just
men could be in the course. He's not just saying, 'Oh no, you don't do this. Oh no,
just give up' ", or something. He's actually helping me to be more into the course.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 125

Interviewer: That's awesome. So last question. How will your experience in this course
influence your decision to take classes next year in college and maybe a career?
Student A: It will influence me a lot. It will help me know what exactly I want to do. There's a
lot of different fields, so it will help me decide the field I want to take,-
Interviewer: Okay.
Student A: ... the kind of actual direction I want to take. I'm still like, "What actual career
should I take?" There's so many. It's also showed me more about how computers
affect everything, how it can affect the cyber bullying, the data, the harmful affects
it has on that. Yeah.
Interviewer: So would you say the course exposed you to a lot more that computer science is?
Student A: Yeah. It's shown me a lot more.
Interviewer: So have you decided on a career?
Student A: I've been thinking towards a STEM teacher 'cause I was like, "Oh, I want to do
what my teacher did for me."
Interviewer: Yeah.
Student A: Or engineering or cyber security or something.
Interviewer: Nice.
Student A: Yeah.
Interviewer: Well, that's it. So that concludes the interview. Let me say thank you again. I really
appreciate your time and your honesty. Thank you so much.
Student A: Thank you.

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Appendix H
Student B Interview Transcript
Interviewer: Alright, so we are here, this is the second interview. Thank you again for willing to
participate, and we have about 15 questions or so, give or take, to go through and
the interview's scheduled to be about 30 to 45 minutes in length. Okay. We're
going to start off with a little bit about your family and cultural influence, some
information about the school that you attended, and then more specifically about
the course that you're currently taking. So let's start off, where were you born?
Student B: I was born in Arcadia, California.
Interviewer: Oh, okay. And your parents?
Student B: My mom was born in Los Angeles, and my dad was born in Mexico.
Interviewer: Okay. Do you know where in Mexico?
Student B: Mexico ... No, not really.
Interviewer: Okay. What about at home, what's the primary language that you guys speak?
Student B: Spanish.
Interviewer: Okay. And is it the main one that you ... That's the same thing. Was that the first
language then you guys spoke since growing up?
Student B: Yes, the first language was Spanish and then we learned English at school.
Interviewer: Oh, okay. So let's talk a little bit about the schools that you attended. Have you
always been in this district, or ... You said you were born in Arcadia. Did you go to
school in Arcadia?
Student B: No, I was always in this district.
Interviewer: Oh, okay. And prior to taking this course in computer science, was there any other
courses that you took similar to?
Student B: I did take HTML Web Design.
Interviewer: Oh, was that in high school?
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Student B: In high school, yes.
Interviewer: Was there anything taken in middle school, any STEM or computer courses or
anything like that?
Student B: No, not that I recall
Interviewer: Okay, so that HTML course that you took in here, was that sort of your first
introduction, too?
Student B: Yes.
Interviewer: Okay. And do you guys have a computer at home?
Student B: Computer? No, we don't.
Interviewer: So a lot of your influence with computers have, would you say has been here at
school?
Student B: Yes.
Interviewer: So can I ask you about this course, this class you're taking? This computer science
class? Can you talk a little bit about why you're taking this course?
Student B: I'm taking computer science because when I was introduced to HTML I really
liked coding, and so Miss Oviedo talked more about the course, about how it's
coding and you get to learn more programming languages like JavaScript and more
of HTML. So I kind of got ... I wanted to take the class because I really liked
HTML, so I thought ... To code, I wanted to develop it more in that class.
Interviewer: How long ago did you take that HTML class?
Student B: I took it on my sophomore year.
Interviewer: Sophomore year. And you're a senior now?
Student B: Yes.
Interviewer: Okay, so there was about a year in between. But that still stuck with ... Still kind of
stuck with you, because after you took that course there was a whole year in
between you deciding to take the other course. That must've been really something
that kind of resonated with you.
Student B: Mm-hmm (affirmative).
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Interviewer: Okay, we kind of already answered the following question, so let's talk a little bit
about your experience with computer science in classes. So you said that the
HTML class was your first introduction to basically computers at school, and that
you didn't take anything at the middle school. Can you describe the HTML class,
just your overall experience in it.
Student B: So the HTML class we designed a website about what we were interested in. And
Miss Oviedo helped us do the whole process of learning the language. And there
was tutors who also helped us design our website and then after introduced us to
all the programming, it was kind of like we were left on our own to build it and
finish it.
Interviewer: Was the HTML course, was it a semester course or was it a whole year?
Student B: It was a whole year.
Interviewer: Oh, it was a whole year.
Student B: We had a whole year to design our website.
Interviewer: And you said that there were tutors in the course. These were college, or
upperclassmen that were coming and helping you?
Student B: They were students who previously took the class. So they already had knowledge
on the course.
Interviewer: Okay. How did you feel about the course, taking it? How did you, just personally
feel about it?
Student B: It was difficult at first, but once you got the hang of it it started to get easier and
you could help the students around you with some codings that was hard to
understand. So it was kind of nice to help others with a thing.
Interviewer: Can I ask you a question about just the demographics of the class? Was there a lot
of women in that HTLM class, if you recall?
Student B: There was mostly men.
Interviewer: Mostly men. And of the few women in the course were there a lot of Latinas or
Hispanic looking women?
Student B: There was a few.
Interviewer: There was a few.
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Student B: Mm-hmm (affirmative).
Interviewer: But the majority you would say definitely men.
Student B: Men, yes.
Interviewer: Did that ever stick out to you, in your mind. Was that something that ever came to
your attention?
Student B: It was at first when I walked into the class. I thought I was in the wrong class
because it was just pure men. I was like, "What am I going to do here?" But it was.
But it was kind of intimidating, because I thought I wasn't going to do as well as
them because it was mostly men in there.
Interviewer: And you said that that was your first impression coming into it.
Student B: I thought I was going to be the only female in there, and it was kind of ...
Interviewer: And did that change at all as you went through the course?
Student B: It changed a little bit towards the middle because they were not as intimidating
anymore because we were all on the same level of learning the coding. So it was
not that stressful anymore.
Interviewer: But it was still ... Would you say it was still there even though it wasn't as
stressful, you still felt like an uneasiness, I guess, because there was this higher
influence of males in the class?
Student B: Yes.
Interviewer: Did it ever make you feel uncomfortable, because you said that ... It sounds like
you're saying it made you question whether or not you were going to be successful,
just by them being there.
Student B: Yeah.
Interviewer: How was their interaction with you in the class?
Student B: Well we didn't really talk, because we were all focused on our work.
Interviewer: Independently?
Student B: Yeah. Okay. So there were people talking and we had to introduce what we were
doing the website on, I feel like people were ... Because they were all choosing
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better topics and I thought my topic wasn't going to be like, as much, so I feel they
were all judging, like, "Oh, she's doing this topic."
Interviewer: Did it ever feel like it was a gender issue, like, "Oh you know what, it's because
I'm a girl, or it's because they're boys."
Student B: Gender issue. No.
Interviewer: No. How was the support from them? Was it supportive or would you ...
Student B: They were supportive on some stuff, like they'll be like, "Oh good job on this
part," or "Oh you did well on this." They would tell you, "Oh you did nice on your
website, you did good things that ... "
Interviewer: What about the class that you're in now? Let's talk a little about the demographics.
Is it similar where you have the majority of the people in the class male?
Student B: They're all male, yes.
Interviewer: They're all male.
Student B: Like a lot of them are male. Like there's a couple of females.
Interviewer: A couple of females. How big is the class, on average would you say how many
students would you say?
Student B: Like around 30, probably.
Interviewer: 30 students. Okay. And you would say more than half of them are males.
Student B: More than half, yes.
Interviewer: And then of the few females, how many Hispanic, Latina, would you say?
Student B: There's three.
Interviewer: Three.
Student B: Including me.
Interviewer: And again, let me ask you that. How does that ... Going into it, how does that come
across, or how does that make you feel?
Student B: It was still intimidating, because knowing even though there was some women I
felt like I was the only one from my culture. And I felt like I wasn't going to do as
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well as all of them because they were all smart. Like knowing some of them they
were smart, so I was like, "Oh, I'm not going to be able to succeed in that class."
Interviewer: And the course you're taking is the AP?
Student B: AP, yes.
Interviewer: Yeah, it's AP Computer Science, or ...
Student B: AP Computer Science Principles.
Interviewer: Okay. Okay. You're finishing up your first semester in the course?
Student B: Yes. Mm-hmm (affirmative).
Interviewer: So again, is the course designed more independent where you work on your own,
similar to the HTML course, or do you find that this course is more forces you to
collaborate with the other students in the class?
Student B: Well it's both. In some things we have to do it independently, but in some of the
project we could do in a group to help each other with the coding.
Interviewer: Okay. And how has your experience been in the class? Do you still feel that
uneasiness with it being such a predominantly male classroom, or has that changed
since you've gone through your first semester?
Student B: I still feel uneased, because it's still a lot of males in there, and I feel like they will
do better than me at computer science, because I'm not that good, but I'm also not
bad at it. So I feel that ...
Interviewer: Well let me ask you how it is with the women, with the other females in the class.
Does it ever become sort of boys versus girls, or does it ever ... Is it very
supportive with the other female students in the class, or how has your experience
been with them?
Student B: They're all supportive when it comes to presenting our topic for our Explorer. They
were all supportive of the topics we chose and how much information we gave out
about it. So they were supportive about that.
Interviewer: Do you find that you're going ... Would you be more inclined to go and ask for
help towards other females students, or are you equally inclined to ask for help
from either male or female, it doesn't matter?
Student B: It don't matter because they're both in the same class so they probably know a little
bit more. I'll ask both of them.
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Interviewer: Okay. Let's move on. So we kind of already talked about this, but what
experiences contributed to you taking the computer course right now in high
school?
Student B: There's a lot of jobs out there now involving computer science, so when I was
thinking, I'm like, "Oh, that should be an easy thing to get into. It shouldn’t be that
hard." But once I got into the class it was difficult going on. But as you learned it
became easy. And each time you learn something new it was hard but then after
you practiced and learn it it became easier as you went on.
Interviewer: Have you been encouraged by others to take the course?
Student B: No.
Interviewer: How has your family been? Do they know that you're taking computer science in
high school?
Student B: They know I'm taking it, but they're not too interested in that. They're mostly like,
"Oh you're going to do that, but you're just wasting time."
Interviewer: Oh, is that what they told you about it?
Student B: Yeah.
Interviewer: Why do you think they said that?
Student B: Because not a lot of Hispanics or females are going into computer science. That's
what they see, because they see mostly a lot of males on TV, like designing
programs and stuff, and they're like, "Oh, why are you wasting time on that when
you could be focusing on going into a different major, like going into nursing or ...
"
Interviewer: And so, how does that make feel when you heard that?
Student B: Knowing that I wanted to go into computer science even in college, it hurt me,
because knowing that they won't be ... They're not going to be supportive about
this decision, because they want me to go into other fields because they think that
I'm not going to be successful in this course.
Interviewer: Have they said anything else to you besides that remark about wasting your time,
or was it just that one instance, or has it been several things that they've said in
regards to you taking computer science in high school, or possibly in college.
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Student B: It was only that one time, but they still like ... When I talk to them about, oh the
course, they just be like, they try to change the subject, they're like, "Oh."
Interviewer: Oh, okay. So it's not like they're necessarily not being supportive, they're just
trying to avoid the subject basically.
Student B: Yeah.
Interviewer: How have you responded? Do you now finding yourself not talking to them about
that course? How have you changed, or have you changed?
Student B: I try not to talk to them about computer science. When they tell me like, "Oh you
applied to college, what did you apply for?" I'm like, "Oh I just applied to college."
I don't talk about the major specifically, because it will be like, "Oh you're just
wasting money on something you probably might not get into."
Interviewer: So what do you think's going to happen if and when they find out that you've
applied to and to major in, or that you're going to major in. Have you thought
about that?
Student B: If I do get accepted they'll probably be surprised, they'll be in shock, but I think if
they do come to accept that I'm going into that major they'll probably start
supporting it. Because they think it doesn't make that much money, because they
mostly want me to succeed and they don't see that field being successful.
Interviewer: Were you surprised by their reaction at all?
Student B: A little bit.
Interviewer: Yeah. Looking back now and reflecting on how they reacted when you told them
that you were interested in the field, do you understand where that response is
coming from? From a cultural standpoint? Or are you still like, "I don't understand
why they're not in support"
Student B: Because for them they don't know much about computers. And they mostly think,
they think it's a male dominant. So when I said I was going into computer science,
they were like, "Oh." They were shocked because it's not for a female to go in
there, especially for them, because from their culture when they were in Mexico,
all people were telling, "Oh what are you going to do with your life?" And then
they wanted to go into nursing or something like a secretary. And so it was a shock
when I told them, "Oh I want to go into computers."
Interviewer: Yeah. Did they ever make that association that, or say it explicitly that computer
science was a male career or ...
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Student B: They hinted at it. Be like, "Oh, there's a lot of males. Won't you be scared going to
that class." And I replied, "A little bit, because it'll be challenging, but I'll still have
to overcome it."
Interviewer: Yeah. Looking back now how has that affected your motivation, their response?
How has that affected your motivation to continue on with pursuing a career in
computer science?
Student B: I'm trying to get a good grade in those class, like I did in HTML. I got an A and I
showed them. And for this class I want to learn more and get more experience so
when I do get good grades I'm like, "I could do it. I could major in that." And just
show them that I could do stuff on the computer.
Interviewer: So would you say that their response is, in a way, motivating you so that you can
show them, like, "Look, I can do it and have the letter grade, like see look, I can do
it. I can get accepted into the college with that major."
Student B: Yes
Interviewer: Okay. Do you have any, I didn't get a chance to ask you this previously, siblings at
home?
Student B: Yes, I have two brothers.
Interviewer: Older? Younger?
Student B: Younger?
Interviewer: What grades?
Student B: The youngest one is in preschool and then the other one's a junior in high school.
Interviewer: Oh. Okay. And he comes here, to the same high school?
Student B: Yes.
Interviewer: Okay. And is he taking any computer science courses now?
Student B: No. He's not interested in it.
Interviewer: Not interested at all. Okay. Let's move on. I mean, I know that you talked about
Miss Oviedo and the HTML class encouraging you and telling you about the AP
course and I'm sure about the career possibilities. Has she been supportive or
encouraging in any other way besides that speech to the class? Has she talked to
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you or mentored you or supported you in specifically one on one or in any other
way?
Student B: No. She mostly goes towards the whole class, like, "Oh I encourage you to take
more computer classes as you move on into college, or if you're still going to be in
Sierra Vista to take these new classes that they're offering next year."
Interviewer: Okay. So just more like whole ...
Student B: Yeah.
Interviewer: We we talked about this. In the next question it says, "Computer science is
typically seen as a male dominated field of study. As a woman, have you ever seen
it that way?"
Student B: Yeah. From the classes they're mostly male so it's like there are mostly males are
going into it.
Interviewer: Does that affect your motivation knowing that going into it?
Student B: A little bit. I'm kind of hesitant at the same time, but I still strive to go forward,
because even though it's mostly males a female could still do it.
Interviewer: Do you think that in a way is a motivation for you? Well, is it motivation, do you
think?
Student B: Yeah, kind of, knowing that I could actually do it just like the males kind of
motivates me.
Interviewer: So let me ask you about how you feel about your abilities in computer science. Do
how do you feel about your ability to do well in the class, in this course right now?
Student B: In this course we're learning JavaScript, and I was used to ... But it's JavaScript in
block form and I learned HTML, so when we do projects with JavaScript in
coding, I see other people doing better projects, like they're doing all these stuff
that we haven't learned. And so I'm just still trying to figure out how to do some
simple stuff, but seeing them, the rest of the class doing a little bit more difficult
stuff, it's ... I want to strive to do what they want to do, what they could ...
Interviewer: How's your confidence in level in the course right now?
Student B: It's kind of low, because they could do better stuff, all the rest of the females and
males could do a little bit more better stuff. And I want to achieve that, be on their
level.
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Interviewer: Is there support though, to go in to get help so that you can achieve what all the
other classmates are doing? Is there support right now, some help?
Student B: Yes. From my teachers and the AP tutor she has. If you're stuck with something
and you want to learn how to do this, they'll help you on the project.
Interviewer: Oh okay. And the tutors there once a week, twice a week, or ...
Student B: The AP tutor there is every day.
Interviewer: Oh every day. Nice. Okay. Well, you kind of ... Let's see, how does your
perspective about your abilities ... How does your perspective about your abilities
impact your decision to continue taking computer science in college?
Student B: In college.
Interviewer: Like now, how does your belief about your ability in this course going to affect
you taking future courses in computer science?
Student B: Well I'm trying to right here to get better as the course moves on, try to get better
with coding and everything. So if I do get better I feel like I'll do good in college,
and the material won't be as difficult as right now, since I'm trying to learn it.
Interviewer: Do you feel like you need to be the ... Do you feel like you need to have your
confidence level really high in order to continue on taking computer science, or
right now as it is, you're already taking classes in college no matter what?
Student B: Well for me I still want to take computer classes and it doesn't matter for me if I'm
confident or not because I know I'll improve. Because when I improve I feel like
I'll gain that confidence to do more.
Interviewer: So whether that happens here or in college ...
Student B: Or in college.
Interviewer: ... you figure it's going to happen at some point, you're confident that it's going to
happen at some point?
Student B: Yes.
Interviewer: I'm going to ask you, I know you said that you might not have an answer to this
question, but I'm going to ask it anyways and it might spark something here. So,
could you tell me about one memorable story that would really help me understand
how you arrived about your beliefs in computer science, because when I asked you
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 137

