This chapter highlights research literature on girls and women of color in technology and computing fields from the last 15 years (2005-2020) in light of the structural and social factors at the K-12, higher education, and workplace levels that hinder or support them. The term structural factors refers to institutional or cultural aspects of a given context, including “demographic composition” (Ahuja, 2002; Armstrong et al., 2018) and “basic elements of norms, beliefs, and values that regulate social action” and their impacts (Bernardi et al., 2007, p. 163; see also Parsons, 1951). Structural factors constitute a set of normative and cultural models that define actors’ expectations about behaviors when interacting with one another. Social factors refer to social and cultural views, experiences, and biases that incorporate and affect external views of girls and women of color (e.g., family support, stereotyping) that are held in society in general, as well as the internal view that girls and women of color have of themselves (e.g., self-efficacy, self-expectations) (Ahuja, 2002; Ragins and Sundstrom, 1989) (Figure 2-1). Research demonstrates that both structural and social factors can affect individuals’ decisions and opportunities to enter, persist, and advance in education and careers in CS/tech (Ahuja, 2002; Armstrong et al., 2018).
This chapter is based on findings from multiple projects. First and foremost, it draws from literature identified and summarized by a team of researchers, led by Maria Ong,1 at TERC2 in their three-year National Science Foundation–funded project, “Literature Analysis and Synthesis of Women of Color in
1 Ong is a member of the National Academies Committee on Addressing the Underrepresentation of Women of Color in Tech.
2 TERC is an independent research-based non-profit organization focused on STEM education pre-K-12, postsecondary, and adult education.
Technology and Computing.”3 Literature included books, book chapters, peer-reviewed articles, and gray literature.4 The chapter also draws from a literature review commissioned by the National Academies, written by Heather Lavender,
3 The Literature Analysis and Synthesis of Women of Color in Technology and Computing (NSF Award ID HRD-1760845) team consists of principal investigator Maria Ong, co-principal investigator Nuria Jaumot-Pascual, Audrey Martínez-Gudapakkam, and Christina B. Silva. A detailed description of the methods—including pre-search activities (e.g., testing and selecting electronic literature databases, selecting search terms); conducting literature searches; literature selection (i.e., comparing the content of each literature piece against selection criteria and deciding if it should be discarded or kept for the synthesis); memo writing to summarize each piece for later analysis; codebook development; and coding and thematic analysis—may be found in Ong et al. (2020).
4 “Gray literature” refers to pieces of literature that are unpublished or published in non-commercial form, such as conference proceedings, dissertations, and reports. They can be of high quality and reflect up-to-date research on understudied topics (Mahood, Van Eerd, and Irvin, 2014), such as women of color in tech. The team’s quality appraisal filtering criteria ensured that all studies met high standards for empirical research.
with support from Nuria Jaumot-Pascual and the Literature Analysis and Synthesis of Women of Color in Technology and Computing project team. Other sources include a 2018 data brief, “Women and Girls in Computing” (McAlear et al., 2018), released by the Kapor Center and the Arizona State University Center for Gender Equity in Science and Technology; works arising from the Women of Color in Computing Research Collaborative; and articles shared by members of the National Academies Committee on Addressing the Underrepresentation of Women of Color in Tech. Findings are not exhaustive; they are meant, rather, to give a sense of the general findings about women of color in tech and to inspire a research agenda based on information that is scarce or missing.
The majority of findings reported in this chapter are based on projects that use qualitative research methods with relatively small sample sizes compared to typical projects that use quantitative research methods. The purpose of qualitative research is to gain an in-depth understanding of a phenomenon—often centered around answering why and how the phenomenon is experienced and the meanings it holds for people—which can be done with small numbers of participants (Creswell, 2013; Glaser and Strauss, 1967). Research based on qualitative methods, such as interview work, aims to understand phenomena by creating categories from the data and then analyzing relationships between categories, while paying attention to the lived experiences of the research participants (Charmaz, 1990, 2006). Qualitative research is a valuable tool for learning about the experiences of women of color in tech, because the understanding of these fields, like many science, technology, engineering, and mathematics (STEM) fields, is hampered by the low numbers of women of color, especially when considering specific institutions, geographic regions, subfields, or races/ethnicities. Qualitative research methods provide an opportunity to examine and understand how the experiences of different groups of women of color vary.
Alice Pawley of Purdue University discussed the value of “learning from small numbers” in STEM (2013, p. 2; also 2019, 2020; Slaton and Pawley, 2018) in a keynote address at one of the project’s workshops. She described how vast resources have been poured into large-scale, quantitative STEM studies and interventions, which were largely ineffective for three reasons: studies often used statistical methods of generalization to explain the experiences of underrepresented groups, even when the presence of members of those groups were too low to be statistically significant; interventions emerging from quantitative studies were often attempts to fix the individual instead of the institution; and most studies were based at one type of institution, predominantly white institutions, and did not take into consideration underrepresented students’ experiences in other contexts. As an alternative way of handling the small number issue, Pawley urged the use of qualitative methods to understand the ways in which the institutional structure of engineering education and other STEM contexts might be comprehended, illuminated, and changed through a limited set of personal narratives (Pawley, 2013, p. 16).
This chapter takes up that call in both its structure and its findings. At each stage of the computing pipeline—K-12, higher education, and the workplace—institutional, or structural, barriers are prioritized by the committee over social barriers; likewise, structural supports are prioritized over social supports. While the charge of this study and subsequent chapters of the report do not focus on the K-12 stage, the committee believes it is critically important to articulate the supports and barriers that exist for women of color in CS in early educational opportunities and experiences that, later, either support or hinder their further participation in computing in higher education and the workforce. Where literature specific to women of color in CS/tech is scarce, the committee draws on findings in the literature regarding students of color, or women of color, in STEM. The chapter concludes with a brief discussion of non-traditional pathways into tech positions and a list of recommendations arising from the research for practitioners, administrators, and CS/tech education researchers.
Nearly a century of research on education indicates that inequality is pervasive throughout the United States’ K-12 education system, and Black, Latinx, and Native American students and low-income students receive systemically unequal opportunities for a rigorous and effective education. These barriers are both structural and tied to individual and social factors. While much of this literature captures the specific structural barriers facing Black, Latinx, and Indigenous women in education broadly (and/or how they differ from their male counterparts), it is important to note that women of color face very different educational opportunities in K-12 than their white counterparts. On average, the foundational educational experiences for girls of color from underrepresented groups are significantly different from those of their white peers, providing vastly different opportunities for academic success, early exposure to tech-focused activities, and for entering the tech pipeline. Further, in the current context of the COVID-19 pandemic, there is evidence that existing opportunity gaps for students of color are at risk of widening due to the pervasive digital divide (Common Sense, 2020), the discontinuation of computer science courses (Martin et al., 2020), and the learning loss and poor quality of online learning which are projected to be greatest among Black, Latinx, and Indigenous students (McKinsey, 2020). More research is needed to specifically understand these differences in foundational educational opportunity affecting girls of color.
Structural Barriers for Girls of Color in K-12 Education
Despite efforts to desegregate public schools after the Brown v. Board of Education (1954) decision, schools remain stubbornly segregated by race and income—and unequal (Orfield, 2001). Non-white school districts receive sig-
nificantly less funding than white school districts, based on the reliance on local property taxes to fund schools. Estimates indicate that this funding gap between non-white school districts and white school districts is as large as $23 billion, with districts spending an average of $2,200 less per student in non-white districts (Baker, 2014; EdBuild, 2019; Kozol, 1992; Morgan and Amerikaner, 2018; NCES, 2012). School funding inequalities are mirrored in the quality and expertise of teachers. There are about twice as many uncredentialed and inexperienced teachers in school districts that serve the highest proportions of low-income and minority students compared with districts with the lowest proportions (Adamson and Darling-Hammond, 2012; Goldhaber, Lavery, and Theobold, 2015). The digital divide is also a pervasive barrier and is pronounced among Black, Latinx, and Native American households, which are significantly less likely to have access to broadband internet and technology devices needed for in-school and out-of-school learning (Common Sense, 2020; PRC, 2012, 2015, 2019). In light of the COVID-19 pandemic, the shift to online learning, and the ways that different groups of girls may be impacted differently (i.e., because of family, community, and geographic characteristics), this foundational structural barrier has become more pronounced and the need to address it more urgent.
