Challenging Assumptions Around the Recruitment, Retention, and Advancement of Women of Color in Higher Education
Applying an intersectional lens to higher education makes sense of the experiences of women of color by situating them within the confines of place (e.g., department, school, college) and position (e.g., undergraduate, graduate student, faculty member), and by examining how they interact with organizing features such as meetings, laboratories, geographical location, and modes of working in academia. For example, how a Latinx, female computer science faculty member journeys through a predominantly white institution seeking tenure and promotion may yield markedly different experiences than the same individual navigating this experience in a minority-serving institution1 as a graduate student. The race and ethnic constitution of higher education institutions are only two categories requiring consideration. Variability in levels of research funding, size, departmental structure (interdisciplinary vs. single-discipline enclaves), whether a higher education institution is public or private, and any combination of these variables (e.g., a predominantly white all women’s college such as Smith College or a historically Black all women’s college like Bennett College) also shapes the experiences of women of color. There is no one-size-fits-all approach to the
1 Minority-serving institution (MSI), refers to (1) historically defined MSIs, those that were established with the expressed purpose of providing access to higher education for a specific racial minority group and (2) enrollment-designated MSIs, those that are federally recognized as MSIs based on student enrollment thresholds. Historically defined MSIs include Historically Black Colleges and Universities (HBCUs) and Tribal Colleges and Universities (TCUs). Enrollment-Designated MSIs include Hispanic-Serving Institutions (HSIs), Alaska Native-Serving and Native Hawaiian-Serving Institutions (ANNHIs), Asian American and Native American Pacific Islander-Serving Institutions (AANAPISIs), Predominantly Black Institutions (PBIs), and Native American-Serving Nontribal Institutions (NASNTIs). In this report discussion of minority-serving institutions is targeted to HBCUs, HSIs, TCUs, and AANAPISIs, collectively.
recruitment, retention, and advancement of women of color in higher education that can be used for all women belonging to any one group. Intragroup difference requires nuanced strategies that recognize explicit and implicit forms of oppression and how these acts may appear differently based on the micro-, meso-, and/or macro-level in which they occur (e.g., at the level of classrooms; departments; and/or universities, states, or geographic regions, respectively).
This chapter discusses three statements identified by the committee that are frequently used by higher education leaders to describe barriers to the recruitment, retention, and advancement of women of color (both students and faculty) in technology and computing fields in their institutions (Box 3-1), and discusses assumptions often cited to underpin these statements. The committee drew on data, both statistical and empirical, to examine assumptions related to challenges that higher education leaders and institutions face in efforts to increase the representation of women of color in higher education computing departments. The committee also reviewed evidence that counters these assumptions and identified promising practices and recommendations for higher education institutions. In cases where there was a dearth of data focused on women of color in tech, the committee relied on data with contextual information drawn from the lived experiences of women of color and on research literature focused on science, technology, engineering, and mathematics (STEM) courses of study and professions more broadly. This chapter offers recommendations for intentional action that leaders in higher education can take to improve the recruitment, retention, and advancement of women students of color pursuing technology and computing degrees and women of color faculty in these fields.
APPLYING AN INTERSECTIONAL LENS TO THE EXPERIENCES OF WOMEN OF COLOR IN HIGHER EDUCATION
As discussed in Chapter 1, the committee used the critical race theory of intersectionality as an analytic framework to interpret evidence about the underrepresentation of women of color in technology and computing fields. Power is a core construct of intersectionality and provides a lens to analyze the experiences of women of color in higher education (Collins, 2019). Crenshaw (1991) described power as relationships. As individuals interact with each other, they develop interpersonal patterns, and meaning is made along various axes such as race, gender, ethnicity, indigeneity, social class, and other social categories. Research illustrates how, through interactions with classmates and professors, women of color are treated as powerless individuals lacking “testimonial authority,” a term used to describe the credibility granted to a person or group by other socially dominant groups (Kidd and Carel, 2017). This phenomenon has been well documented in computer science departments (Whitecraft and Williams, 2010). The resultant power dynamic is most evident during critical transition points—periods during which significant changes in academic and career tra-
jectories can occur in the lives of students and faculty—such as transitions from community college to a four-year college, from undergraduate to graduate or graduate to faculty, and in promotion and tenure.