about your confidence, you said it was low. Is there a specific moment that you
can think back about why or how your confidence got to that level?
Student B: No. I can't think of one.
Interviewer: Was there a project or a comment that someone made to you or a moment of doubt
in a class or at home about an assignment that felt overwhelming or too hard or too
difficult that perhaps made you question your ability in the course?
Student B: I think it was one of the projects we just finished. It was a Halloween project just
for fun. And I was trying to learn how to do this, trying to make a list for what she
wanted, because there was a list of requirements, and we were going to present it
in front of the class. But I was so busy on that one little thing that I didn't get to do
anything else. And then when we presented them I was hesitant to show what I had
so far because everybody else's was so ... It was nice and ...
Interviewer: Right. They had done more already. And how was the response from the teacher,
from the students. Because you did eventually have to share it right? You had to go
up into the class and share, or you didn't?
Student B: I didn't. I told Miss Oviedo I was finished, and she's like, "Oh well, you still have
to turn it in and make it better." And so I did make it better, but I don't know that ...
Because everybody else had the same opportunity to make it better, so I don't
know if my project is going to be compared to the rest of them.
Interviewer: How has the support been from Miss Oviedo? How has your relationship been?
Because the HTML class that you took, was it with her as well?
Student B: Miss Oviedo, yes.
Interviewer: And so how has the relationship been either at the start when you first took that
HTML class to now? Have you had much interaction with her one on one, or do
you just interact with her in the class?
Student B: When she found that I was taking computer science she was happy. She was glad
because I was actually taking the course, because I did improve in HTML. My
website, it was nice. So she was surprised and happy that I was in this year's class.
Interviewer: And now, has see you struggling with some of those projects has there been more
interaction, more support, or does she wait for you to go and ask her?
Student B: She waits for me to go and ask her about a certain thing and then she'll help me out
with that.
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Interviewer: So let me ask you this. What do you think can be done to help improve your
confidence in computer science?
Student B: Help me improve. I think, what's it called, like learning more, because I know
we're learning new things, but as a whole class learn the same thing, like what's it
... Because in that class we're all at different levels of how we know, so to improve
anybody's confidence it'll be nice if people shared their knowledge and so other
people could build from that and improve their coding and the basics of that class.
Interviewer: Do you think being a woman in any way affects your confidence in computer
science?
Student B: A little bit.
Interviewer: Can you talk a little bit about that.
Student B: Because it's mostly males there so it's like, they know a little bit more stuff about
computers and games. Like what I've seen in that class, they know a little bit more.
And I don't know that much about computers so I feel like I won't be as good as
them.
Interviewer: What about as a Latina? Does it in any way affect your confidence at all?
Student B: A little bit, because a lot of Latinas are not introduced to computer science, and it's
mostly other womens from other countries or cultures that are introduced to it and
their parents want them to make a career in that. But for my culture, my family,
they want me to pursue something else.
Interviewer: So do you think it's a differences in culture where one culture might want to have
their daughters pursue it whereas yours might question it?
Student B: Yes.
Interviewer: Why do you think that it? Why is there this difference in your culture and with
other cultures to how they see for their daughters?
Student B: Because with my family when they were back in Mexico they didn't know a lot
about computers. It was something they didn't have. And their parents wanted to
make them go into nursing, more specifically. And so my parents now want me to
go into nursing, and I see with other cultures, especially with some of my friends
because they're from a different culture, their parents, it doesn't matter to them.
They're like, "Oh go what you want to do. If you're happy doing it, then go for it,"
whereas my family's more about, "Go get a good job so you could support
yourself."
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Interviewer: So I know we talked about this, why do you think there's so few women in
computer science? We talked about it being one of the fastest growing careers out
there, but why do you think there's some few women going into it?
Student B: Because I don't think a lot of women are introduced to it in some schools. Because
they might ... They could like something else, because not a lot of ... They don't
see a lot of female figures in computers in general. It's mostly males, "Oh a male
developed this. They developed that," but they don't hear any women. So they
don't hear anything about that.
Interviewer: And do you think the same is true for Latinas as well?
Student B: Yes.
Interviewer: Because it sounds like what you were saying is that there's this lack of role models,
would you agree to that?
Student B: Yes.
Interviewer: Do you think thr fact that your teacher is a female has anything to do with your
confidence in the class? Like had it been a male you might have felt differently?
Have you ever thought about that?
Student B: No. I haven't thought about that.
Interviewer: Do you think if you had a role model, like an older sibling or sister or cousin or
aunt that had already majored in computer science, do you think that would have
made a difference?
Student B: I think it would, because it would have helped me gain more confidence in the
career. Because nobody in my entire family knows about computers, so I'm one of
the first ones to be like, "Oh I could do this. I could do that."
Interviewer: And how does that make you feel, being the only one in your whole family going
into this career?
Student B: A little bit scared and pressured.
Interviewer: What do you mean by pressured?
Student B: Pressured because I'm the only one in that family so I feel like pressures on me
even though they're not so concerned with it, I still feel pressured to do good.
Interviewer: Oh okay.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 140