Disparities also exist in access to rigorous STEM courses, which vary dramatically by the demographics of schools. Students of color are significantly less likely to have access to advanced placement (AP) and international baccalaureate courses, or to a full range of STEM courses (e.g., physics, calculus) than their peers (ECS, 2017; OCR, 2018). In computer science specifically, students of color, low-income students, and rural students are significantly less likely to have access to computer science courses in their schools, and more specifically lack access to AP computer science courses, which play a critical role in driving interest and preparation in computing in college and career (Code.org 2020; Google/Gallup, 2020; Martin et al., 2015; Scott et al., 2019).
Social Barriers for Girls of Color in K-12 Education
Beyond policies, resources, and course offerings, education research indicates that Black, Latinx, and Indigenous students in K-12 public schools face social barriers stemming from teachers’ and administrators’ negative biases, belief systems, stereotypes, and expectations. Teachers consistently rate the mathematical proficiency of girls significantly lower than boys (Cimpian et al., 2016) and of girls of color lower than white students—both boys and girls (Copur-Gencturk et al., 2019). Beliefs about the ability of Black, Latinx, and Indigenous students lead counselors and teachers to track students into lower level courses and pathways (Oakes, 1985). Research also indicates that teachers hold lower expectations of college success for Black students than white students (Papageorge et al., 2020). These beliefs can be self-fulfilling and hinder actual student achievement, students’ pursuit of STEM fields (Scott and Martin, 2014), and students’ rate of de-
gree completion (Gershenson and Papageorge, 2018). Stereotypes and biases also impact how Black girls in particular experience school discipline, with Black girls having suspension rates that are six times higher than white girls (OCR, 2014).
Stereotypes about computer science and computer scientists have been well documented in American society, with assumptions that computer scientists are male, tech oriented, and socially awkward (Cheryan et al., 2013), and that computer science requires brilliance (Leslie et al., 2015) and involves solo, non-collaborative, and non-communal work (Diekman et al., 2010; Margolis and Fisher, 2002). Research shows that classroom cultures with stereotypical cues about computer science have a negative impact on female students’ sense of belonging in computer science and their interest in pursuing computing majors and careers (Cheryan et al., 2009; Master et al., 2016). While the research on gendered stereotypes in computing shows that they are present for female students broadly, additional research is needed to fully explore stereotypes and perceptions of computing fields as they relate to girls of color in particular.
As a result of cumulative structural and social barriers, data indicate that girls of color are significantly less likely to take the computer science courses in high school that are significant predictors of entering college and career pathways in this field (Mattern et al., 2011). Girls of color make up approximately 21 percent of the K-12 student population but just 7 percent of all students taking advanced placement computer science courses at the high school level (College Board, 2019; McAlear et al., 2018). Just 77 Native American girls, 3,477 Black girls, and 8,183 Latinx girls took an Advanced Placement Computer Science course in 2019. These numbers have remained static over the period from 2016 through 2021.
Research demonstrates that students who take the AP Computer Science Principles exam are up to three times more likely to major in computer science and that taking this exam is also a significant predictor of taking the more advanced AP Computer Science A course—a correlation that is particularly strong for Black, Latinx students and girls (Wyatt et al., 2020). Further, students who take the AP Computer Science A exam are seven to eight times more likely to major in computer science in college than their peers who did not take the AP Computer Science A exam (Mattern et al., 2011), indicating that exposure to rigorous computing content in high school is a strong predictor of entering into computing.
Out-of-school exposure to computing activities is also demonstrated to have a positive impact on the interest, aspirations, and knowledge of girls of color. Scott and White (2013) found that culturally responsive after-school programming stimulated the interests and motivations of girls of color to persist in computing—specifically, to learn to master technology and foster an innovative
mindset and to disprove negative racial and gender stereotypes about ability in the field of computer science (Scott and White, 2013). Scott and colleagues (2017) found that among girls of color participating in a summer STEM program, levels of computer science interest were low at the outset but increased significantly after multiple exposures to computer science course interventions, although gender differences remained (Scott et al., 2017). Madrigal and colleagues found that an after-school and summer program for Black girls, which included wrap-around mentorship and culturally relevant curricula, yielded promising results for Black girls’ interest and confidence in computer science (Madrigal et al., 2020).
A growing body of literature building from the culturally relevant and responsive theoretical frameworks of Gay (2010) and Ladson-Billings (1995) posits that culturally relevant computer science education, curriculum, and pedagogy can improve the classroom experiences, identities, and outcomes of students of color (Scott et al., 2014). Additionally, Ashcraft and colleagues (2017) demonstrated that promising practices for engaging girls of color in computer science were to intentionally develop girls’ identities as technosocial change agents and help them understand how technology can be used to advance social justice. There is also some evidence that exposure to counter-stereotypical role models can increase self-concept, attitudes, and career aspirations for women and girls in computer science, although this research is not specific to girls of color (Olsson and Martiny, 2018; Stout et al., 2010). Additional research in both areas will contribute significantly to our understanding of effective interventions for girls of color in K-12 computer science education.
Most research on women of color in technology and computing fields focuses on higher education. Women of color make up 39 percent of the female-identified population in the United States, yet account for less than 10 percent of bachelor’s degrees earned in computing and less than 5 percent of doctorates in computing (McAlear et al., 2018). This section first discusses structural and social barriers, followed by structural and social supports. It must be noted that within higher education, most studies are at the undergraduate level; thus that emphasis is reflected here. While research on women of color in technology and computing fields is needed at all levels, it is especially needed at the graduate level.
Structural Barriers for Women of Color in Higher Education
Structural and institutional barriers identified in the literature for women of color at the higher education level include campus and departmental climates
experienced as unwelcoming, a scarcity of on-campus and departmental supports aimed specifically at advancing women of color, offensive or discouraging faculty and staff conduct, and the costs related to enrollment in higher education. These are described in detail the sections that follow.
Chilly Campus and Departmental Climates
Several research studies described how chilly, and even hostile, campus and departmental climates contribute to negative experiences of women of color in technology and computing fields in higher education. Institutions and departments that are experienced as unwelcoming often lead students who are women of color to feel excluded and alienated (Ashford, 2016; Charleston et al., 2014b; Thomas, 2016). For example, all 15 African American women in Charleston and colleagues’ study agreed that the computer science culture in their respective departments during graduate school at predominantly white institutions were not very welcoming to women, and even less so to African American women. Other studies showed that women of color felt isolated within their departments due to their being the only one, or one of a few, of their gender and/or race or ethnicity (Agbenyega, 2018; Lyon, 2013; Rodriguez, 2015). These women also experienced a sense of lack of commonality with white male peers and cultural disidentification with other students in computer science and other tech departments (Herling, 2011; Tari and Annabi, 2018; Thomas, 2016).
Dearth of On-Campus and Departmental Supports
Another factor contributing to negative experiences of women of color in higher education is the dearth of on-campus formal supports that are prepared to understand and address their unique experiences. Mónica, a first-generation Latina undergraduate in Lyon’s (2013) study, lacked information about selecting a major once she arrived at college. Mónica reached out to advising groups at her university, but described her experience as, “I feel like I haven’t had a clear advisor. I go to people and I tell them how I feel. . . . But they don’t really know what to say back to me” (Lyon, 2013, p. 81). Despite supports at Mónica’s university such as assistance in selecting courses and majors as well as an office designed to assist first-generation college students who are the children of migrant workers, she still felt a lack of support given that these services did not address her individual needs, such as helping her choose a major based on her interests. Lyon (2013) also described Kelsey, a first-generation Filipino student interested in informatics, who had access to on-campus support for persistence in college but no guidance on selecting or navigating through a major.
Institutionally sanctioned organizations for students, such as student support programs, are intended to provide students with academic and social support and professional development; for students from underrepresented groups, they
may also serve as counterspaces, or safe spaces for belonging (Ong et al., 2018). Some organizations focus on aspects of STEM and gender, such as chapters of the Society of Women Engineers, or STEM and race/ethnicity, such as chapters of the American Indian Science and Engineering Society; however, few are prepared to fully meet the needs of women of color (Herling, 2011). For example, Anu, a Bengali American undergraduate in Ratnabalasuriar’s (2012) study, attempted to join the student organization Supporting Women in CS [Computer Science], but she felt out of place and unwelcomed. She stated that “there were very few women in the group. Of the women that were there, most of them were grad students. Almost all of the officers in the organization were men. The students in computer science just aren’t very friendly” (p. 127).