Power also influences how individuals relate to structures such as institutional hierarchy or tenure and promotion. Analyses of the extent to which individuals follow the policies and procedures that subjugate women of color or push them out of higher education can reveal what undergirds the power structure. Recognizing the disciplinary, cultural, and structural domains by which the policies and procedures operate is also key to an intersectional endeavor and will reveal not only the complexity of contexts but also how pernicious strategies and systems operate at all levels. Enobong (Anna) Branch, senior vice president for equity at Rutgers University who presented to the committee in April 2020, discussed the problematic nature of using the pipeline metaphor to describe the trajectory from K-12 to higher education. The pipeline metaphor frames women of color as passive participants in an unchangeable system rather than individuals who must actively challenge, engage, and interact with existing systems. Branch proposed an alternative framework for articulating the agency of women of color and the challenges they face—a road with exits, pathways, and potholes. This framework recognizes multiple entry and exit points, challenges that may be experienced differently by different individuals, and challenges that are universal. It recognizes that the ability to navigate even universal challenges can be affected by an individual’s experience, agency, self-efficacy, and skill sets (Branch, 2020). The committee adopted this perspective in its activities and analysis.
Through a multitude of structures and policies, higher education institutions have been established and maintained endowing certain individuals with power, financial support, and privilege provided they assimilate the cultural mores of the context. Those in power set the rules, standardize regulations, and maintain the status quo. Promotion and tenure committees, institutional review boards, department chairs, deans, and other authoritative leaders maintain a coveted position within this ecosystem. Endowed as gatekeepers, these individuals are privileged—and at most institutions include few women of color. However, power is not only about status or role. While data clearly illustrate how few women of color obtain leadership roles in technology and computing in higher education, the few women of color who do obtain positions of power endure more oppressive environments than their white peers (Dotson, 2011). To improve the recruitment, retention, and advancement of women of color in higher education it is critical to analyze and offer solutions as to how women of color can have space to narrate their experiences and be heard as testimonial authorities.
A discussion of each key statement excusing the underrepresentation of women of color in tech, and its underlying assumption(s), follows.
ASSERTION: “WE CANNOT FIND QUALIFIED WOMEN OF COLOR”
A lack of qualified women of color is often cited as a reason for disproportionately low numbers of both students and faculty members. The committee examines the validity of some of the key assumptions that are used to support this assertion in the sections that follow.
Assumption: Women of Color Don’t Pursue Tech Degrees Due to a Lack of Encouragement or Interest
The number of women of color who graduate with computer science degrees is low.2 In 2018, women of color constituted 18 percent of the overall population in the United States; however, they make up less than 10 percent of all bachelor’s degrees earned in computing, with Latinx women the most underrepresented in computing bachelor’s degree completion rates relative to their population in postsecondary education. At the doctoral level, women earned 21 percent of all doctorates in computing with less than 5 percent awarded to Black, Latinx, Native American/Alaskan Native, or Native Hawaiian/Pacific Islander women (McAlear et al., 2018). However, students from underrepresented groups aspire to major in STEM in college at the same rates as their white and Asian American peers, and have done so since the late 1980s (NAS, NAE, and IOM, 2011, p. 4), and women of color express strong interest in science and engineering fields and greater intention to major in these fields in postsecondary education than do white women (Malcom and Malcom, 2011, p. 163).
Within higher education, one excuse given for the lack of representation of women of color has to do with the influence of the family—the argument being that young girls of color, as early as middle school, are not encouraged by their families to pursue careers in computing, thus the seed is not planted early enough. Encouragement from family can indeed contribute to a student being interested in a career—it contributes to a sense of self-efficacy (e.g., “I can study this”), and it is important that young women of color know early on that a career in tech is possible (see Chapter 2). It is also true that interest in STEM careers can be expressed as early as middle school; however, this assumption perpetuates the notion that interest begins in middle school and continues in a linear trajectory through high school and college, leading to a career in STEM, and implies that there is a pipeline to a career in STEM that has early leaks (Harackiewicz et al., 2012). This assumption overlooks the structural and social factors that can deter women of color from pursuing computing degrees.