Student B: I try to show them, "Oh I could do it."
Interviewer: So if you go into this field, this field that's predominately male, there's a lot of
pressure from, you feel from your family, to succeed.
Student B: Yes.
Interviewer: Do you feel like it would be easier to go into other fields that are more female
dominant, like nursing or something like that? Do you think it'd be easier to go that
route?
Student B: It would be easier, but stuff like nursing, it doesn't interest me, but it could be
interesting to somebody else. For me it's mostly like computers, once I was
introduced to it I wanted to learn more, and nursing's not a career for me.
Interviewer: So we already talked about some of these, so I'm going to just skip some of these
questions. Okay, so besides your parents and Miss Oviedo has there ever been
anybody else that influenced your interest in computer science either one way or
another, whether to pursue a career, or ... And it can be family or previous past
teachers or anyone else.
Student B: There was this one coworker who told me about computers, and the computer
science, because she was at this school but they didn't offer it, computer science,
so she was talking about, "Oh, it could've been so helpful right now since I'm in
college doing computer science. It could've been helpful to have these courses."
And so she talked to me about it during my sophomore year, and want me to
pursue it. Because after HTML I was hesitant during that one year to take this
course.
Interviewer: So do you think that helped you, talking to, you said your coworker?
Student B: Yeah, coworker.
Interviewer: Did that conversation happen before taking this AP course?
Student B: Yes. It happened during taking my HTML course.
Interviewer: So what influenced your decision, but you just said that you were hesitant in that
one year in between to take the AP course. What for you did it to take this next
step and take an AP course? What was that deciding factor, do you think?
Student B: I think it was most before I still wanted to code, and it was on my mind when I was
taking other classes. I'm like, "Oh, I could've been in this class doing something to
improve, but ... " So I decided to take it this year.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 141

Interviewer: Any regrets on taking the course?
Student B: No.
Interviewer: No. So last question. So how will your experience in this course now that you're
taking, how will it influence your decision to take any future computer science
classes in college or career?
Student B: Since this is something I want to major in, this course will help me hopefully build
confidence and learn more about programming and what jobs you can go into. In
the future you could go into gaming or any type of web development or developing
anything.
Interviewer: You mind if I ask you just one more, in terms of colleges, have you ... You've
already applied to some of the colleges already?
Student B: Yes.
Interviewer: And which one are you hoping to get into, if you don't mind me ask.
Student B: I was looking more into UC Irvine.
Interviewer: Okay.
Student B: Because I've heard about their school of engineering, like computer science. I
heard from an aunt who went there that she was going to major in that but she
changed it, but I wanted to get into that school.
Interviewer: Have you thought about a career that you might be interested in pursuing after?
Student B: After I want to go into web development.
Interviewer: Nice. Nice. Well thank you so much, this was great. You've really been
tremendous.

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Appendix I
Student C Interview Transcript
Interviewer: Okay, so we're here today conducting an interview. The study is about Hispanic
female’s in computer science and we're looking primarily at understanding the
perspective of Latina women still in high school towards computer science. I want
to first start off the interview by just asking a couple of background information
questions, if you're okay with that. We'll talk about your family and then we'll talk
about your school experience and then more specifically about how you're doing in
the computer science class that you're in right now. Without further ado, you are
currently a senior?
Student C: I'm a junior.
Interviewer: Oh, junior? Okay. Can you talk a little bit about where you were born?
Student C: I was born in Mexico and I came here when I was a baby.
Interviewer: So all your schooling has been here in the States?
Student C: Yeah, all of it.
Interviewer: Okay. And your parents were also born in Mexico?
Student C: Yes, Born in Mexico
Interviewer: Both?
Student C: Yeah.
Interviewer: So the primary language spoken at home then was ...
Student C: Spanish.
Interviewer: Spanish. Is that still the language that you guys speak?
Student C: Yeah.
Interviewer: Have you always been in this district or have you attended schools in other
districts, as well?
Student C: No, I've been in the Baldwin Park District since I was little, so yeah.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 143

Interviewer: Besides the computer class that you're currently in, have you taken any other
computer classes?
Student C: Freshman year when we had computers, I guess that one.
Interviewer: Anything prior to, like in middle school, any tech classes or anything like that?
Student C: No.
Interviewer: The computer class that you took in ninth grade, that was just a semester long-
Student C: Yeah, just a semester.
Interviewer: Can you just briefly talk to me about how ... Do you guys have access to a
computer at home?
Student C: Yeah.
Interviewer: Have you always had access to a computer at home?
Student C: Yeah, actually, yeah.
Interviewer: Let's talk about some of the classes that you've been taking. Your past experience
in computer class that you took ... Was it with the same instructor?
Student C: No, I was in Mr. Saucedo.
Interviewer: You said it was a semester long course.
Student C: Yeah.
Interviewer: Can you just talk about that class and what was it and what was some of the things
that you remember and what you guys did?
Student C: I remember doing code.org which is kind of like what we do in computer sciences
right now because we use Snap and it's block programing so it's kind of the same
thing, very similar. So I remember that.
Interviewer: How was the demographics of the class? Was it more male, more female or was it
equal?
Student C: I feel it was equal.
Interviewer: What about the class that you're in now?
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Student C: Now, I think it's more male, yeah, it's more male. Definitely.
Interviewer: Has that ever occurred to you and has that ever influenced you in any way, the
demographics of how, as you said, the class that you're in right now, the computer
science class, that it is more male? Did it ever come to your attention?
Student C: Yeah, I noticed because it's like right there. You can tell because there's just a
small amount of girls but I still need to take it so I went for it.
Interviewer: Because of demographics in the class, does it ever affect your motivation in the
class or how-
Student C: In a way, it made me want to take it more because I feel like girls should go more
into it because I know it is a male-dominated field and I want to go into
engineering which is also male-dominated so it makes me want to take it because I
think girls can do as much as men.
Interviewer: Can I ask you a little bit about that?
Student C: Yeah.
Interviewer: So where did that come from? One, computer science is a male-dominated field
but I still want to go into that. Where do you think that came from for you?
Student C: Because I myself am interested in that, I've always been interested in tech stuff and
everything like that and my major, which I want to go into, which is engineering is
also that, it's related to that. I just really like it so I still want to take it. I don't really
mind that it's male-dominated. I do think girls should go into it.
Interviewer: Where do you think your interest in tech and computer and engineering came
from?
Student C: I guess from home because my dad really likes that stuff, too. He's always fixing
stuff, he's always coming up with little things at home and I saw him and I just ... it
caught my eye. I like looking at him doing it so ... I don't know, do you want me to
go into that?
Interviewer: Is there a particular moment or time that you can think of of seeing your dad doing
something at home that you remember or recall?
Student C: Not specifically, but when I was smaller I would just see him and that caught my
eye and that really interested me.
Interviewer: What does your dad do?
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Student C: My dad works at a car wash, actually.
Interviewer: Really. But at home, he's always fixing stuff and-
Student C: Yeah, he likes to do that. He likes to fix stuff, he just likes to work around the
house and stuff like that, with tech stuff.
Interviewer: Does he include you when he's doing that or are you just observing him?
Student C: No, I just watch.
Interviewer: You said that the demographics now in the class that you're in, the computer
science class that you're in, is very male-dominated. Do you ever look at it
differently? You say you obviously noticed it, but does it ever make you see the
class differently compared to other classes that are more balanced in terms of
males and females, or not really?
Student C: In a way, yeah, because I know guys are going through because they like it, too,
and I don't know, I just like ... I do notice it and I'm like, "I don't know why girls
don't go into ... " I don't know, they always go into girly stuff, I guess you could
say.
Interviewer: What does that look like? When you say girlie stuff, in your mind, what is that?
Student C: I feel that it's like teaching and design or stuff like that.
Interviewer: What about your parents, do you think your parents have that same perception that
you have or ...
Student C: I feel they do, too, but then, I don't know.
Interviewer: We can get into that. Let's see. You talked about your experience at home with
your dad. Was that the reason for taking the computer science here in school or
was it-
Student C: No, the reason I took it is because I want to go into engineering and my cousin in
college right now and she's taking ... She's going to be an engineer, too, and she
told me that she's had to code. One of her classes has to do with that and I'm like,
"Well, I'd like to get a head start so why not start now?"
Interviewer: Nice. My next question is have you been encouraged by others to take computer
science?
Student C: Yeah.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 146