Offensive or Discouraging Faculty Conduct
Research showed that faculty sometimes contributed to the negative departmental atmosphere experienced by students who are women of color. Multiple studies found that women of color students in technology and computing fields reported receiving verbal insults or harassment or being treated as invisible by their professors (Ashford, 2016; Charleston et al., 2014a; Hodari et al., 2014). Another way faculty contributed to a negative atmosphere was to engage in institutional microaggressions, such as being aware of inequities against women of color but not taking action to rectify them (Charleston et al., 2014a, 2014b). Faculty’s racial and gender biases and attendant lack of support contributed to the perception held by women of color that their departments were hostile (Ashford, 2016; Charleston et al., 2014a, 2014b). For example, women of color reported that professors refused to recommend them for industry positions, regarded teaching women as a chore in comparison to doing their scholarly research, and stated that African American women, in particular, lacked talent and were not intelligent enough to be in computer science (Charleston et al., 2014a; Herling, 2011; Ratnabalasuriar, 2012; Thomas, 2016).
Paying for higher education is a key concern for many students and their families. Lack of access to adequate financial resources can serve as a hindrance, especially for underrepresented students of color in STEM, and availability of financial aid for students in need varies across schools (Fenske et al., 2000; Palmer et al., 2011). Students of color from underrepresented groups are more likely to come from families with fewer financial resources, which increases their reliance on paid work while in school, decreases the time they can dedicate to their studies or to participating in STEM organizations and internships, and contributes to stress (AIP, 2020; Estrada et al., 2016; Perna, 2009). Perna (2009), who studied Black women pursuing STEM degrees at Spelman, a historically Black women’s
college, noted that non-traditional students such as those who commuted, those who were financially independent from their parents, and transfer students were especially vulnerable to financial challenges. In Agbenyega’s study (2018), one Latina relayed her financial hardship by providing examples of her difficulties purchasing books for her courses and food insecurity. She stated, “If it wasn’t for the pretzel guy on campus, I don’t know how I would’ve lived. That’s how I got lunch every day, especially when I didn’t have any money” (pp. 161-162). In Foster’s (2016) study, two Native women described how they had to pay close attention to the courses they enrolled in at their two-year college to ensure the credits’ transferability; they needed to avoid spending more time and money than necessary in obtaining their degrees.
Sufficient financial aid has been highly correlated with persistence of members of underrepresented groups on STEM trajectories (Estrada et al., 2016; Fenske, Porter, and DuBrock, 2000; St. John et al., 2005). Surprisingly, research on financial aid specifically regarding women of color students in technology and computing fields is scarce. Two notable exceptions, studies by Foster (2016) and Lyons (2013), described how communities came together to provide financial support (among other forms of support) to signal their encouragement of women of color entering computing paths. The dearth of published research on the experiences with financial aid of women of color in tech and the role of institutions and communities in addressing women of color’s financial need constitute gaps in the literature that need to be addressed.
Social Barriers for Women of Color in Higher Education
Research on women of color in technology and computing fields in higher education reveals a number of social barriers, including challenging relationships with majority peers, challenges related to navigating negative stereotypes, and limitations of family, such as family members’ lack of knowledge about the college application process. These factors are discussed below.
Competitive Peer Relationships in the Classroom
In computer science programs an unwelcoming or hostile departmental climate often pervades the classroom environment. Research shows that instead of taking a creative, collaborative approach with learning, peers of women of color students often compete with them, comparing grades rather than discussing course content (Tari and Annabi, 2018), questioning the women’s merits because of their ethnicity and gender (Hodari et al., 2016), or questioning their intelligence and abilities (Rodriguez, 2015; Thomas, 2016). Some research reported incidents of peers not wanting to work with or even talk to women of color (Ratnabalasuriar, 2012).
In some cases, because of their interactions with peers, women of color suffered from imposter syndrome, the sense of not legitimately belonging in their field (Ashford, 2016). For instance, a participant in Tari and Annabi’s study (2018), whose peers were predominantly white and male, stated that she felt perceived by her peers as a token. Sensing her academic legitimacy was threatened, she stated, “I don’t speak out as much as I would have when I went to high school” (p. 4). Tari and Annabi concluded that this participant’s legitimacy threat was a major factor in her feeling excluded.
Studies further reveal how certain gendered and racial stereotypes negatively affected women of color students in technology and computing fields, and how the women responded in order to belong. For example, women who presented themselves in a feminine way, such as wearing high-heeled shoes or dresses, were frequently viewed and treated by peers as less intelligent (Thomas, 2016; Varma et al., 2006). All Latinx women participants in Rodriguez’s study (2015) felt there was no middle ground in how their male peers perceived them: The women were seen as either brilliant or stupid, and their competence was called into question even when their work was of the same or higher quality as that of the men. Participants in Lyon’s study (2013) combatted the stereotype that the only people who were truly interested in technology and computing fields were male, white and Asian introverted gamers. In response to this stereotype, one Latina student in the study repositioned herself to spend time with classmates who were men instead of the women. Other studies showed that, in the classroom environment, women of color often combatted the perpetuation of the stereotypes of the “angry Black woman” and the “affirmative action” candidate, which contributed to their feelings of not belonging (Ashford, 2016; Charleston et al., 2014a). In response to feelings of exclusion and isolation resulting from falling victim to stereotypes, some women of color adjusted their behavior, language, or attire to be more masculine in order to better fit into their department’s environment (Herling, 2011; Thomas, 2016) or considered leaving their program (Rodriguez, 2015).
Lack of Family Support or Assistance
While family can have a very positive effect on women of color who engage in and persist in technology and computing fields (see “Family Supports” below), the research literature suggests that not all family influences are positive. Two studies found that women of color experienced active resistance from family members, such as fathers and stepfathers, who were opposed to the idea of having a female going into a field that they considered inappropriate for females (Agbenyega, 2018; Lyon, 2013). This was the case for a Latina undergraduate in computer engineering in Agbenyega’s study, whose father discouraged her from
pursuing her major because he saw it as a “men’s field.” In other cases, family was not an active barrier, but it sometimes lacked the cultural capital of understanding how the U.S. college system works. Lyon (2013) described two women of color who were first-generation college students. They were interested in majoring in informatics but had received little or no information while growing up about the college selection process or resources for finding out such information; the advice these women received from their families was to attend an Ivy League school or community college, with no mention of other viable options, such as state institutions.
Structural Supports for Women of Color in Higher Education
The literature suggests that several structural supports exist to advance women of color in higher education. These include strong, supportive faculty and advisors; STEM and non-STEM campus student groups; and the positive atmosphere and constructive teaching and mentoring provided to students attending historically Black colleges and universities (HBCUs). These factors are described in detail below.
Supportive Faculty and Advisors
While several studies found faculty to be barriers in the education of women of color in technology and computing fields (see “Faculty Conduct” section, above), a few studies identified ways in which faculty members and advisors were very supportive. Ashford (2016) reported women of color participants who learned that their abilities and potential were recognized when they were asked to work in faculty members’ labs; these women thus gained valuable advisors. Faculty at HBCUs are known for creating positive learning atmospheres for their students, providing them with professional development and supporting their advancement in STEM, and tech fields such as computer science are no exception (Kvasny et al., 2009; Murray-Thomas, 2018; Wilson, 2016). Finally, a participant in Ratnabalasuriar’s study (2012) recalled her computer science department recruiting two women instructors, with mixed results. While these instructors demonstrated a concern for retaining students in the major, the presence of the women instructors did not outweigh the negative climate perceived by the participants.
STEM and Non-STEM Campus Student Groups
Campus student groups, even ones that are not necessarily STEM related, can serve as counterspaces—or safe havens—for women of color and students from other underrepresented groups who may not feel an automatic sense of belonging in their own STEM departments. These groups can help students engage in academic or cultural aspects of campus life in positive ways, and they can
Two studies in the literature on technology and computing fields specifically spoke to the importance of campus groups. In the study by Herling (2011), one participant, Gracia, a Hispanic doctoral student, started her own organization at her university for Latinx women in computing. She explained her reasoning: “That was my supportive group, which helped me get through the Ph.D. because we all shared and talked about it” (p. 58). Ninety percent of Herling’s participants were members of the group started by Gracia; they attributed their persistence, at least in part, to the group. In Lyon’s study (2013), a Latina first-generation college student joined a sorority for Latinas because these peers provided familiarity and comfort to her. The student said of her sorority, “I feel like when I’m tired of being over here in the science field with other people, I feel like I can go ‘home’ to someone who understands me. . . . I feel like they’re supportive to me. And so, they’re there for me” (Lyon, 2013, p. 86). More research needs to be done on the benefits of STEM and non-STEM campus student groups for women of color in technology and computing fields overall, and specifically for Asian American, Black and African American, and Native American students.