Other factors can also influence whether young girls feel encouraged to pursue tech as a potential career and whether they feel accepted within tech environments. During its February 2020 workshop, the committee heard from Kyla McMullen, assistant professor and director of the SoundPad Lab at the
University of Florida. McMullen presented data from a 2012 study by the Girl Scout Research Institute showing that 62 percent of African American girls felt their teachers were unsupportive of their career interests compared to 73 percent of white girls who felt their teachers were supportive. She also highlighted the role of personal culture, how it may sometimes conflict with the culture of tech and science for classrooms, and how that conflict can potentially discourage girls of color from pursuing technology and computing careers. For example, students whose cultures value cooperation more than competition may not feel that they fit in in fields where competition, individual assertiveness, and highlighting one’s own contributions are valued more than collaboration with peers (McMullen, 2020). The lived experiences of these students later in life may have a greater influence on their decision to pursue a computing major than early encouragement.
Challenges to Starting
Much of the literature related to underrepresentation of women in tech and STEM focuses on deficits in the contexts or capabilities of women of color (e.g., programs that are too difficult, lack of encouragement from family, family obligations, lack of parental or other role models, and lack of access) rather than structures and systems that impede progress and result in persisting inequity in the number of women of color in tech majors (Figure 3-1). For example, admissions to academic programs can be biased and present an obstacle to women of color at the very start of their pursuit of a tech degree. Admissions criteria for many higher education institutions often include standardized test scores; however, research has demonstrated that racial and gender bias may show up in standardized tests in a number of ways (e.g., questions that use expressions that are more common in white society or use of a multiple choice format) and can underpredict future academic success at the postsecondary level (NEA, 2021; Sukumaran, 2020). For example, Holloway and colleagues (2014) found that at a large Midwestern public university while student applications to engineering departments increased 46 percent over a five-year period, admission of women increased by only 23 percent. (While the study did include women of color, the results were not disaggregated by race and gender.) They also found that biases that affected admission of women into programs, when addressed, had a positive impact and increased the number of women admitted. Of interest, they reported that the cognitive metrics of women applicants had statistically significant higher values than the men in grade point average, class rank, and Scholastic Aptitude Test (SAT) verbal scores.
Education infrastructure during the K-12 years can influence outcomes for women of color and can also inform an understanding of barriers to tech fields in higher education. Disparities in early educational and life experiences (such as a lack of educational opportunities) of social norming suggesting that girls, particularly girls of color, are not as well suited for technology and computing
fields, can shape later life experiences and opportunities for women of color as students and as they pursue postsecondary education or seek to advance into careers as faculty. Kamau Bobb, senior director of Constellations Center for Equity in Computing at Georgia Tech, presented to the committee in May 2020 to discuss the connections between secondary school and higher education and the importance of understanding the contexts of where students in higher education are coming from. Using Atlanta as an example, Bobb highlighted how unequal allocation of educational resources and opportunities among schools even within the same city can disproportionately and negatively impact students of color—for example, when students have less access to advanced placement courses or lack of access to internet and computing devices at home. For students who attend these schools, these inequalities in infrastructure can lead to underpreparation and lack of access to rigorous coursework for students who are motivated and capable, which can have lasting effects that affect outcomes in higher education (Bobb, 2020).
The committee also heard from speakers from its June 2020 workshop who discussed infrastructure challenges experienced by Native students. Twyla Baker, president of Nueta Hidatsa Sahnish College, also cited lack of wireless internet access, and in some cases even cell phone towers, as a major infrastructure challenge for students and their communities and a potential barrier to successful preparation and persistence in higher education (Baker, 2020; Delgado-Olson, 2020). Historically, communities located on tribal lands have had lower levels of access, to telecommunications services relative to other populations (Adcock, 2014). As mentioned in Chapter 2, the lack of or insufficient access to reliable broadband internet service in rural areas can be a significant barrier to learning for Native American students. The digital divide is notable in minority-serving schools, particularly in tribal schools (Varma and Galindo-Sanchez, 2006). In interviews with Native American undergraduate students enrolled in a computing program at six nontribal and tribal universities, lack of exposure to computing and technology was cited by female respondents more frequently than male respondents. Female respondents from tribal sites reported a lack of resources more than respondents from nontribal sites (Varma and Galindo-Sanchez, 2006). Andrea Delgado-Olson, founder and chair of Native American Women in Computing, discussed how the digital divide on reservations impacts students and communities, discussing how the needs of communities may differ since the nature of this challenge can differ by region and within regions.