Interviewer: So your cousin. How old is your cousin?
Student C: She is 19.
Interviewer: Are you guys close?
Student C: Yeah. I don't know if you remember her, Patricia [crosstalk 00:08:16].
Interviewer: Yeah.
Student C: ... my cousin.
Interviewer: Really?
Student C: Yeah.
Interviewer: That's funny. I was speaking about her and, "You know, she kind of reminds me of
a student I had before." I never put that together. We'll talk about that later. Has the
interaction with your cousin, Patricia, has she influenced your decision making to,
not only take the class now but to major in engineering, do you feel, or has that
come from other instructors, parents or siblings?
Student C: I feel she has influenced it but then again, it's also part of me. I feel it's both, in two
parts, I guess. I did get influenced by her because I'm like, "This is really
interesting," but I've always been interested in it and I would like to be a pilot
engineer or an astronaut, one of those.
Interviewer: Wonderful, wonderful. I'm just going to ask you about the ... Let me see, I'm sure
... So now let's talk a little bit about the class that you're in right now, this
computer science class. How would you describe your feelings and beliefs about
your ability in this computer science class where you're now a semester into the
class?
Student C: Yup.
Interviewer: How do you feel about it? How's your confidence level and your ability to do well
in this class?
Student C: I'm actually pretty confident because I get this stuff or if I don't get it I do like to
ask because I actually want to know because it's something that I'm interested in so
if I don't get it, I do like to ask questions so I can actually get it on my own.
Interviewer: Can I ask you about the interaction between what you see, not only between
yourself and the other students, but between the female and male students in the
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 147

class? Have you noticed anything or do you feel like everyone's sort of helping
each other out or do you-
Student C: I notice the guys usually help each other out because they're like a group so I
notice that.
Interviewer: What about for you or for the other women in the class? How is that?
Student C: I feel the girls are mostly shy in that class, so we don't really talk but sometimes,
yeah.
Interviewer: How many females would you say are in the class? Just guess.
Student C: There's about six, probably, seven.
Interviewer: Six, and what, 20, 25 students, maybe, in the-
Student C: Yeah, and the rest are guys.
Interviewer: If you were to ask for help, would you be more likely to ask a male or female
student?
Student C: I think a female student at first and if they don't get it, I would go to the male
students.
Interviewer: Really. Is that something that you thought about already? If I do need help I'm
more likely to go-
Student C: Yeah.
Interviewer: How come?
Student C: I don't know. I guess, in a way, I'm scared. I don't know because they're going to
think something so, I don't know. Because they're guys, I don't know. I feel ... I
don't know.
Interviewer: Coming into the class and seeing the demographics.
Student C: The first day I came in I was really surprised because I saw a lot of guys and
hardly any girls and I was like, "Oh, wow."
Interviewer: How did that make you feel?
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 148

Student C: I was a little scared at first because I was like, "Oh, I guess this might be a hard
course, I don't know." That actually proves to me that it was a male-dominated
field so I'm like, "Well ... "
Interviewer: Has that impression that you had, has it changed now a semester in?
Student C: Yeah, because my cousin has told me that when she goes to her conferences or the
creator fairs, there's a lot of girls, too. She's like, "It's not just guys. More girls are
actually getting into this."
Interviewer: Let's see. So we already talked about this, I'm going to skip that question because
you already addressed it. How confident are you that you are able to understand
the most difficult concepts or skills that are presented in this course?
Student C: I'm actually pretty confident because I just like to look over the stuff if I don't get
it. I like to ask questions or look over the stuff and then I feel confident. Then I do
it on my own and I do get it and I feel really happy that I'm getting it.
Interviewer: Talk briefly about the course that you're in now, the computer science course that
you're in now. Is it more group projects, are you working a lot of individual time or
do you feel balanced?
Student C: Most of it is individual, but we do kits and group projects sometimes because you
do have to collaborate. I know that, yeah.
Interviewer: Are the groups usually randomly assigned or do you get to pick?
Student C: We get to pick.
Interviewer: With you and the other women in the class, do you tend to stick together or do you
guys usually mix with the other boys in the class?
Student C: Actually, yeah, it's just like the girls' group and then the guys' group.
Interviewer: How is the interaction between the boys and the girls? How would you describe it?
Student C: We do talk and everything but when it comes to work, everybody goes on their
own.
Interviewer: Do you feel it's competitive?
Student C: Not necessarily, but I feel that it is sometimes you do have to work on this lab on
your own. It is individual stuff that we have to do.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 149

Interviewer: Do you ever feel supported or judged whenever you're presenting or doing
something in front of the class, in front the boys?
Student C: No, the whole class is very supportive of each other and I notice that. I really like
that about the class because everybody is supportive of each other in that class. We
all help each other out.
Interviewer: Great. I want to throw this out there. I know you told me that there was not one
particular moment that sparked this interest for you but if I asked for you to tell me
one memorable story that would really help me understand how you arrived at
your feelings and beliefs in computer science.
Student C: I guess it would be when my dad works on the computers, he tries to find a way to
... We had a computer and he was trying to connect it to the TV and he was
looking for a lot of stuff and then after a while he figured out what cables to use
and what to get so that we could just put something on the computer and then it
would appear on the TV. I don't know, I just really liked that because I'm like,
"Oh, that's really cool."
Interviewer: If you had to say one role model that you've had, who would you say that would
be?
Student C: I would say my cousin, actually.
Interviewer: Really?
Student C: Yeah.
Interviewer: Can you talk a little about why?
Student C: She was going into fifth grade so she came here not that young, but she's
accomplished a lot already.
Interviewer: Can you go a little bit into detail about some of the things, if you don't mind?
Student C: Patricia graduated with honors, she played soccer here, and she's at college right
now, UC Davis, and I really look up to her.
Interviewer: Do you think that her being that role model has really helped you out and
influenced your success?
Student C: Yeah.
Interviewer: As you said, the field of computer science is seen as predominantly male. Why do
you think so few women go into computer science?
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 150

Student C: I feel the ones that go in is because they actually like it and something that
interests them, with something that they're passionate about and they really like
because most girls are not into that stuff. When I tell friends, I'm like, "You should
take this class." When I tell them they're like, "No," they just say no and they nod
off and I'm like, "Okay, whatever."
Interviewer: Did that ever cross your mind or did you ever feel ... Because when you took this
class, did you have friends that you knew you were going to take it with?
Student C: No.
Interviewer: So no friends?
Student C: No.
Interviewer: Did it come across your mind like, "Oh no one's going to take it. I'm going to be
here on my own"?
Student C: I mean, yeah, it did but I'm like, "I want to take it," this is a class that it's going to
help me out, so I took it because I know it's going to help me out.
Interviewer: Students in that class, are they mostly juniors or seniors or is it mixed evenly?
Student C: Most of them are seniors, actually.
Interviewer: So you're taking it almost a year ahead, in a way?
Student C: Yeah.
Interviewer: Similar question. We talked about women going into computer science, what about
minority, under-represented minorities, Hispanics, Latinas? Why do you think so
few of them end up in the field of computer science?
Student C: So few of them. I feel that most want to go into social work and I feel because
that's a big issue, too. They feel like that they could help out more in that area,
that's what I think.
Interviewer: Do you think there's some cultural aspect to Hispanic women going more into, as
you said, social work than into computer science?
Student C: I feel it's just like what we see and then we want to help other people out because
we don't want them to go through bad things so they feel that they could help out
more in another area than in computer science.
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Interviewer: May I ask you this, in terms of your family, do they know that you're taking a
computer science course?
Student C: Yeah.
Interviewer: Are they supportive, would you say? How are they when you tell them that you're
taking a computer science course?
Student C: I tell them but they don't really mind. My mom was like, "Oh, it's good because
you know it's going to help you and everything." That's really it. They haven't
really told me anything about it.
Interviewer: Have you told them what you're thinking about majoring, though?
Student C: Yeah.
Interviewer: How did that go over with them?
Student C: When I told them they were like, "Well, at least it's going to help you, the class is
going to help you in the future."
Interviewer: You mentioned about Hispanic women more likely to go into social work.
Student C: Yeah.
Interviewer: Do you think your family thought maybe you would be going into social work or
to teaching?
Student C: No.
Interviewer: No. They knew that you'd be going into something else?
Student C: I feel they thought I would go into something related to math because that's my top
subject so I feel that's what they thought.
Interviewer: Hypothetically, do you think your family would have supported you if you'd
decided to go into any major?
Student C: I think, yeah.
Interviewer: Yeah? From your perspective as Latina, do you think computer science is seen as a
successful career for women?
Student C: For women. In general, I would say yes. For women, I'm not sure, actually.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 152

Interviewer: Do you think there might be a difference between for the men and for the women
in-
Student C: Yeah.
Interviewer: ... Hispanic culture?
Student C: Yeah, I feel that either way, males would get picked first when it came to giving a
job to someone. I feel they would still pick a male.
Interviewer: Let me ask you this. We know that there's so few women and you're trying to
encourage your friends to come and take this course, what do you think can be
done to increase the amount of women in this field? What would help you or
encourage you or your friends to come into this field, do you think?
Student C: I feel we tell them about all the options or all the jobs you can actually find with
this because I know that a lot of jobs now are related with computers so it's a job
that we will actually get because most of it is tech now, honestly.
Interviewer: So just making them informed of the career benefits to all of it?
Student C: That come with it, yeah.
Interviewer: Last question. So your experience in this course, how do you think it will help
influence your decision in majoring in computer science or engineering? Do you
think it's going to help you out as you move forward into college in a couple of
years and then into your career?
Student C: I think it will, actually, yeah. That's why I took it, because my cousin ... like she
says, she's an engineer and she told me she had to take ... One of her classes does
require her to start coding and she showed me some of it and she said it's not
complicated but she's ... And I told her about the class before, during summer, that
I was going to take and she was like, "Oh yeah, that's a good idea. That way you
can get a head start." She's like, "I didn't know anything," and then she's like, "That
way you know, you have a general idea of what it's going to be."
Interviewer: That's nice that you have that kind of support.
Student C: Yeah.
Interviewer: To help you out. I'm going to ask you one more question-
Student C: No, that's okay.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 153