Historically Black Colleges and Universities
HBCUs make up about 3 percent of all of the colleges and universities in the United States, yet they graduate 25 percent of Black and African American students who receive bachelor’s degrees in science and engineering (NSF, 2019; UNCF, n.d.). Similarly, HBCUs graduate a disproportionately high number of Black and African American students who advance to graduate programs in STEM. In 2011, 24 percent of all Black students finishing a doctorate in science and engineering had received their bachelor’s degree from an HBCU (Fiegener and Proudfoot, 2013; UNCF, n.d.).
A few studies focused on the experiences of women of color provide insights into reasons for HBCUs’ success. In one study, women of color majoring in technology fields at an HBCU reported that their institutions provided an encouraging environment; examples included the teaching of life skills, providing on-campus job fairs, and interacting with faculty who exhibited interest in them (Murray-Thomas, 2018). For example, one participant, Mary, said that a faculty member’s encouragement was responsible for her graduating with a combined bachelor’s and master’s degree in computer science in five years. Mary recalled how the faculty member motivated, supported, and made the students feel at home: “I will not trade having gone to another HBCU for anything. I just feel every time I go back for homecoming; it’s like a family” (Murray-Thomas, 2018, p. 66). HBCUs have also provided students with a sense of empowerment and security (Kvasny et al., 2009; Murray-Thomas, 2018; Wilson, 2016). Megan, an application analyst
in Kvasny and others’ study (2009), stated, “I said [to myself], ‘Well, I realize I don’t know a lot about the African American culture except for my growing up. I want to know more about the African American culture; I want to be in a little bit more relaxed environment at least for four more years until I have to get out into the real world and deal with the discrimination’” (p.15). And, the reputation of selective HBCUs can aid some women of color in securing jobs. A participant in Middleton’s study (2015) perceived that graduation from a top-ranking HBCU aided in her in securing employment within the information technology (IT) company where she worked. More research is needed on the experiences of women of color in technology and computing fields at HBCUs and at other minority-serving institutions,5 at both the undergraduate and graduate levels.
Social Supports for Women of Color in Higher Education
Research literature on women of color in technology and computing fields in higher education suggests that social supports for women of color include their families, non-STEM peers, other aspects of community, and themselves.
Early exposure to technology and computing through family members had a mostly positive effect for women of color (Agbenyega, 2018; Ashford, 2016; Lyon, 2013; Middleton, 2015; Murray-Thomas, 2018; Thomas, 2016; Thomas et al., 2018). In some cases, family members worked in technology and computing-related careers. For example, one African American woman in Middleton’s study (2015) shared that her interest and career in the IT field was sparked by witnessing, as a child, her grandfather work in his television repair shop and seeing what was inside the equipment. Several African American participants in Thomas’s study (2016) described their fathers as being a catalyst for their interest in computers and mathematics; one talked about how she “learned to create playlists and clean viruses off of her home computer with her father as her guide” (p. 66). Other studies described how families influenced women of color to pursue computing by emphasizing early on the value of mathematics. For example, one participant in Agbenyega’s study (2018), Rosa, a first-generation college student majoring in computer science and daughter of Dominican immigrants, described that her family was overall “mathematically inclined,” which helped her strive to excel in mathematics throughout her years in school (p. 161).
Positive family influences were not necessarily specific to technology and computing fields or even STEM. In some cases, the fact that families emphasized the general value of education and of maintaining high academic expectations
5 In this report minority-serving institution refers to historically Black colleges and universities, Hispanic-serving institutions, tribal colleges and universities, and Asian American and Pacific Islander–serving institutions, collectively.
influenced women of color to pursue and persist in technology and computing (Ashford, 2016; Lyon, 2013; Thomas, 2016). Lexi, a participant in Thomas’s study (2016), explained how her mother did not have the chance to attend college, but made sure that Lexi pursued college, whatever the subject. In other cases, families, and particularly mothers, served as positive role models for pursuing the educational path that a daughter desired (Foster, 2016; Lyon, 2013; Skervin, 2015). In one notable example in Lyon’s study (2013), a participant was inspired to persist in her computer science education by the example of her mother, who, despite protests from her spouse, returned to school to obtain her GED high school equivalency diploma, and then completed a cosmetology certificate.
To persist in their tech fields, women of color students often draw support for their emotional well-being through a community of non-STEM friends. In several studies women of color reported leaning most consistently on other women (Lyon, 2013; Thomas, 2016). Rankin and Thomas (2020) described several Black women participants in their study who leveraged the social capital of friends outside of their computer science program to meet other Black women on campus. As mentioned above, some women of color joined race- or ethnicity-specific sororities in order to find a sense of “home” on their campus (Lyon, 2013). These findings resonate with other research in STEM education (e.g., Ong et al., 2018; Tate and Linn, 2005) that addressed the ways in which women of color kept their STEM peers separate from the other friends with whom they socialized. The above examples also bring into high relief the importance of counterspaces (safe spaces) for women of color on the campus, even if these individuals or groups are outside of STEM.
The community at large—people who are not family members or non-STEM peers—plays a significant role in the support of women of color in tech. Women of color received support from their community through words of encouragement (Agbenyega, 2018) and financial assistance (Foster, 2016; Lyon, 2013). The three Native women featured in Foster’s study (2016) received emotional and financial support from their home communities when they left their reservations to pursue higher education. This support was significant for them because it was emotionally difficult to leave their reservations. One participant, Jaemie, said that support came from elders who told her that she needed to “go get an education, be successful, and come back” (Foster, 2016, p. 120). The women in Foster’s study returned to the community as a means of restoring their balance when they had encountered hardships at school. In Lyon’s study (2013), Mónica, a first-generation Latina student, received encouragement from her entire com-
munity when she learned that she had received a scholarship to a prestigious university. She recounted that she “got support from everyone in the community. Even the Spanish stations were saying my name” (p. 85). This type of support and community recognition was important because Mónica knew her community’s sentiment was that computer science was “very difficult and they would be very proud because it’s pretty hard to get someone to do something big from our community” (Lyon, 2013, p. 85).
Numerous studies focused on individual or “self” aspects of women of color when reporting on reasons for positive outcomes and supports. The factors include intrinsic qualities and self-efficacy, a sense of creativity and fun and a love for problem solving, science identity development, and the desire to give back.
Intrinsic qualities and self-efficacy.
The research literature suggests intrinsic qualities as a key factor in the persistence and success of women of color in tech. Among the intrinsic qualities most frequently cited were those related to motivation, such as being hard working, driven, ambitious, and loving to learn (Foster, 2016; Lyon, 2013; Middleton, 2015; Murray-Thomas, 2018; Thomas, 2016), and those that defined abilities such as being smart or good at math (Agbenyega, 2018; Ashford, 2016; Herling, 2011; Lyon, 2013; Ratnabalasuriar, 2012; Rodriguez, 2015; Zarrett et al., 2006). One study by Charleston and colleagues (2014b) noted that all 15 African American women in their study attributed their own resilience, inner strength, and ability to resist negativity as factors for their endurance in their graduate programs in computing.
Early literature on women of color persisting in STEM focused heavily on aspects of self-efficacy (see Ong et al. (2011) for an overview). In more recent literature on women of color in tech, self-efficacy is identified as a factor in a few studies on women of color, but overall, it is not as heavily emphasized as it once was. For instance, Johnson and colleagues (2008) found that African American women had similar levels of self-efficacy in IT compared to those of African American and white men, contrary to what the researchers had initially hypothesized. Similarly, studies by Zarrett and colleagues (Zarrett and Malanchuck, 2005; Zarrett et al., 2006) and Trauth and colleagues (2012a, 2012b, 2016) found that Black and Hispanic women possessed high confidence and aspirations with regard to computer-related tasks and careers compared to other gender and racial/ethnic groups.
Creativity, fun, and problem solving.