Challenges at Transition Points
Students from underrepresented groups face obstacles at transition points after entering higher education (Hurtado et al., 2007). A significant number of women of color pursuing tech degrees are non-traditional or “post-traditional” (NASEM, 2020) and do not fit the old notion of full-time enrollment in college,
coming straight from high school, living on campus, without an outside job, and graduating in four years. Women of color as well as women in general are more heavily concentrated in community colleges and therefore face transitions that can put up barriers to their progress.
There are numerous factors that may influence women of color to begin higher education in community colleges (such as family obligations, access to support structures, and lack of sufficient financial aid at more expensive schools) even when they could otherwise begin at a four-year institution (Gates, 2020). Women of color represent a disproportionate number of students who received an associate’s degree at a community college prior to earning a STEM baccalaureate degree (NASEM, 2016; Reyes, 2011). During the 1990s and early 2000s, part-time enrollment grew for women in community colleges, with particularly strong increases for African American, Hispanic, and Asian American women (Reyes, 2011).
As a result, a significant number of women of color start their academic careers in community colleges and then transfer to four-year institutions. A transfer usually requires declaring a major, which can be influenced by amount of financial aid, number of credits that can be transferred, and even availability of preparatory courses in the community college for the desired major. Thus the transition to four-year colleges can lead to many women of color dropping out or changing majors to fields other than technology and computing. Challenges such as these, rather than lack of interest in computing, create obstacles for many women of color who might otherwise continue the pursuit of a technology and computing degrees or careers.
Challenges During the Undergraduate Years Due to Institutional Culture and Climate
According to one longitudinal study of students enrolled in postsecondary education, 32 percent of students who declared engineering and engineering technology majors and 28 percent of students who declared computer and information sciences majors changed majors within three years of initial enrollment (NCES, 2017, 2020). While the decision to change majors may be influenced by a number of factors, often it is not an issue of academic preparation (e.g., school selectivity or rigor) that prevents women of color from pursuing their interests but rather institutional climates. Institutional climates are a manifestation of a college or university’s culture, and are created and sustained by physical structures, policies, underlying values, and social norms. Climates can influence student performance, engagement, and persistence (NASEM, 2016, p. 60). As discussed in Chapter 2, unwelcoming campus and departmental climates can be structural barriers for the success of women of color in technology and computing in higher education. In Cohoon’s study (2001) across computer science departments in Virginia, cultural factors had an impact on retaining women students in computing programs at
the undergraduate level. The study found that departmental factors that affect gendered attrition include the availability of same-sex peer support; faculty characteristics and behaviors; and institutional and community environment.
Several presentations to the committee during its four public workshops in spring 2020 also highlighted the role of institutional climate and peer attitudes and how they affect the persistence of women of color. For example, Gregory Walton, associate professor of psychology at Stanford University, highlighted how the belief that one does not belong can become self-fulfilling. He also presented examples of statements from Black women in higher education on their experiences in that environment, including: “my input is undervalued because it’s not ‘mainstream’ or ‘relatable’” and “I’m more qualified than my peers but I’m treated as less than” (Walton, 2020). Once women of color are in their four-year academic programs, they may face “social pain.”3 In situations where students are from underrepresented groups, their social identities are more salient to both minority and majority group members (Hurtado et al., 1996). Being the “only” (or having “solo status”) brings more scrutiny of their performance and might trigger the stereotype threat associated with their group (Hurtado et al., 2007; Steele, 1997; Thompson and Sekaquaptewa, 2002). Such barriers can be more pronounced for women of color who find themselves in a “double bind” of race and gender marginalization when navigating the STEM culture (Malcom et al., 1976; Williams et al., 2014). Other challenges include low self-confidence (or low self-efficacy) and financial aid struggles (Ong et al., 2020; Reyes, 2011).
Assumption: Women of Color in Tech Are More Interested in “Soft” Computing Sub-Disciplines
Women and people from underrepresented groups are more highly represented in applied computing areas,4 such as computing education, human factors, and human-computer interaction, fields often characterized as “soft” sub-disciplines that may not be valued as highly in the field. Publication patterns show that women are more likely to publish in conferences on human factors, seen as a less prestigious field and considered in alignment with feminine stereotypes, while men are more likely to publish in conferences on algorithms, a field with higher prestige and considered in alignment with masculine stereotypes (Cohoon et al., 2011). These trends lead some observers to conclude that the smaller presence of women overall and women of color in particular in less prestigious technology and computing fields is due simply to their interests and preferences.