Interviewer: ... because now that I'm thinking about it. You talked about how the career of
computer science might be seen differently for men or for women from a Hispanic
cultural standpoint. Would you say that there are, in terms of a Hispanic cultural
background, that there're certain careers that are accepted for Hispanic families for
women versus other careers, would you say?
Student C: I'm not sure, actually. I feel Hispanic parents just would want you to find a
successful career that you like, I don't know. That's what I think.
Interviewer: Do you think that they would be open for the child to define that successful career?
Student C: Yeah, I think they would be open to that. I know that my parents are. I think they
would have not minded any career I chose. They're just supporting me in anything
I choose.
Interviewer: Let me throw a curve ball at you. Hypothetically, you tell your parents you want to
major in engineering and they respond to you, "That's a guy career, you're going to
be wasting your time." What would be your response?
Student C: I would say that that is not true, there're more women are actually going into this
field and it is a field that will get me a successful job in the future and this is
something I want to do, too.
Interviewer: Do you think those words coming from your family would have discouraged you
from going into it or do you think yourself would have ...
Student C: I feel for a while it might have discouraged me but then again it's going to be my
life and it's going to be my own choice, my life that's going to be affected by it so I
would still go with my choice.
Interviewer: Alright. Wonderful, I think we went through all the questions really fast. That was
great. That was it. Thank you so much.

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Appendix J
Student D Interview Transcript
Interviewer: Well, thank you again for being here. The focus again of this study is to look at
Latinas in computers science and factors that might create their perspective about
their beliefs. And so ... we're here to gather some information about you and your
belief in the computer class that you're currently in. As well as a little bit of
background information, about how you've arrived and your belief and your
abilities, okay? So ... let's start off with a little bit about your background. Can you
talk about where you were born?
Student D: In Montclair.
Interviewer: Montclair, California.
Student D: Yes.
Interviewer: Parents?
Student D: I believe my dad was born here in the United States but was raised in Mexico.
Interviewer: Okay, do you know where in Mexico? It's okay.
Student D: I think Guadalajara.
Interviewer: Okay, and your mom?
Student D: I'm not sure. I believe she was born in Mexico, but she was raised over here in the
United States.
Interviewer: Okay. And the primary language that you guys speak at home?
Student D: English.
Interviewer: Is that always the ... was that the first language and only language pretty much,
that you guys speak at home?
Student D: Most-
Interviewer: Okay. I believe dad was born in Mexico, raised here. Mom was born here but
raised in Mexico.
Student D: No. My dad was born here but raised in Mexico, and my mom was born in Mexico
but raised here.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 155

Interviewer: Okay. Then you said the language that is most often spoken at home is English?
Student D: Yeah.
Interviewer: Okay. This interview is concerned around computers and your perspective on your
beliefs with the computers. Can I ask you if you guys have a computer at home?
Student D: Yeah.
Interviewer: Have you always had a computer at home?
Student D: No.
Interviewer: How old or what grade were you in when you remember when you guys got one?
Student D: Probably 7th grade.
Interviewer: 7th grade. Was there ever an issue of not doing your work at school or from school
because you didn't have a computer at home?
Student D: No.
Interviewer: Okay. So you wouldn't say that not having a computer at home for a few years in
any way impacted how well you did at school?
Student D: No. Most assignments that had to be done on the computer, I got them done at
school.
Interviewer: Okay. Let's talk a little bit about your school since we're heading in that direction.
Have you always been in this district?
Student D: Yes.
Interviewer: Okay. Besides the class that you're taking now on computers, have you taken a
similar class in computers before?
Student D: No.
Interviewer: Can you talk a little bit about the class that you're in right now? What's your
experience? Can you just talk just briefly about the class that you're in right now?
What is it and how long have you been in it? What's your initial thoughts on it?
Student D: I've been in it since the beginning of this semester, and I find it a little confusing
because of all the programs and stuff.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 156

Interviewer: Yeah.
Student D: But other than that ... I'm not really in that class much because of my soccer.
Interviewer: Okay.
Student D: Because I've been taken out of that class for games and stuff.
Interviewer: Is it at the end of the day? Sixth period?
Student D: Yeah. It's sixth period.
Interviewer: Okay. Prior to the class, have you had much experience with computers or tech?
Student D: No. The only experience I have with computers is with that class.
Interviewer: Okay. How has that affected your belief? What is your belief? You said it was a bit
confusing. Can you talk a little bit more about that? Being taken out of class for
soccer. How does that affect your belief in how well you can do in the class?
Student D: Well, I just find it really confusing because of all the programs and all the stuff
you have to remember. Since I'm being taken out of that class, I don't get to learn
all that stuff that is being taught that day. When I come back the next day, I'm a
little behind and I have to ask some friends, "Oh, what'd you guys do? Can you fill
me in?" I just find it really confusing with all the programs that you have to
remember and with all the networks and stuff.
Interviewer: Now you didn't request this course, right? You had to take it?
Student D: Yeah. It was a requirement.
Interviewer: Requirement. Can I ask you, if it hadn't been a requirement, do you think you
would have on your own chosen to take this computer science class?
Student D: I don't think so.
Interviewer: How come?
Student D: Because computers don't really interest me. It doesn't catch my eye when choosing
a class.
Interviewer: Let me ask you this. Computer science is typically seen as a male-dominated field
of study. As a woman, have you ever seen it or thought about it that way?
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 157

Student D: I have. If there's a problem with the computer at my house, it's mostly call my
brother.
Interviewer: Really?
Student D: Yeah. He knows a lot about that stuff.
Interviewer: Do you think that in general though, people that work on computers and people
that are in computer science, either in school or a career, tend to be more males?
Student D: Yeah.
Interviewer: Why? Why do you think that is?
Student D: I believe males find that stuff more ... I guess it catches their interest more and
they could learn it really quick.
Interviewer: Do you think that that in any way influences your motivation to ... In the class or to
take any more computer classes at all?
Student D: No.
Interviewer: No. Where do you think that motivation comes from? You said that you really
don't have that motivation to take it and that you wouldn't have chosen to take the
computer class if you didn't have to. How come?
Student D: I think if I were to take this class, I would have to have the curiosity of knowing,
"Oh, why is this and why is that about computers?" I feel like you have to be
raised with, "Oh, computer this, computer that," to actually want to learn that stuff.
Interviewer: Can I ask you just quickly, the class that you're in right now, the demographics, is
it even? Boys, girls.
Student D: Yeah.
Interviewer: Yeah. How's the interaction between the boys and the girls? Do you ever feel that,
as we talked about, the field is seen more as male-dominated? Can you give the
example of your brother at home, fixing the computers? Do you see interaction,
like they're equal, or do you see the boys in the class have a superiority or they feel
better at the class?
Student D: Yeah. The boys in my class would pretty much know more stuff and be caught on
more because they know the answer.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 158

Interviewer: Do you ever feel less than because of that? Do you ever feel like, "Maybe I can't
get it or I'm not that smart," because you have that perception about the boys?
Student D: No.
Interviewer: There is the AP computer science course. Are you aware of that?
Student D: Not until now.
Interviewer: You saw the elective. You went to the elective fair and you saw some of the other
computer classes that they showed you. Was there any interest in those classes or
no?
Student D: Well, I saw this one about web design and that really interests me.
Interviewer: Okay. There is some interest there. In terms of this class, how confident are you
that you'd be able to understand the most difficult concepts and skills in the class?
Student D: Biology?
Interviewer: No, no, no. Sorry. Your tech class that you're in.
Student D: If I was thrown a problem?
Interviewer: Yeah.
Student D: I don't think I would get it at all.
Interviewer: How is the support in the class? Do you feel supported? Do you feel like you can
get the help that you need?
Student D: Yeah. If I contact my teacher and if I ask questions, I probably will.
Interviewer: We're going to jump ahead. We talked about the field of computer science being
male-dominated, even though it's one of the fastest growing fields. What do you
think can be done to improve and have more women go into computer science?
Student D: I think just making a requirement, I guess, for women to start taking these classes.
Just try to get their interest in it.
Interviewer: Why do you think there's so few women in computer science right now?
Student D: Probably because they don't catch interest like boys and games. They're all about
technology and girls are not really into video games or stuff.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 159

Interviewer: Growing up with your background and your parents' background, do you think
there are certain gender biases about the field of computer science? As you talked
about boys with their computers and their games and stuff like that, do you think
culturally there are some biases? Like women should be going into certain fields.
Boys, it's okay for them to go into other fields. Has that ever come up in your
experience? In your family about certain careers or certain things that because
you're a girl?
Student D: No. My parents are mostly like, "Oh, girls should clean and boys should do the
more manly stuff and take out the trash."
Interviewer: So what would your parents say or what do you think they would say if you told
them that you wanted to major in computer science?
Student D: I think they would support me.
Interviewer: Yeah?
Student D: Yeah.
Interviewer: Do you think that what we can do for ... What you said, to get more women in
computer science. Do you think it's the same for minorities like Latinas in the field
or do you think that we need to focus differently on how to get more
underrepresented minorities like Latinas in the field?
Student D: I think it would be the same.
Interviewer: Do you think your experience in taking the next course ... Because you said the
web design course caught your interest. Do you think that after taking that course,
you might change your perspective about the field of computer science? That was
something that you yourself ... It's not a requirement. It's something that you want.
You think you might see it differently that way because it is of your choosing?
Student D: Yeah, because if I caught that interest myself and not being a requirement, I think
my interest into computer science would grow more.
Interviewer: Just to clarify, you said you think your family would support you if in fact you said
you wanted to major in computer science. Do you think that they would see
computer science as a successful career for a woman?
Student D: I'm not sure, but all I know is that they probably would support me. I'm not sure if
they'd think that's the right job or something for a woman.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 160

Interviewer: All right. I think that's pretty much it. It wasn't that long. I think we're going to end
there.
Student D: All right.