Creativity, fun, and problem solving also emerged as interrelated individual factors that influenced the decision of women of color to pursue and persist in technology and computing fields. Researchers found that computer science and coding attracted them because they enjoyed the
challenge and the problem-solving opportunities (Agbenyega, 2018; Herling, 2011), the puzzle-like experience (O’Connell, 2018; Skervin, 2015), the logical thinking required (Smith (2016), and the creativity and innovation that is central to the field (Herling, 2011; Smith, 2016). Many of the women of color spoke of how their values of creativity, fun, and problem solving were rooted in their own childhood experiences, such as playing with what were traditionally considered boys’ toys like robots and LEGOs (Herling, 2011), tinkering with electronics and computers (Agbenyega, 2018; Herling, 2011; Middleton, 2015; O’Connell, 2018; Ratnabalasuriar, 2012; Thomas et al., 2018), and playing video games (O’Connell, 2018; Ratnabalasuriar, 2012).
Science identity development.
Carlone and Johnson’s theory of science identity development (2007) may be useful in helping to understand why some women of color persist in technology and computing fields and some do not. In their study of undergraduates who are women of color, they defined three main science identity categories: research scientist, altruistic scientist, and disrupted scientist. Those with research scientist identities recognized themselves as scientists, were focused on the prototypical aspects of science, and were recognized by others as scientists. In contrast, women of color with disrupted scientist identities reported disruptions in their pursuit of a science identity because they were recognized not as scientists, but as representatives of stigmatized groups. Finally, those with altruistic scientist identities recognized themselves as scientists, but they created their own definition of science through the lens of altruistic (philanthropic, self-sacrificing) values.
The research literature on women of color in tech provides a few examples wherein study participants recognized themselves as scientists while they were students (Ashford, 2016; Rodriguez, 2015). Jeanne, a first-generation Haitian American and a postdoctoral researcher at a predominantly white institution, stated that being strong in STEM had always been part of her identity (Ashford, 2016). She shared a story about her father wondering aloud about how she came up with “the most challenging, random [science] questions that would stump the adults” (p. 104). Thus, her science identity was grounded in her intelligence and her competence in STEM. Similarly, Ashley, a Latina undergraduate, used technology-related humor and engaged in computer science–related extra-curricular activities to perform her STEM identity (Rodriguez, 2015). Unfortunately, Ashley simultaneously experienced a disrupted scientist identity, due to the fact that her peers did not recognize her as competent in computer science. In the same study, a participant named Maria described her career identity as aligned with the health care field and her desire to serve her Latinx community, which she identified as a significant part of her overall identity. According to Carlone and Johnson’s classification, Maria had an altruistic scientist identity, and this served as a source of motivation for persistence (Carlone and Johnson, 2007).
Desire to give back.
According to the research literature, another strong motivation for women of color to pursue and persist in technology and computing fields in higher education is the desire to give back by helping others. This desire to give back connects to Carlone and Johnson’s concept of the altruist scientist, whose scientific identity is tied to altruistic values and sees science as a way to improve people’s lives. The literature on women of color in tech shows that many women of color see altruistic values as an intrinsic part of their identity as scientists and seek to give back by supporting their communities, mentoring or serving as role models, and supporting those who are like them in some way, such as sharing their same gender and/or race/ethnicity or being interested in similar fields (Agbenyega, 2018; Foster, 2016; Herling, 2011; Hodari et al., 2014, 2015, 2016; Lyon, 2013; Rodriguez, 2015; Skervin, 2015; Thomas, 2016). For example, Abbie, an African American computer science major, emphasized the need to be successful in school in order to be a role model for her younger siblings (Thomas, 2016). Francesca, an Asian American undergraduate student in computer science, used her coding skills to create computer games to aid the learning of middle school algebra students, many of whom were young students of color (Hodari et al., 2015). The research showed that even as women of color engaged in helping others, their giving-back activities contributed equally to their own persistence along their tech trajectory.
Studies on women of color in tech at the workplace level are rare and relatively recent; most have been published in the last decade. Similar to the discussion in the section on “Higher Education,” findings in this section are presented as structural and social barriers, then structural and social supports.
Structural Barriers for Women of Color in the Workplace
Structural barriers at the workplace level identified in the literature include the lack of diversity and the resulting isolation experienced by women of color, the hypermasculine “bro” culture of tech, and the lack of recognition of the competence and achievements of women of color in these fields.
Lack of Diversity and Resulting Isolation
As described Chapter 1, the technology and computing workforce in the United States is overwhelmingly composed of white men, and, to a lesser degree, Asian or Asian American men (Skervin, 2015). Literature demonstrates that the lack of gender and racial/ethnic diversity in workplaces increases the sense of isolation for women of color in tech and negatively affects their sense of belonging. In O’Connell’s study (2018), three women of color “expressed feelings
that this intersection of identities enhanced their sense of being the ‘other,’ and compounded the challenges they face” (p. 76). Women of color felt isolation due to the lack of diversity at their job level. For example, participants in Alegria’s (2016) study, who saw few other colleagues who looked like them, stated they felt that women of color were nearly invisible; moreover, those who were there received greater scrutiny in their work than did employees who were white. Participants in Smith’s study (2016) reported that they struggled to maintain their identity, or sense of selves, as African American women in their tech workspaces; they described “adjusting their behavior at times to assimilate more into the group, but want[ing] to guard against going too far” (p. 142). Most women of color in Skervin’s study (2015), with the exception of Asian women, said they felt tokenized. In other words, they felt “simultaneously a visible representation of their ethnicity, and invisible to their boss for opportunities and promotion” (p. 173).
The isolation of not seeing oneself well represented among peers in the workplace is compounded by lack of diversity in the organization’s leadership. In O’Connell’s study (2018), Caroline, an East Asian programmer, reflected how persistence in tech was challenging for those like her who embody intersectional, underrepresented identities as women and people of color: “[the isolation is] even more so [as] the level of representation of people like me disappears at higher levels. It’s just harder to see yourself there” (p. 72).
“Bro” Culture of Tech
A 2017 study on workers who leave tech found that individuals working in the tech industry experienced and observed more unfairness in the workplace than those employed in non-tech industries, suggesting that tech companies may have significantly more challenges in both culture and employee treatment, and women were much more likely to experience mistreatment of all forms (Scott et al., 2017). The hypermasculine, “bro” culture of technology and computing fields likely contributes to these observations and outcomes. The “bro” culture is well documented, with characteristic behaviors including gender discrimination, sexual harassment, extreme partying, cut-throat competition, bullying, and rule-breaking (Berdahl et al., 2018; Chang, 2019; Payton and Berki, 2019; Sahami, 2018). One widely known documented example of “bro” culture in tech workplace culture is described in a blog post by Susan Fowler, an engineer at Uber, who reported repeated sexual harassment by her manager. Fowler’s complaints to the human resources department were not acted upon since the manager was regarded as a top performer at the company (Chang, 2019; Fowler, 2017). Fowler’s account, which went viral, put into high relief the institutionalized behaviors that enable “bro” culture to continue. Even with public scrutiny and fall-out (the Uber chief executive officer resigned), in many tech companies, such “bro” behaviors not only are still tolerated, but are normalized and encouraged (Berdahl et al., 2018).
Unsurprisingly, this culture is often blamed for the low representation of women, and especially women of color, in technology and computing fields (Chang, 2019; Smith, 2016; Williams, 2020). In Scott and colleagues’ study mentioned above, women of color in particular were much more likely than their peers to be negatively stereotyped, passed over for promotions, and sexually harassed within tech workplaces than their peers (Scott et al., 2017). Skervin’s study (2015) showed that women of color participants reported feeling excluded when men would treat them like “the Lady” by noticeably avoiding inappropriate conversations and language in their interactions with them. At the same time, they disliked the “boys’ club mentality” where men made women uncomfortable with sexualized conversations. Similarly, Agbenyega (2018) described how women of color participants in her study felt excluded in their workplaces due to their male coworkers’ not treating them as “one of the guys” and not inviting them to socialize outside of work. Such exclusion meant they were left out of opportunities to socially bond with colleagues or discuss work, which, in turn, meant it was more difficult for them to succeed.
Lack of Recognition of Competence and Achievements
A few studies have found that women of color were not given adequate public recognition by supervisors and leaders for their competence and achievements in technology and computing. Smith’s study (2016), for example, found that African American women in IT reported that they felt their professional advancement was inhibited by a lack of recognition. While the women received good general work performance reviews, they did not receive public acknowledgment or appreciation for successfully completing specific job projects, as their white male coworkers did; this disparity in public recognition, an example of attribution bias, negatively impacted the women’s visibility and advancement (Smith, 2016). O’Connell (2018) reported that women of color, instead of being recognized and rewarded for excelling at soft skills such as communication, teaching, and mentoring in the technology workplace, were punished. The literature also shows instances in which, upon making a mistake, women of color were not provided the second chance that others received (Kvasny et al., 2009) and that supervisors tolerated a lack of productivity from white men but not from women of color (Alegria, 2016; Kvasny et al., 2009; Skervin, 2015).