4 See the Computing Research Association’s Taulbee Survey for more data on enrollment and degree completion in information, computer science and computer engineering and in providing salary and demographic data for faculty. Statistics given include gender and ethnicity breakdowns. https://cra.org/resources/taulbee-survey/ (accessed October 7, 2021).
Computing education and human factors are examples of popular computing sub-disciplines where women publish. Two conferences of the Association for Computing Machinery’s Special Interest Group on Computer Science Education, the Technical Symposium on Computer Science Education and the Conference on Innovation and Technology in Computer Science Education, have high percentages of women authors at 29 percent and 32 percent, respectively. Women typically outnumber men among teachers, and publications in computing education also have high participation from women. Human factors has strong ties to psychology, another area where women outnumber men. Differences in authorship along gender lines are also often present in the popular press, helping cement the notion that women are not interested in technical areas of technology and computing fields. For example, an article in Forbes emphasized the notion that women can be in tech without being an engineer or developer (McCullough, 2016). While statements like these encourage women and young girls to consider STEM careers, they reinforce the artificial division within computer sciences that more technical, and possibly higher-paying jobs, belong to men, and women should focus on the more social, applied, feminine jobs.
However, the committee did not attribute the greater participation of women of color in specific areas of computing solely to their interests. Rather, women may lean toward human-related computing areas because these areas afford fulfillment of communal goals or because they are where they see role models, receive mentoring, or simply feel welcomed and thus face fewer social pains (Corbett and Hill, 2015; Ong et al., 2020). These sub-disciplines in computing have been better at mentoring and supporting women. Evidence suggests that a few women of color pioneers in some computing sub-disciplines—possibly brought into computing through interdisciplinary research—have found a home and played a significant role as sponsors to bring in others like them into computing. As these areas grew, the numbers grew and the spaces became more welcoming. However, women may suffer during tenure process as a result of leaning into “soft” computing sub-disciplines. For example, a core technical research grant and an education grant are seen in a very different light, the latter often seen as a second class citizen. Information Systems/Information Sciences is another area which is often seen as a second class citizen in computing. This could be due to campus cultures that elevate some departments over others.
The power of role models also helps explain increased numbers of women of color in some areas of computing. For example, the Computer-Human Interaction Mentoring Workshop has brought together a talented group of students from underrepresented groups doing research in human-computer interaction, beginning in 2010 and 2012 and continuing in 2018 and 2020.5 Many participants have noted the impact that these workshops had in their careers, highlighting the networking, social connection, and support derived from each other. Most
of these students are now in tenure-track positions in academia or in industry research positions (Metoyer et al., 2019).
More study is needed to determine why these sub-disciplines in computing have been better at mentoring and supporting women, to understand whether strategies that attract women of color to these sub-disciplines could be applied to other technical sub-disciplines where women of color are less represented, and to understand the role that women of color play in these spaces.
Lack of Recognition of the Relevance of Communal Goals in Computing Sub-Disciplines
A report by Corbett and Hill (2015) highlights findings from a number of researchers that show that work with a clear social purpose that prioritizes communal goals over career goals and that allows one to help and work with others is preferred more by women than by men. Although there are opportunities for computing jobs to provide these kinds of opportunities to fulfill communal goals, these jobs are typically not viewed that way. More often jobs in computing and other tech fields are thought of as careers with limited opportunities to work with others and contribute to one’s community. While this may be true in some cases, this perception may help to partly explain the continued underrepresentation of women in these fields (Corbett and Hill, 2015). Data presented to the committee also support the idea that a lack of persistence in tech can be motivated by culture. Kathy DeerInWater presented preliminary data from research that found that Native American women and two-spirit individuals were motivated to remain in computing when their work allowed them to give back to the community—an important component of Native identities. These findings support results from previous work in this area (DeerInWater, 2020). Research found that many women of color place great value on connecting work to community impact, activism, and outreach, especially in their home communities and as a tool for improving conditions in the workplace for other women of color (Gates, 2020; Ong et al., 2020).