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 161

Appendix K
Student E Interview Transcript
Interviewer: Okay. So, first of all, thank you again for willing to participate to be interviewed.
Again, the focus of this study is around self-efficacy of Latinos in computer
science and kind of potential factors that gives them that perspective.
Interviewer: Another purpose of it is to just kind of gather background information to give us
some insight into how that perspective is created.
Interviewer: So we want to just kind of talk about yourself. Can you just briefly talk about what
grade you're in, the computer class that you're in and yeah, start with that.
Student E: I'm a ninth grader in high school, and I'm in tech right now with Ms.O
Interviewer: Can you talk briefly about like what that tech ... Like what is tech, and what kinds
of things do you do in the class?
Student E: We do like coding and like a lot of keyboarding, typing and stuff.
Interviewer: And is that like the first class that you had like that, or have you taken any class in
middle school?
Student E: No. This is the first class I had.
Interviewer: Was this class your choice or was it mandatory?
Student E: It was mandatory.
Interviewer: Okay. A semester long class?
Student E: Yeah.
Interviewer: Have you thought about taking any additional classes in computer science?
Student E: Yeah, I thought about it.
Interviewer: Do you know which one you might be taking?
Student E: I don't know. But I want to do like coding.
Interviewer: Now, you said you haven't taken any additional class in computer science. Have
you done like coding or anything like that? No?
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 162

Student E: No, I never did.
Interviewer: So is this your first experience ...
Student E: Yeah.
Interviewer: ... with it? Do you know anyone that has done work like in coding or programming
or anything in like a computer science related field at all?
Student E: No.
Interviewer: No? What about at home? Can you talk to us just a little bit about home? Do you
guys have a computer at home?
Student E: Yeah.
Interviewer: Have you always had one at home?
Student E: Yeah.
Interviewer: What about in terms of like your family background? Can you talk a little bit about
where you were born and your parents and kind of the language you guys speak at
home?
Student E: I was born here. My mom was born in Mexico and my dad was born here too. And
... Wait. What was the question?
Interviewer: Well, the primary language that you guys speak at home.
Student E: Oh, we speak English.
Interviewer: Okay. So can we just briefly go back to talking about the tech class that you're in
right now. Can you just talk about some of the things that you guys ... I mean, you
actually kind of already did talk about that. Can you talk about the demographics
of the class? Is it an even mix of boys and girls or is it more one than the other?
Student E: It's an even mix of boys and girls.
Interviewer: Okay. And can you just talk about like how confident you feel in your ability in
that class? Do you feel very confident?
Student E: Yeah. It's like pretty easy, so ...
Interviewer: What do you think contributes to kind of that feeling, that confidence when you're
doing that stuff?
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 163

Student E: Well, like anyone can do it in the class, so I feel like everyone has their own
confidence in that, because like ... I don't know. It's like simple.
Interviewer: So if I asked you how confident you would feel about understanding like the most
difficult concepts in the class, what do you think so far?
Student E: Well, she hasn't really gave us anything difficult.
Interviewer: Okay.
Student E: So I think everything's still kind of like in the beginning of the simplicity of the
class.
Interviewer: The field of computer science is often seen, or it is a male dominated field. Why
do you think there are so few women going into computer science?
Student E: I think 'cause like we're not really exposed to it, or like ... 'cause I remember in
elementary it was only boys who wanted to do it 'cause they never really gave us a
brief understanding of what it was. So I think if they would have told us more
about it and kind of gave us a little demo or presentation about it, we would
probably do it, because I enjoy it.
Interviewer: So can you just talk a little bit about that, because you mentioned in elementary
school?
Student E: Yeah, and in junior high I didn't really see it.
Interviewer: But there was an opportunity to take classes or to do coding or whatever?
Student E: Yeah.
Interviewer: And it was just whoever ... How did that go? I mean, how did they introduce it to
you guys or how were you aware of it? Go ahead.
Student E: Like in sixth grade they had this thing called STEM. And like all the boys were
like into it. But it was only the boys who were like in honors classes.
Interviewer: Okay.
Student E: And the girls like, they kind of pushed away from that and they wanted to do like
leadership or something else, but they didn't every really tell us what STEM really
was. Because like even the boys ... I'd say there was like 10 boys that joined.
Interviewer: Why do you think that is? Who do you think sort of the boys sort of kind of
gravitated towards it and, like you said, the girls went to like leadership?
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 164

Student E: I don't know. I think it's just like we didn't really find any interest in it, because we
weren't able to see what it was.
Interviewer: Yeah. And now, being in the class, seeing what it is?
Student E: Yeah. I like it, because I got to experience it.
Interviewer: Now, you're in the class you said because you had to take the class. It's mandatory.
Student E: Yeah.
Interviewer: If the class wasn't mandatory, do you think you would have taken the class on your
own or what do you think?
Student E: I probably wouldn't because I always felt like STEM was just like making things,
not really like going on the computer and making like codes and stuff.
Interviewer: So just being aware of what it is.
Student E: Yeah. Like they never told us that computer science was also part of like the big
companies like Apple and all that.
Interviewer: And so, this leads me to my next question. What do you think can be done to
improve the underrepresentation of women in fields such as computer science?
Student E: I think they should talk about it more and like have like specific like presentations
for us, like maybe in the gym or something, to just tell us more about it.
Interviewer: Would it make a difference if it was a woman giving that presentation or a man
giving that presentation to you?
Student E: I don't think it really would, because it's not like ... I don't know. If you like it, you
like it. If you don't, you don't. It doesn't matter who's saying it.
Interviewer: So as I mentioned before, women are, of course, underrepresented in the field. But
amongst women, in particular, Latinos are significantly underrepresented in the
field. Any thoughts on why might specifically Latinos and people of Hispanic
descent might be underrepresented and not going into computer science?
Student E: Maybe due to our backgrounds and how we are or how we're ... Like at home, like
my parents never told me about STEM or anything. And my family like they're
just like, "Oh, yeah, it's like just science." Like they never really went in depth
with it.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 165

Interviewer: Do you think that in your background do you think if you told your parents you
were going to like major in computer science, how do you think they would react
to that?
Student E: I think they would be happy for me, because if that's what I want to do in the
future, they would accept it.
Interviewer: Do you think there's any like cultural or bias or stereotypes about women going
into STEM or STEM fields or even computer science at all from your background?
Student E: No, not really, because we're never ... Well, we're not exposed to computer
science. Like we're ... Like they don't talk about it, so it's like we don't know
anything about it mostly.
Interviewer: Do you have any siblings?
Student E: Yeah, I have two, but they're not into that either.
Interviewer: Brothers? Sisters?
Student E: Just sisters.
Interviewer: Sisters? Hypothetical situation. Do you think that, or would you say that your
parents have ... Would you say your parents have a belief about certain careers or
fields that are for women and certain that are for men?
Student E: No. My parents think like everyone is like equal and there's no like gender to do
one specific job. Like everyone needs to contribute.
Interviewer: And you said your parents are from Mexico?
Student E: Yeah.
Interviewer: And from their background do you think there is any cultural bias about women in
science or women in STEM at all?
Student E: In like my cultural background?
Interviewer: Yeah, or from your parents' perspective. Like from growing up in Mexico do you
think there's any like stereotype or any bias about women going into STEM?
Student E: I'm not sure. I've never really asked them. But I would say like probably not.
Because like, again, I don't see a lot of Latino women in STEM, and even when I
do go to Mexico, if I were to ask them that, they probably wouldn't know what it
was.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 166

Interviewer: Do you think still today?
Student E: Yeah.
Interviewer: Anything different about in particular because it's about how you would encourage
Latinos to get into STEM besides what you mentioned already, exposing them,
having rallies to get women? Anything in particular about Latinos that we can do
to encourage more to go into the field?
Student E: No. I think just ... 'cause my background, I feel like our background is more like ...
their people are more closed minded and they don't like to see what things are.
Like they just think of it as like, "Oh, that's just for smart people. Like I don't
deserve to be there." I feel that's why some people don't do it.
Interviewer: And can you talk a little bit more about that? You said that your background, they
kind of see it as close minded? What do you mean?
Student E: Yeah, like ... I don't know. They're always like ... Okay. When I go to Mexico, my
aunts like, they're like, "Oh, that's a man's job," like to go outside and go to like a
working field where it's ... like working on cars. Like that's a man's job. Like
women can't do that.
Interviewer: So there is like some stereotypes and biases about ...
Student E: Yeah.
Interviewer: ... the kind of job men do ...
Student E: Yeah.
Interviewer: ... versus what kind of job women. Do you think your parents still have that as well
or ...
Student E: No, my parents are not like that.
Interviewer: How do you think growing up if they were, if they had that kind of mentality, how
do you think that might have impacted, or do you think it would have impacted
your decision to come ...
Student E: I think it would, because like I'd feel like I'd want to make my parents proud. So by
doing something they want me to do and making them happy, I'd probably do it.
Interviewer: Let me see. Do you ever feel any less confident when you're interacting with like
the other boys in the class at all? Like do you ever say, "Oh, the boys are in there,
or they're getting it because they're smarter, because they're boys and they can get
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 167

this easier"? Or do you ever question your ability because you're a woman in
computer science?
Student E: Not really, no.
Interviewer: Would the demographics of the class ever ... Like if you walked into a computer
science class let's say next year and it was all boys and you were only a handful of
females in the class, how do you think you would react?
Student E: I think I'd feel fine. Like because they're there for a reason because they like it.
Interviewer: All right. I think that's it, honestly. I think you've done a good job and answered all
my questions. All right. We're going to stop it there. Thank you.
Student E: You're welcome.

LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 168

Appendix L
Recruitment Script

Good afternoon, my name is William Sullivan, I’m a doctoral candidate working on my
dissertation study with the Rossier school of education at the University of Southern California.
The purpose of the study will exam current levels of high school women’s self-efficacy (SE) in
computer science (CS) as well as factors that might influence Latina and other underrepresented
minorities groups from going into computer science as a major and/or career. The research will
help me, and society, understand what are the potential underlying conditions that are
contributing to the consistent underrepresentation of Hispanic females in the sub-STEM field of
computer science. Findings from this study will go a long way to develop a better understanding
of the limitations and barriers Hispanic females face and outline potential solutions on how to
increase their representation in the field. Since the study is exploring current levels of SE for
females in computer science course, only female students will be eligible to volunteer for the
study.
The study will ask participates to take a one-time, online 15-question survey in their
computer science class. The survey should take approximately 15 minutes to complete. Your
participation is voluntary and your involvement in the study in no way will impact your grade for
this class or any other class. Although there is no risk associated with this study, if you do not
wish to participate, you may stop your involvement at any time. Surveys will be confidential, and
will only ask for your student identification number for potential recruitment in part two of the
study. All female students will be eligible to take the survey; however, only those identified as
Latina will be eligible to participate in the qualitative phase, phase two of the study.
Based on teacher recommendations, six students will be asked to volunteer for phase two
of the study. Phase two of the study will ask for only 6 participates to volunteer to be interviewed
individually once for approximately 45-minutes afterschool in the school library and observed
twice for the whole period during their CS class. No names will appear on the final write up of
the dissertation. Students that are recruited for phase two of the study will be de- identified with
names coded with pseudonyms, such as Student-A, Student-B, etc. Your response to the survey
and interview questions are completely confidential, not even your instructor will see your
responses.
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 169

Please review the document careful as it covers in detail the information I’ve gone over
with you today. Please note your participation in the study is voluntary and in no way will impact
your grade for this class and any other class. In addition, there is no compensation for your
involvement in the study. If you would like to participate in the study, an assent form is being
passed out to you today as well as a parent letter of consent. As minors, your parent consent is
required in order to participate in the study. Please review both documents careful, sign along
with parent consent, and return both documents to your instructor by the end of the week. Surveys
will be conducted in class next week. I thank for your consideration. If you or your parents have
any questions in regards to the study, my contact information is provided on both documents.
If you have any further questions regarding any part of this study, I can be reached at

Sierra Vista High School
3600 N Frazier St
Baldwin Park Ca
91706

Wssullivan176@bpusd.net or (626) 960-7741 x 2416
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 170

Appendix M
HSLS:09 Student Questionnaire: Appendix A Section D: Science Experiences
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Screen: Introduction to Section D
Question wording: Now we are going to ask you a few questions about your experiences with
science.

Routing: Go to S1 D01.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Screen: S1 D01
Question wording: How much do you agree or disagree with the following statements?
Variable: S1SPERSON1
Item wording: You see yourself as a science person
1=Strongly agree
2=Agree
3=Disagree
4=Strongly disagree
Variable: S1SPERSON2
Item wording: Others see you as a science person
1=Strongly agree
2=Agree
3=Disagree
4=Strongly disagree
Routing: Go to S1 D02.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Screen: S1 D02
Question wording: When you are working on a science assignment, how often do you think you
really
understand the assignment?
Variable: S1SUNDERST
1=Never
2=Rarely
3=Sometimes
4=Often
Routing: go to S1 D03.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Screen: S1 D03
Are you currently taking a science course this fall?
[Were you taking a science course in the fall of 2009?]
Note: For interviews conducted prior to late-December 2009, this question appeared in the un-
bracketed
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 171

form above; for interviews conducted late-December 2009 or later, this question was
displayed using the bracketed text above.
Variable: S1SFALL09
1=Yes
0=No
Routing: If S1SFALL09=1 go to S1 D04; else if
Y_SGRP=1 go to Introduction to Section E; else
if Y_SGRP=2 go to Introduction to Section C.
Note: So as to more evenly distribute item non-response resulting from an inability to complete
the
student questionnaire within the allotted time, the survey instrument rotated the order in which
certain
sections of the student questionnaire were administered. Y_SGRP=1 indicates that student
questionnaire
sections were administered in the following order: A, B, C, D, E, F, G; Y_SGRP=2 indicates
that the
student questionnaire sections were administered in the following order: A, B, D, C, G, F, E.
Appendix A. Base-Year Questionnaires
HSLS:09 Base-Year Data File Documentation A-21
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Screen: S1 D04
Question wording: What science course(s) are you currently taking this fall?
[What science course(s) were you taking in the fall (2009)?]
(Check all that apply.)
Note: For interviews conducted prior to late-December 2009, this question appeared in the un-
bracketed
form above; for interviews conducted late-December 2009 or later, this question was
displayed using the bracketed text above.
Variable: S1BIO1S09
Item wording: Biology I
0=No
1=Yes
Variable: S1EARTHS09
Item wording: Earth Science
0=No
1=Yes
Variable: S1PHYSS09
Item wording: Physical Science
0=No
1=Yes
Variable: S1ENVS09
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 172

Item wording: Environmental Science
0=No
1=Yes
Variable: S1PHYSIC1S09
Item wording: Physics I
0=No
1=Yes
Variable: S1INTGS1S09
Item wording: Integrated Science I
0=No
1=Yes
Variable: S1CHEM1S09
Item wording: Chemistry I
0=No
1=Yes
Variable: S1INTGS2S09
Item wording: Integrated Science II or above
0=No
1=Yes
Variable: S1ANATOMYS09
Item wording: Anatomy or Physiology
0=No
1=Yes
Variable: S1ADVBIOS09
Item wording: Advanced Biology such as Biology II, AP, or IB
0=No
1=Yes
Variable: S1ADVCHEMS09
Item wording: Advanced Chemistry such as Chemistry II, AP, or IB
0=No
1=Yes
Variable: S1GENS09
Item wording: General Science
0=No
1=Yes
Appendix A. Base-Year Questionnaires
A-22 HSLS:09 Base-Year Data File Documentation
Variable: S1TECHS09
Item wording: Principles of Technology
0=No
1=Yes
Variable: S1LIFES09
Item wording: Life Science
0=No
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 173

1=Yes
Variable: S1ADVPHYSIC09
Item wording: Advanced Physics such as Physics II, AP or IB
0=No
1=Yes
Variable: S1OTHENVS09
Item wording: Other earth or environmental sciences such as ecology, geology, oceanography,
or
meteorology
0=No
1=Yes
Variable: S1OTHBIOS09
Item wording: Other biological sciences such as botany, marine biology, or zoology
0=No
1=Yes
Variable: S1OTHPHYS09
Item wording: Other physical sciences such as astronomy or electronics
0=No
1=Yes
Variable: S1OTHS09
Item wording: Other science course
0=No
1=Yes
Routing: Go to S1 D05.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Screen: S1 D05
Question wording: Why are you taking [fall 2009 science course]?
[If late December or later add:
(If you are no longer taking this course, think back to the fall when you answer this question and
the
questions that follow.)]
Note: Question wording was customized such that the specific science type indicated by each
respondent (on Screen S1 D04) was displayed in place of "fall 2009 science course"; if the
respondent
indicated taking more than one science course during fall 2009, this question was asked only
once and
referred to the student-indicated course type appearing first in the following list: "Advanced
Physics",
"Advanced Chemistry", "Advanced Biology", "Anatomy or Physiology", "Environmental
Science",
"Integrated Science II or above", "Integrated Science I", "Principles of Technology", "Physics I",
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 174

"Chemistry I", "Biology I", "a biological sciences course", "Earth Science", "an earth or
environmental
science course", "Life Science", "Physical Science", "a physical science course", "General
Science".
Variable: S1SENJOYS
Item wording: You really enjoy science
0=No
1=Yes
Variable: S1SCHALLENGE
Item wording: You like to be challenged
0=No
1=Yes
Variable: S1SHSREQ
Item wording: You had no choice, it is a school requirement
0=No
1=Yes
Appendix A. Base-Year Questionnaires
HSLS:09 Base-Year Data File Documentation A-23
Variable: S1SCOUNSEL
Item wording: The school counselor suggested you take it
0=No
1=Yes
Variable: S1SPARENT
Item wording: Your parent(s) encouraged you to take it
0=No
1=Yes
Variable: S1STEACHER
Item wording: A teacher encouraged you to take it
0=No
1=Yes
Variable: S1SNOOTHR
Item wording: There were no other science courses offered
0=No
1=Yes
Variable: S1SCLGADM
Item wording: You will need it to get into college
0=No
1=Yes
Variable: S1SCLGSUCC
Item wording: You will need it to succeed in college
0=No
1=Yes
Variable: S1SCAREER
Item wording: You will need it for your career
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 175

0=No
1=Yes
Variable: S1SASSIGNED
Item wording: It was assigned to you
0=No
1=Yes
Variable: S1SOTHREASN
Item wording: Some other reason
0=No
1=Yes
Variable: S1SNOREASON
Item wording: You don't know why you are taking this course
0=No
1=Yes
Routing: go to S1 D06.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Screen: S1 D06
Question wording: How much do you agree or disagree with the following statements about
your
[fall
2009 science] course?
Note: Question wording was customized such that the specific science type indicated by each
respondent (on Screen S1 D04) was displayed in place of "fall 2009 science course"; if the
respondent
indicated taking more than one science course during fall 2009, this question was asked only
once and
referred to the student-indicated course type appearing first in the following list: "Advanced
Physics",
"Advanced Chemistry", "Advanced Biology", "Anatomy or Physiology", "Environmental
Science",
"Integrated Science II or above", "Integrated Science I", "Principles of Technology", "Physics I",
"Chemistry I", "Biology I", "a biological sciences course", "Earth Science", "an earth or
environmental
science course", "Life Science", "Physical Science", "a physical science course", "General
Science".
Variable: S1SENJOYING
Item wording: You are enjoying this class very much
1=Strongly agree
Appendix A. Base-Year Questionnaires
A-24 HSLS:09 Base-Year Data File Documentation
2=Agree
3=Disagree
4=Strongly disagree
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 176