Social Barriers for Women of Color in the Workplace
Research literature on women of color in technology and computing at the workplace level demonstrates social barriers including biases and microaggressions in the workspaces. Specifically, several studies reported that women of color had the credibility of their expertise and competence questioned, had to prove
their abilities and worth to peers and supervisors continually, and felt the burden of disproving negative stereotypes of groups to which they belonged.
Biases and Microaggressions
Several research studies describe aspects of hostile work environments for women of color in tech. Sue (2010) defined a hostile work environment against women as a workplace in which “sexual harassment, physical abuse, discriminatory hiring practices” are manifested or where “women [are] subjected to a hostile, predominantly male work environment” (p. 11). Additionally, Sue (2010) argues that as society and employers have become more sensitive to these issues, hostility against women and other marginalized groups has become increasingly expressed in the workplace through microaggressions. Thus, microaggressions—such as messages that people of color are less capable or untrustworthy or that women’s contributions are less worthy than men’s—must be added to a broadened list of criteria for analysis of hostile work environments.
Three broad, related issues contributing to a hostile work environment for many women of color are described in the sections that follow: the questioning of the credibility of women of color and the constant pressure for them to prove themselves, the pressure on them to disprove stereotypes, and the exclusionary “bro” culture of tech environments.
Credibility and prove-it-again.
Questioning the credibility of women of color was particularly pervasive in the literature (McGee, 2017; Middleton, 2015; O’Connell, 2018; Skervin, 2015; Smith, 2016). McGee (2017) identified three women of color tech professionals in her study who had their legitimacy and credibility repeatedly doubted. For example, one Latina participant described how, during her first job out of college, a male coworker pulled her aside and asserted that the only reason she had her job was because of affirmative action. Another participant, an African American woman, likened the recurring invalidation to the movie Ground Hog Day: “There’s . . . all the speculation around how you got to be where you are. And that never stops” (pp. 83-84).
In response to having their credibility persistently questioned, many women of color feel pressure in the workplace to continually prove themselves, that is, pressure to provide “more evidence of competence than men in order to be seen as equally competent” (Williams, 2014, p. 5). Williams refers to this particular form of work gender bias as the “prove-it-again” phenomenon (p. 5). Kvasny and colleagues (2009) reported that women of color needed to do more than white male coworkers to be seen as equally qualified. In O’Connell’s study (2018), six women of color professionals reported receiving recurrent messages that they were “not technical enough.” One African American participant reported how the challenge to prove herself began with the pre-hire interview and continued through her career at her company: “I’ve been told a lot that I’m not technical
enough, which is funny because I write code for a living” (p. 65). A South Asian woman in the same study described the toll that contending with proving-it-again can have on members of underrepresented groups: “People who are minorities in tech feel like they need to prove more of themselves. . . . [T]here’s a whole thing at companies that they don’t want to lower the bar to hire more diverse candidates. You hear that all the time. So, a part of it also messes with your head in the whole process.”
Disproving negative stereotypes.
Women of color, especially African American women, are often negatively stereotyped in the tech workplace. According to Williams (2014), women of color in STEM deal with unique, negative stereotypes—for example, that Latinas have fiery tempers, Asian women are meek and mild, and Black women are angry (pp. 7-8). Additionally, all women, including Asian and Asian American women, contend with stereotypes that they are not as intelligent in the workplace as men. For example, Black and Latinx women have the extra burden of disproving the stereotype of laziness (Williams, 2014, pp. 48-49) and broader race-related stereotypes about intellectual ability (Scott et al., 2017).
The literature demonstrates the ways in which women of color in tech assume the burden of addressing stereotypes that result from the embodiment of intersecting identities. Studies have noted how assertiveness is necessary for respect in the tech industry, and is rewarded for people who are not women of color (McGee, 2017; Skervin, 2015), yet others describe the challenge faced by African American women who are assertive in the tech workplace and must contend with the stereotype of being seen as an “angry Black woman” or combative when they were simply being assertive in the tech workplace (O’Connell, 2018; Ross, 2014). At the same time, the studies also note that such assertiveness is necessary to be respected in the tech industry, and it is, in fact, rewarded for others (McGee, 2017; Skervin, 2015). To illustrate, one African American participant in Ross’s study (2014) described how her colleagues translated her assertiveness as her being an “angry Black woman” who was “trying to prove something or trying to over-exert [her] authority” (p. 113), while the same level of assertiveness from her white female colleague was deemed acceptable by others. Additionally, African American women were burdened with the extra work of ensuring they did not appear angry in their workplace interactions (Ross, 2014).
Structural Supports for Women of Color in the Workplace
The literature discusses four types of structural supports that can help to advance women of color in the workplace: diversity in the workforce and leadership, on-the-job supports of networking and mentoring, opportunities for professional growth, and compensation, described in the sections that follow.
Diversity in the Workforce and Leadership
Research on workplaces suggests that companies that prioritize diversity, equity, and inclusion practices better retain employees from underrepresented groups (Cloutier et al., 2015).6Smith (2016), for example, found that African American women expressed that experiencing diversity at all levels in their workplace helped to retain them at their organization and in the field of information technology. Conversely, in O’Connell’s study (2018), a lack of diversity in the workplace was seen by women of color as a red flag.
Furthermore, studies have found perceptions by women of color that the leadership of a company influenced their own career path. The race or ethnicity of the company leaders often impacted the perception of women of color in their own treatment. For example, McGee (2017) reported on an Asian American woman who attributed the diversity and culture of the workplace, and her own positive opinion of the company, to the fact that the chief executive officer was Asian. Similarly, Natalie, an African American woman in McGee’s study (2017), felt that because her company’s chief executive officer was an African American man, she was judged solely on her work performance and not her race. Notably, while Natalie expressed the belief that race was not a factor at her workplace, she observed that women of color experienced a slower rate of promotion (McGee, 2017).
Leaders who are people of color have the potential to adapt non-traditional leadership styles that benefit women of color, among others. For example, an African American woman who was in a leadership position approached giving recognition differently than her peers:
I make sure that the right parties get credit. And that you will be amply regarded for that idea and for the contributions you make to the team. For example, if you bring in a sale, I make sure that you are amply rewarded for that sale specifically, because that typically causes people to work a little bit harder. So, I am very goal-oriented because of that, and I believe in setting goals for employees and recognizing them when they hit those goals. I think that is a wonderful, wonderful way to motivate folks, because that is what motivates me. I try to give people as much recognition that I possibly can (Ross, 2014, pp. 121-123).
6 We use the New England Resource Center for Higher Education’s definitions of diversity, equity, and inclusion. Diversity refers to individual and group/social differences that can be engaged in the service of learning and in the workplace. Equity refers to creating opportunities for equal access and success for historically underrepresented populations through representational equity, resource equity, and equity-mindedness. Inclusion refers to the active, intentional, and ongoing engagement with diversity, which has the potential to increase individuals’ awareness, context knowledge, cognitive sophistication, and empathic understanding of the ways individuals interact within systems and institutions (NERCHE, 2016).
This leader was aware of the importance of public recognition for all employees (Carlone and Johnson, 2007) and made sure that she provided this recognition when deserved.
On-the-Job Supports: Networking and Mentoring
Studies of women of color working within the technology field reveal the importance of networking and mentors to both emotionally survive the workplace (Agbenyega, 2018; Foster, 2016; Skervin, 2015) and thrive in their career (Hodari et al., 2014; Middleton, 2015; Smith, 2016). The literature shows that women of color seek to make informed choices in education and career advancement through networking with people in and outside of STEM (Foster, 2016; Middleton, 2015). Participants in Middleton’s study (2015) noted that networking was very important, having had a direct role in their obtaining jobs. The need for networking and support was found to be crucial among African American women in Smith’s study (2016); they actively sought out informal networks and mentoring relationships within the workplace, often crossing both gender and racial boundaries.