The communal goal congruity perspective suggests that an important aspect of the decision of whether or not to pursue a career in a STEM field is the belief that STEM careers do not fulfill communal goals. To the extent that individuals anticipate and experience STEM fields as fulfilling their valued communal goals, they will be more likely to enter and persist in such fields (Diekman et al., 2017). Drawing on the literature related to women in STEM, evidence suggests that because women may place a greater value on communal goals than men, women may be more likely to decide against careers in STEM in favor of careers in other fields (Corbett and Hill, 2015). This may hold true for women of color, in particular, as well. Thus, the reason for women’s relatively greater increased interest in computing sub-disciplines such as computing education, human factors, and human-computer interaction may be because of their perception that these areas will allow them to meet highly valued goals.
A study examining interest in computing among middle school African American girls found that students who saw the application of computing as relevant to their lives showed increased interest in applied computing areas like human-factors and human-computer interaction. The study included creating a hand-sketched user interface for an iPhone app that included text chat, video chat, and/or audio chat features (Robinson, 2015; Robinson and Pérez-Quiñones, 2014). Participants showed high levels of ownership of their designs, creating names for the app (e.g., Chirper, Musicana, Mingle) and images that reflected their own personality (Figure 3-2). Before this activity, the girls expressed the opinion that computer science was boring. Once they were able to “visualize their designs as realistic applications” and interact with the study director, a young African American woman from the same region as the participants, their perception of computing changed. In a survey at the end of the study, they expressed that computing was “cool” and were willing to explore it further. The research demonstrates how exposure to an applied area of computing can change the perception of the discipline and build interest (Robinson, 2015).
Assumption: Women of Color Are Willingly Opting Out of Academic Careers in Tech
Although the proportion of science degrees granted to women has increased, there is a persistent disparity between the number of women receiving doctoral
degrees and those hired as junior faculty. This enduring gap suggests that the problem of underrepresentation of women of color among tenured STEM faculty will not resolve itself solely by more generations of women moving on an upward trajectory through academia; rather, it suggests that women’s advancement within academic science may be actively impeded (Moss-Racusin et al., 2012). There is an assumption that any time women of color in tech leave higher education careers or choose not to pursue faculty or leadership positions, they are willingly opting out. The illusion of choice as the sole motivating force persists as a result of the failure to recognize how existing systems as well as organizational and academic climates that serve to limit opportunities for women of color prevent their entry, create unwelcoming environments, and effectively force them out.
It is often assumed that women of color who leave their careers in academia early (e.g., before making full professor) do so because they prioritize attending to family needs (such as taking care of kids or elderly family members) over their career aspirations. While work-family factors have been found to play an important role in women’s exits from engineering (Hunt, 2010), family factors do not account for the majority of exits from STEM jobs (Ashcraft et al., 2016; Glass et al., 2013). Rather, there are a multitude of structural and systemic factors and conditions affecting these decisions (e.g., organizational culture, workplace bias, lack of advancement). The prevalence of this assumption leads to reform efforts focusing on the individual rather than the structures the individual must endure. Focusing on individual choice at the exclusion of systemic challenges maintains important blind spots. The following sections elaborate on some of these blind spots regarding institutional structures, such as gatekeeping, workplace hostility, lack of access to power, and institutional policies that may negatively impact women of color.
Gatekeeping, a commonplace process used by academic programs to establish and adhere to protocols and policies designed to evaluate students’ suitability for a professional practice (Hunt and Nicodemus, 2014), starts early and continues along individuals’ career trajectories. However, it can take the form of academic elitism in the hiring process for faculty whereby the academic system devalues people whose doctoral degrees are not from prestigious schools—a group disproportionately including women and underrepresented minorities—thus limiting these individuals’ opportunities (Clauset et al., 2015). Higher education is a primary site of “opportunity hoarding” where members of the dominant group serve as gatekeepers for access to resources (Riegle-Crumb et al., 2019). When faculty and administrators serve as gatekeepers, their behaviors may serve to discourage and disadvantage women of color (Canning et al., 2019). Women faculty of color can be subjected to epistemic gatekeeping when their scholarship and contributions are minimized and devalued (Dotson, 2012, 2014).