Variable: S1SWASTE
Item wording: You think this class is a waste of your time
1=Strongly agree
2=Agree
3=Disagree
4=Strongly disagree
Variable: S1SBORING
Item wording: You think this class is boring
1=Strongly agree
2=Agree
3=Disagree
4=Strongly disagree
Routing: Go to S1 D07.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Screen: S1 D07
Question wording: How much do you agree or disagree with the following statements about the
usefulness of your [fall 2009 science] course? What students learn in this course...
Note: Question wording was customized such that the specific science type indicated by each
respondent (on Screen S1 D04) was displayed in place of "fall 2009 science course"; if the
respondent
indicated taking more than one science course during fall 2009, this question was asked only
once and
referred to the student-indicated course type appearing first in the following list: "Advanced
Physics",
"Advanced Chemistry", "Advanced Biology", "Anatomy or Physiology", "Environmental
Science",
"Integrated Science II or above", "Integrated Science I", "Principles of Technology", "Physics I",
"Chemistry I", "Biology I", "a biological sciences course", "Earth Science", "an earth or
environmental
science course", "Life Science", "Physical Science", "a physical science course", "General
Science".
Variable: S1SUSELIFE
Item wording: is useful for everyday life.
1=Strongly agree
2=Agree
3=Disagree
4=Strongly disagree
Variable: S1SUSECLG
Item wording: will be useful for college.
1=Strongly agree
2=Agree
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 177

3=Disagree
4=Strongly disagree
Variable: S1SUSEJOB
Item wording: will be useful for a future career.
1=Strongly agree
2=Agree
3=Disagree
4=Strongly disagree
Routing: Go to S1 D08.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Screen: S1 D08
Question wording: How much do you agree or disagree with the following statements about
your
[fall
2009 science] course?
Note: Question wording was customized such that the specific science type indicated by each
respondent (on Screen S1 D04) was displayed in place of "fall 2009 science course"; if the
respondent
indicated taking more than one science course during fall 2009, this question was asked only
once and
referred to the student-indicated course type appearing first in the following list: "Advanced
Physics",
"Advanced Chemistry", "Advanced Biology", "Anatomy or Physiology", "Environmental
Science",
Appendix A. Base-Year Questionnaires
HSLS:09 Base-Year Data File Documentation A-25
"Integrated Science II or above", "Integrated Science I", "Principles of Technology", "Physics I",
"Chemistry I", "Biology I", "a biological sciences course", "Earth Science", "an earth or
environmental
science course", "Life Science", "Physical Science", "a physical science course", "General
Science".
Variable: S1STESTS
Item wording: You are confident that you can do an excellent job on tests in this course
1=Strongly agree
2=Agree
3=Disagree
4=Strongly disagree
Variable: S1STEXTBOOK
Item wording: You are certain you can understand the most difficult material presented in the
textbook used in this course
1=Strongly agree
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 178

2=Agree
3=Disagree
4=Strongly disagree
Variable: S1SSKILLS
Item wording: You are certain you can master the skills being taught in this course
1=Strongly agree
2=Agree
3=Disagree
4=Strongly disagree
Variable: S1SASSEXCL
Item wording: You are confident that you can do an excellent job on assignments in this course
1=Strongly agree
2=Agree
3=Disagree
4=Strongly disagree
Routing: if student's school did not agree to their teachers responding to the HSLS Teacher
Questionnaire, go to S1 D11;
else if pre-loaded science teacher names are available, go to S1 D09;
else if pre-loaded science teacher names are not available, go to S1 D10.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Screen: S1 D09
Question wording: What is the name of your [fall 2009 science] teacher?
Note: Question wording was customized such that the specific science type indicated by each
respondent (on Screen S1 D04) was displayed in place of "fall 2009 science course"; if the
respondent
indicated taking more than one science course during fall 2009, this question was asked only
once and
referred to the student-indicated course type appearing first in the following list: "Advanced
Physics",
"Advanced Chemistry", "Advanced Biology", "Anatomy or Physiology", "Environmental
Science",
"Integrated Science II or above", "Integrated Science I", "Principles of Technology", "Physics I",
"Chemistry I", "Biology I", "a biological sciences course", "Earth Science", "an earth or
environmental
science course", "Life Science", "Physical Science", "a physical science course", "General
Science".
Variable: not delivered, but used to help link students and science teachers
1=[pre-loaded science teacher #1]
2=[pre-loaded science teacher #2, if available]
3=[pre-loaded science teacher #3, if available]
4=[pre-loaded science teacher #4, if available]
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 179

5=[pre-loaded science teacher #5, if available]
6=[pre-loaded science teacher #6, if available] 7=[pre-
loaded science teacher #7, if available]
8=Another teacher
Routing: If a pre-loaded teacher is selected from the dropdown menu, go to S1 D11;
Else if the last response option ("Another teacher") is selected, or no response is provided, go to
S1 D10.
Appendix A. Base-Year Questionnaires
A-26 HSLS:09 Base-Year Data File Documentation
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Screen: S1 D10
Question wording: What is your [fall 2009 science] teacher's name?
Note: Question wording was customized such that the specific science type indicated by each
respondent (on Screen S1 D04) was displayed in place of "fall 2009 science course"; if the
respondent
indicated taking more than one science course during fall 2009, this question was asked only
once and
referred to the student-indicated course type appearing first in the following list: "Advanced
Physics",
"Advanced Chemistry", "Advanced Biology", "Anatomy or Physiology", "Environmental
Science",
"Integrated Science II or above", "Integrated Science I", "Principles of Technology", "Physics I",
"Chemistry I", "Biology I", "a biological sciences course", "Earth Science", "an earth or
environmental
science course", "Life Science", "Physical Science", "a physical science course", "General
Science".
Variable: not delivered, but used to help link students and science teachers
1=Mr.
2=Mrs.
3=Ms.
4=Miss
5=Dr.
Variable: not delivered, but used to help link students and science teachers
Item wording: First name:
Variable: not delivered, but used to help link students and science teachers
Item wording: Last name:
Routing: go to S1 D11.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 180

Screen: S1 D11
Question wording: How much do you agree or disagree with the following statements about
[your
science teacher]? Remember, none of your teachers or your principal will see any of the answers
you provide. Your science teacher...
Note: Question wording was customized in the survey instrument such that the name of
the respondent's science teacher (if available) was displayed in place of "your science
teacher". Variable: S1STCHVALUES
Item wording: values and listens to students' ideas.
1=Strongly agree
2=Agree
3=Disagree
4=Strongly disagree
Variable: S1STCHRESPCT
Item wording: treats students with respect.
1=Strongly agree
2=Agree
3=Disagree
4=Strongly disagree
Variable: S1STCHFAIR
Item wording: treats every student fairly.
1=Strongly agree
2=Agree
3=Disagree
4=Strongly disagree
Variable: S1STCHCONF
Item wording: thinks every student can be successful.
1=Strongly agree
2=Agree
3=Disagree
4=Strongly disagree
Variable: S1STCHMISTKE
Item wording: thinks mistakes are okay as long as all students learn.
1=Strongly agree
Appendix A. Base-Year Questionnaires
HSLS:09 Base-Year Data File Documentation A-27
2=Agree
3=Disagree
4=Strongly disagree
Variable: S1STCHTREAT
Item wording: treats some kids better than other kids.
1=Strongly agree
LATINAS’ SE IN CS AND POTENTIAL FACTORS UNDERGIRDING THEIR PERSPECTIVE 181

2=Agree
3=Disagree
4=Strongly disagree
Variable: S1STCHINTRST
Item wording: makes science interesting.
1=Strongly agree
2=Agree
3=Disagree
4=Strongly disagree
Variable: S1STCHMFDIFF
Item wording: treats males and females differently.
1=Strongly agree
2=Agree
3=Disagree
4=Strongly disagree
Variable: S1STCHEASY
Item wording: makes science easy to understand.
1=Strongly agree
2=Agree
3=Disagree
4=Strongly disagree
Routing: If Y_SGRP=1 then go to Introduction to Section E;Else
if Y_SGRP=2 then go to Introduction to Section C.
Note: So as to more evenly distribute item non-response resulting from an inability to complete
the
student questionnaire within the allotted time, the survey instrument rotated the order in which
certain
sections of the student questionnaire were administered. Y_SGRP=1 indicates that student
questionnaire
sections were administered in the following order: A, B, C, D, E, F, G; Y_SGRP=2 indicates that
the student questionnaire sections were administered in the following order: A, B, D, C, G, F, E.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Abstract (if available)

Abstract This study aimed at understanding the current levels of self-efficacy as well as explore the contributing factors of high school Hispanic females currently enrolled in computer science (CS) courses. Using a mixed-method approach, the study found no statistical difference of self-efficacy between Hispanic and non-Hispanic female students. When conducting a qualitative analysis, three emergent themes were found as potential contributing factors to their science self-efficacy, motivational, environmental, and role models. Of the three, students’ internal motivation resonated highest amongst respondents, specifically a pattern that was inherent of a growth-mindset. Findings suggestions that students’ mindsets, irrespective of the content area, such as computer science, will likely influence their self-efficacy in any given subject. This appeared to differ from the body of literature, as most previous studies focused on factors related to CS

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Asset Metadata

Creator Sullivan, William Scott (author)

Core Title Latinas’ self-efficacy in computer science and potential factors undergirding their perspective

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 07/24/2019

Defense Date 07/22/2019

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

Tag Bandura,Computer Science,CS,equality,gender,gender differences,gender equality,growth mindset,High School,Hispanic,Latina,male-dominated,OAI-PMH Harvest,Race,retention,self-efficacy,STEM

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Freking, Fredrick (committee chair), Herrera, Richardo (committee member), Maddox, Anthony (committee member)

Creator Email sullivan8885@hotmail.com,wssulliv@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-189692

Unique identifier UC11663256

Identifier etd-SullivanWi-7588.pdf (filename),usctheses-c89-189692 (legacy record id)

Legacy Identifier etd-SullivanWi-7588.pdf

Dmrecord 189692

Document Type Dissertation

Format application/pdf (imt)

Rights Sullivan, William Scott

Type texts

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

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

Repository Name University of Southern California Digital Library

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