Women of color also actively seek out mentors for leadership training, career advancement, assistance with technical career goals, and interpersonal skills (Hodari et al., 2014; Smith, 2016). For example, in Hodari and colleagues’ study (2014), a Latina professional in industry received leadership skills training from an internal mentoring relationship that she proactively formed. Additionally, being mentored earlier in one’s career proved to be an effective strategy for navigating the workplace and putting in place a plan for future advancement (Smith, 2016).
Opportunities for Professional Growth
In addition to role models and mentors (Foster, 2016; Hodari et al., 2016; Skervin, 2015; Smith, 2016), career growth and advancement are dependent on several elements of the work environments of women of color, including opportunities for professional development and advanced technical training (Hodari et al., 2016; Skervin, 2015; Smith, 2016). For example, Smith (2016) found that African American women professionals in IT reported that having role models and mentors at a company during the first five years of their career was beneficial to their career growth. After this point, they felt they had outgrown the need for role models or mentors, but they wanted to mentor and serve as role models for more junior African American women in order to increase the numbers of this population in the IT subfields of health care, financial services, education, business consulting, and technology organizations. Smith (2016) found that professional development and advanced technical training helped to retain women of color in the workplace. Because the tech industry is in perpetual transformation,
professional development offerings helped to expand their skill set, which then helped lead to career advancement.
The median salary in computer and information technology positions in 2019 was $88,240, compared with the median annual wage for all jobs of $39,810 (BLS, 2020). Moreover, jobs in technology and computing are projected to increase 11 percent between 2019 and 2029, which is faster than the average for all occupations, and even faster than most other STEM jobs (BLS, 2020). Unsurprisingly, research studies found that job security and high-earning positions were identified as factors for attracting and retaining women of color in tech, even those graduating with bachelor’s degrees (Herling, 2011; Middleton, 2015).
A participant in Thomas’s (2016) study, Tamara, learned early in life from her mother how lucrative tech careers could be: “‘Oh my God, technology, technology’. Telling me all the jobs go to the technology people in the company and how much money they make . . . and so as a kid I was always into technology because my mom wanted me to learn programs on the computer for that reason” (p. 68). One participant in Middleton’s study (2015) witnessed how her peers in high-paying IT jobs had been pulled away from school prior to completing their degrees to pursue these jobs. She remarked, “You know, back then, kids were making a lot money. They weren’t even letting people with IT degrees finish college back then, they were like, look . . . we’ll start you off with a good salary, just come to work for us” (p. 94).
However, the research also identified a negative side to compensation: while technology and computing provided a “good salary,” the salary could also “trap” women of color. Some studies suggested that even as structural barriers prevented women of color from advancing in their companies, they stayed in the tech jobs because they felt they would not have the same quality of life if they left (Middleton, 2015). For example, in Opara et al.’s (2005) study, an African American IT worker at a petrochemical company said, “I can’t go any higher in the organization. There is a glass ceiling at this place, but I can’t make this same money anywhere else, so I will probably stay where I am” (p. 45). Additionally, a participant of Smith’s (2016) study stated
I feel like computer science is a trap. It is a good field in that it’s well paid. But you can burn out after a while so you feel trapped not knowing what else you can do. But what keeps you is that it’s the comfort of being well paid for something you are comfortable doing (p. 123).
Opara et al. (2005) found that women of color in IT fields seemed to be satisfied with salary, whereas men were more likely to look at a combination of factors for their job satisfaction.
Social Supports, Personal Drive, and Women of Color in the Workplace
The literature on women of color in technology and computing in the workplace describes the role of social supports that improve outcomes for women of color such as professional organizations, faith and church, and non-STEM friends, as well as the influence of personal drive to attain a better life. These factors are discussed in the sections that follow.
Three studies identified the importance of professional organizations, particularly those that focus on people of color or women in STEM professions, as strong social supports for women of color, particularly Latinx and Black women. Herling (2011) found that the two national organizations, Women in Computer Science and Latinas in Computing, provided Latinx women and Hispanic women professionals with a sense of support and reinforced their computer scientist identities. Similarly, Agbenyega (2018) found that a professional organization serving Hispanic engineers and the National Society of Black Engineers (NSBE) provided Latinx women and Black female professionals in her study with a sense of belonging in STEM, strategies for navigating the STEM workplace, and opportunities to give back to communities with whom they had something in common. Middleton (2015) also found NSBE played a key role in the persistence of African American women computing professionals in the field. One participant stated, “I think [seeing others who look like me] helped me more than I realized while I was going through it. Because it helped me find people like me, men and women, Black men and women, who were going into this field, where it is predominately dominated by white males” (p. 99).
Faith, Church, and Community
Several studies reported on women of color relying on their spirituality or religious faith to guide their workplace behaviors and as means of coping with barriers and even thriving at the tech workplace (Foster, 2016; Ross, 2014; Skervin, 2015). Some women of color attributed their success to their faith (Ross, 2014; Skervin, 2015). Churches were described as encouraging environments (Murray-Thomas, 2018) and as an empowering source, particularly for African American women (Kvasny et al., 2009). For example, a participant in Ross’s (2014) study explained that her faith enabled her “to conquer complicated goals and strive toward better outcomes” (pp. 123-124). African American women in Ross’s (2014) study who were in leadership positions at their workplaces used their faith as the guide for treating others kindly and for framing problems in a positive way. One participant reflected how
In the African American community the church and our religion has been such a large part of our culture, and it is a part of my coping mechanism. What I use to cope is my belief, my faith in God. . . . But not only that, but my faith that tells me that nothing happens by coincidence, and even in the role [as a leader] I am there to make an impartation to the people I interact with. That I am there to have this as a growth and development experience as well (p. 125).
One study by Skervin (2015) illustrated the importance of community composed of family and friends outside of the STEM workforce. These family members and non-STEM friends provided women of color with social supports, a sense of belonging, and spaces to safely discuss their negative experiences in the workplace. Skervin found that the support of a strong community outside of work can help women of color persist and succeed in the workplace. One African American industry professional in the study noted, “[W]hen you have good people around you—outside of the workplace—it really helps you with negativity of the workplace, because you’re not just defined by that job” (p. 135).
Desire for a Better Life
While the motivations of women of color for pursuing a career in technology and computing fields vary greatly, one reason recurring in the literature was the desire to have a better life. The meaning of “better life” had several elements, such as wanting a flexible lifestyle that allows a better work-life balance (Ashford, 2016; Thomas, 2016). The most frequently mentioned influences, however, were the related factors of job availability and financial security that technology and computing could offer (Herling, 2011; Kvasny et al., 2009; Middleton, 2015; Murray-Thomas, 2018; Opara et al., 2005; Skervin, 2015; Smith, 2016; Thomas, 2016). For example, Gloria, a Hispanic woman in Herling’s study (2011), changed her major to computer science because “being able to find a job after graduation was a huge consideration on my part” (p. 69). In Murray-Thomas’s study (2018), Mary, a Black female master’s student in computer science, chose her field with the goal of living, with her child, above the poverty line. She stated that “my motivation came from wanting to escape the home environment I grew up in and to have a better life” (p. 87).
NON-TRADITIONAL PATHWAYS TO TECH
Lastly, the committee reviewed the literature on pathways into technology and computing fields that involve job training outside of academic degree programs. Job training currently includes a variety of training initiatives, including, but not limited to, coding bootcamps, such Coding Dojo, which is primarily based on the West Coast, and Boston-based Resilient Coders; web development bootcamps such as Fullstack Academy in New York; apprenticeship programs
such Apprenti, which is nationwide; and live-and-learn programs, such as G|Code House in Boston, which is currently under development. Organizations such as Per Scholas, which has multiple training sites throughout the United States, and the Bay Area Video Coalition and Street Tech in California also offer short-term (two- to nine-month) training programs. Programs at community-based and non-profit organizations also offer job training and short IT certificate courses (Chapple, 2006; Kvasny and Chong, 2006). Though some of these initiatives have existed for decades, research literature reporting on them has not kept pace, indicating a gap in the empirical research that needs to be addressed.
The sparse existing research reveals that women of color who took nontraditional pathways into technology and computing often began training in order to escape poverty or to improve their lives (Kvasny and Chong, 2006). Chapple (2006) found while training programs were not exclusive to women of color, they attracted this population due to the promise of employment opportunities enabled by IT skill. However, that promise may or may not be borne out in reality. While Chapple found that most job options immediately available to women of color completing short-term training programs were often low-wage, entry-level IT positions (such as software testing), websites of programs such as Resilient Coders and Apprenti boast an average salary of its participants of around $100,000.