Organizational and Systemic Structures Affecting Academic Climates
Earlier in this chapter institutional climates are discussed that cause social pain that deter women of color from pursuing degrees in technology and computing fields, but once women of color are on a pathway to enter academia or are faculty or administrators in these fields, they also often contend with unsupportive and hostile climates that can push them to leave their career trajectories in tech fields. A number of large-scale empirical research studies have documented the persistent and pervasive problem of hostile culture. For example, at least half of all women academics in STEM (versus 19 percent of men academics in STEM) report experiencing sexual harassment, and even greater numbers (78 percent) of women in male-dominated STEM workplaces report experiencing gender-based discrimination (Funk and Parker, 2018; NASEM, 2018a). Also discussed above, several studies have investigated stereotypes encountered by women of color. Black women, for example, are reported as being seen as defiant, angry, or incompetent, and Asian American women are often perceived as not being natural leaders or as being eternal foreigners. Awareness of these stereotypes causes many women to change their behaviors in the workplace to avoid these types of characterizations. Nevertheless, both student and faculty women of color express feelings of isolation and tokenism in the classroom and in the workplace (Ong et al., 2020).
Women of color are often placed in disadvantaged positions due to historical and current discrimination and a lack of access to power and positions of leadership (McGee, 2020, 2021). A number of experts invited to present to the committee at its public workshops highlighted the importance of access to power within academia and the role that access to decision-making power can play in improving outcomes for women of color. Stephanie Adams, dean of the School of Engineering and Computer Science at the University of Texas at Dallas, discussed the importance of accountability in higher education. Leadership at the institutional and departmental level plays a role in shaping the diversity of higher education institutions, cultivating a climate of inclusivity, and creating policies that encourage and reward practices that increase equity (Adams, 2020; Gilbert, 2020; Su et al., 2015). Consistency of leadership in academia, from the chancellor/president down through the provost and deans to department chairs, is important. Constant changes in leadership can lead to changes in strategic plans, departmental foci, degree programs, and requirements, which make it increasingly difficult for students and faculty who are already at risk for retention to persist.
Women of color are underrepresented in these positions of leadership. While not specific to higher education, data show that women of color report slower or even non-existent promotion rates relative to their peers and are more likely to have their credibility questioned by their peers and leaders. Different groups of women of color may experience different challenges related to accessing power or moving into positions of leadership (ACE, 2021; Hill et al., 2016). Asian American women, for example, while overrepresented at the bachelor’s level
and at the career entry level, face significant challenges advancing to positions of leadership and fare worse in advancement than other groups of women of color (Kim et al., 2018; Peck, 2020). Although a growing number of women have begun to occupy top-level leadership positions, research suggests that these women are likely to be promoted into positions of leadership where the risk of failure is high or in times of crisis—a phenomenon referred to as the glass cliff (Ryan et al., 2016). Women of color who want to advance may end up taking on unwinnable roles without sufficient institutional supports in place.
ASSERTIONS: “WE JUST HIRE THE BEST” OR “WE ARE COLOR BLIND”
An assertion of equality and fairness underpins many of the assumptions surrounding hiring, tenure, and promotion policies and practices. The committee examines these assumptions in the sections that follow.
Assumption: Recruitment and Advancement Decisions Are Based on Meritocracy
The ideology of meritocracy has embedded within it two tacit assumptions: (1) equal opportunity for all, and (2) success is the result of hard work and intelligence. These assumptions lead to unintended outcomes, both of which warrant further exploration. For women, there is a significant threat to academic and career progression when meritocratic explanations are substituted for structural explanations of inequality (Cech and Blair-Loy, 2010). Ample evidence supports the notion that “structural racism in STEM often manifests as meritocracy” (McGee, 2020, p. 635). The illusion of meritocracy ignores patterns of inequality throughout higher education and society, and how structural inequality rewards and privileges those who have wealth and access to influential connections.
Challenging meritocracy is most often met defensively and seen as an attack on the concept of merit. When the challengers are women of color, they often face hostility and backlash for confrontation and, in fact, for their very presence. However, the assumption that decisions are based on meritocracy leads to numerous non-meritocratic outcomes for women of color in STEM: unequal opportunities for entry and advancement, exclusionary and unsupportive cultures, unequal distribution of rewards when deserved, and situations where organizations that purport themselves to be meritocratic, but are not, reinforce members’ beliefs that they and their organizations are fair and objective (Kang and Kaplan, 2019). Holding on to the assumption of meritocracy also prevents the pursuit of meaningful systemic change. Not surprisingly, those who benefit most from the assumption of meritocracy are least likely to challenge it—for to do so would require admitting that their own merit might be in question. In challenging meritocracy, the claims of merit-based advancement must be disrupted along with the
presumption of equal opportunities, equal access to connections, and equitable distribution of rewards.