In addition to providing training, non-traditional programs also offer other benefits, such as networking opportunities and professional development. For example, the District of Columbia Web Women, a non-profit organization, caters to women and fosters a space where like-minded women support each other and learn about the rapid changes within technology fields (Sniderman, 2014). Regarding the organization’s workshops, Sibyl Edwards, an African American woman study participant, stated, “The workshops help people make themselves more marketable to get hired. And since many of the members are freelance contractors, myself included, we are having more events geared toward contracting, pay, and salary negotiation to empower those groups” (Sniderman, 2014, p. 42).
CONCLUSIONS AND SUMMARY OF NEEDS
The sections that follow provide brief summaries of the literature on girls and women of color in technology and computing fields from the last decade. At each level—K-12, higher education, and the workplace—institutional or structural barriers are prioritized over social barriers; likewise, structural supports are prioritized over social supports. Where literature specific to women of color in tech is sparse, the committee drew on findings in the literature regarding students of color or women of color more generally in STEM. The section concludes with a brief discussion of non-traditional pathways into tech positions and a list of research needs for practitioners, administrators, and technology and computing education researchers.
Summary of K-12 Findings
The research literature shows that structural barriers for girls of color at the K-12 level include de facto segregation in many public school systems, including predominantly non-white schools receiving less funding per pupil and having fewer resources, such as more inexperienced teachers (e.g., EdBuild, 2019) and fewer advanced placement and computer science classes (e.g., Code.org, 2020). Social barriers include negative biases held by teachers about girls of color, which translate into low expectations for STEM achievement and these girls’ placement into lower academic tracks (e.g., Copur-Gencturk et al., 2019; Papageorge et al., 2020). Moreover, technology and computing fields have strong stereotypes associated with them—such as its being highly masculine, competitive, non-collaborative, and non-communal (e.g., Master et al., 2016)—that often discourage girls of color from considering the field as a possible career path.
The literature suggested that effective structural supports at the K-12 level for girls of color include course offerings and out-of-school exposure to technology and computing. Research shows that when students, especially girls, Black, and Latinx students, are able to prepare for and take CS AP exams, they are more likely to persist on a technology and computing track and major in computing in college (Mattern et al., 2011). Moreover, studies have found that when girls of color participate in after-school or summer tech programs, they are more likely to express interest in pursuing tech careers (Madrigal et al., 2020; Scott and White, 2013). Social supports include culturally responsive curricula and pedagogy that incorporate into computing tasks the identities of girls of color as technosocial change agents (Ashcraft et al., 2017). Research also suggests that providing students of color with counter-stereotypes improves their self-concept and aspirations in computer science and tech, though more research specifically on girls of color is needed (Olsson and Martiny, 2018).
Summary of Higher Education Findings
Research literature shows that structural barriers for women of color in higher education include experiencing chilly campus and departmental climates (e.g., Ashford, 2016); a dearth of on-campus and departmental supports, such as helpful advisors or student support programs fully prepared to serve them (e.g., Lyon, 2013; Herling, 2011); and hostile or unsupportive faculty (e.g., Charleston et al., 2014a, 2014b). A few studies (e.g., Agbenyega, 2018) hinted at the importance of financial support for women of color in tech, but this aspect of structural support needs to be better studied. Research shows that social barriers for women of color have included negative peer interactions such as having their intelligence questioned (e.g., Rodriguez, 2015), dealing with negative stereotypes (e.g., Thomas, 2016), and not having strong family support (e.g., Agbenyega, 2018).
According to the literature, structural supports for women of color in higher education include supportive faculty and advisors (e.g., Ashford, 2016) and stu-
dent groups that provided safe places for belonging (e.g., Herling, 2011). A few studies focused specifically on the characteristics and practices of HBCUs that support the success of Black or African American women. HBCUs were shown to provide a supportive environment, a sense of empowerment and security (e.g., Kvasny et al., 2009), and faculty invested in students’ success (e.g., Murray-Thomas, 2018). Social supports include family members who supported women of color’s STEM interests (e.g., Middleton, 2015) or just cheered them on their technology and computing path (Thomas, 2016); non-STEM peers (e.g., Rankin and Thomas, 2020); and other types of community, such as people in their hometowns (Foster, 2016; Lyon, 2013). Finally, numerous studies focused on qualities of the self, including intrinsic STEM talent and self-efficacy (Ratnabalasuriar, 2012; Zarrett et al., 2006); enjoyment of mathematics, science, and problem solving (e.g., O’Connell, 2018); a strong sense of their scientist identities (e.g., Ashford, 2016); and a desire to give back to their communities (e.g., Hodari et al., 2015).
Summary of Workplace Findings
At the workplace level, research shows that structural barriers for women of color include a lack of diversity and resulting isolation (e.g., Alegria, 2016); the alienating, hypermasculine “bro” culture of tech (Scott et al., 2017); and the lack of recognition of the women’s achievements, which translated into slower rates of professional growth and promotions (e.g., Smith, 2016). Social barriers include challenges related to workplace biases and microaggressions, specifically, having their credibility in technology and computing questioned (e.g., McGee, 2017) and needing to disprove negative stereotypes (e.g., Williams, 2014).
The literature suggests that structural supports to advance women of color include diversity in the workforce and leadership (e.g., McGee, 2017); on-the-job supports such as networking and mentoring (e.g., Foster, 2016); opportunities for professional growth like advanced technical training (Smith, 2016); and job security and relative high pay in tech (Middleton, 2015). The literature further revealed that social supports for women of color include professional organizations such as Latinas in Computing or the National Society of Black Engineers (Herling, 2011); faith, church, and community (e.g., Ross, 2014); and a desire for a better life (e.g., Opara et al., 2005). Finally, given the increasing demand for workers with expertise in computing, there is a burgeoning number of short-term, alternative education options arising that enable women of color to enter jobs in the tech sector without having to complete a multiyear academic degree (e.g., Kvasny and Chong, 2006).
Recommendations for Future Research and Funding Needs
The research described in this chapter represents the burgeoning number of studies published in the past decade on girls and women of color in technology
and computing fields. However, several gaps in our knowledge base remain on this topic; these gaps are described below. The committee strongly recommends that researchers consider taking up these topics in future research work, and that funders prioritize funding for these topics. Research that helps address the gaps identified by the committee will critically contribute to the knowledge base about how to better support and retain girls and women of color in technology and computing education and careers, and funding for such research should be prioritized.
K-12: Topics for Future Research and Funding
- Differences between girls of color and non-Hispanic white girls with regard to the digital divide, access to computer science courses, and quality of online learning
- Differences between girls of color and non-Hispanic white girls, and between women of color and non-Hispanic white women, with regard to educational experiences during the COVID-19 pandemic
- Intervention components that can positively impact the identity, confidence, interest, and aspirations of girls of color in tech and related fields, including counter-stereotypical role models, culturally relevant computing curricula, access to early childhood education that promotes culturally relevant socioemotional development, and diversity in the computer science teacher workforce
Higher Education: Topics for Future Research and Funding
- Impact of family support/encouragement and other early exposure experiences for women of color in tech and related fields
- How finances and financial aid (e.g., scholarships, loans and debt, salaries) impact women of color’s entry into and persistence in tech and related fields
- Experiences of women of color at transition points throughout their academic career (e.g., from K-12 to higher education, from community college to four-year institutions, and from undergraduate to graduate education)
- Experiences of women of color in tech and related fields at the undergraduate and graduate levels at minority-serving institutions
- Experiences of women of color in tech and related fields at technical colleges and community colleges
- Impact of peer mentoring on the success of women of color in tech
- Experiences of graduate students in tech and related disciplines who are women of color
- Experiences of women of color in tech in STEM and non-STEM community and counterspaces (i.e., safe spaces)
Workplace: Topics for Future Research and Funding
- Effective recruitment and hiring of women of color in tech and related fields
- Alternate pathway programs for women of color into tech careers
- Experiences of women of color in tech in STEM and non-STEM community and counterspaces (i.e., safe spaces)
- Award nominations and award receipt rates for women of color in tech
- The intrinsic qualities of women of color that contribute to persistence in tech and related careers
- Women of color in the tech workplace, specifically
- how they enter the field (having a technical background vs. not having one)
- promotion rates, experiences with employers, reasons for persistence or attrition
- how finances (e.g., salaries, pay inequality) impact women of color’s entry and persistence in technology and computing
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