Inequitable Burden of Service and Mentoring Activities
Because of their scarcity, women of color in faculty positions can face demanding out-of-class instructional loads. Unlike white male faculty members, many women of color are called on to advise students of color and others studying in similar fields and to handle minority and gender affairs. Institutional reward systems often preference faculty who spend more time on research and scholarship in tenure decisions over faculty who spend more time on service that is assigned to meet institutional needs (Jaschick, 2010; Turner, 2002, p. 82). Women of color are often asked to take on a large number of service commitments (e.g., serving on hiring committees, serving as a representative of both their gender and their race/ethnicity to speak to potential new hires, serving as an advisor to student groups focused on their identity) which take up time that faculty without such obligations can use for research and publishing. The small numbers of women faculty of color compel them to serve simultaneously as a role model for their profession, race, and gender. In many instances, extra service, diversity work, and higher teaching and mentoring loads are less likely to lead to tenure or to prestigious positions related to committee service, and serve to limit career progression and success (NRC, 2013). Junior faculty members are particularly at risk.
Tenure and Promotion Policies
Institutional policies may also negatively affect whether women of color are granted tenure. So-called stop-the-clock policies have been used as a way to support both men and women faculty who are new parents by providing extra time before a decision is made whether to grant them tenure. However, taking personal or family leave time or needing to shift attention to caregiving responsibilities (e.g., for children or elderly family members) can lead to women being viewed as less committed to their careers (Rosser, 2004). Consequently, many women on the tenure track opt out of using policies meant to counteract negative effects on their career progression such as stop-the-clock policies (Wasburn, 2004).
Moreover, research has shown that men may actually benefit more from these policies as they are more likely to utilize the extra time to publish more (potentially raising the bar for others) rather than for its intended purpose (Jaschik, 2016). In addition, research suggests that women are not exiting these careers primarily for family concerns, but that when they do leave due to family obligations they might have made different choices if more flexible options to support these competing responsibilities had been available (Ashcraft et al., 2016). In theory, this is a policy that could also be used to grant extra time to account for relatively
heavy faculty service obligations. However, more research is needed to determine whether uptake of this policy in broader contexts would lead to increases in the number of women of color being granted tenure.
Another area that warrants further research is whether bias and inequitable treatment in the evaluation of faculty scholarship affect the progression of women of color in academia. Settles et al. (2020) finds that scholarly devaluation6 is more common to women and faculty of color. In their study of over 100 faculty of color at a research-intensive institution they found that some types of scholarship were evaluated as lower quality because of the topic (e.g., social problem focused), method (e.g., qualitative), publication outlet (e.g., top-tier journals or presses), and whether it was grant funded. The study found that scholarly devaluation occurred through evaluation processes that the university used to make merit, promotion, and tenure decisions (Settles et al., 2020).
ASSERTION: “WE HAVE MADE PROGRESS”
Defining metrics of success and collecting adequate data are key steps to accurately measuring progress in improving the representation of women of color in technology and computing majors and faculty positions. Although many higher education institutions state that they have made progress in increasing diversity, evidence suggests that there are caveats to this assertion.
Assumption: Increasing Diversity Numbers Equals Success
Much of this report indicates how progress in the advancement, recruitment, and retention has been slow and, in some cases, nonexistent for women of color in tech. Nevertheless, there remains a narrative in higher education mythologizing how progress has indeed occurred, at least for certain groups, with the underlying assumption that an increase in diversity on campus must mean that institutions are taking the right steps. The positivist approach to research has a long history of using numbers to reveal what the researcher deems as the “truth.”
The Distinction Between Diversity and Inclusion
Although there have been considerable critiques against positivism (Tuck and McKenzie, 2015), the argument that numbers are best suited to document the totality of experiences for women of color prevails. The presence of this approach promulgates a troubling assumption that precludes thoroughly identifying the complex, interrelated issues affecting women of color in tech.
6 Scholarly devaluation is a component of epistemic exclusion—a theory that “proposes that women and faculty of color are disproportionately harmed by invisible biases built into ostensibly objective and neutral performance standards within systems of evaluation” (Settles et al., 2020, p. 4).
Measuring diversity alone often fails to capture the full picture. Far too often, institutions of higher education measure progress in terms of diversity numbers. Thus, counting and revealing the number of students of color entering and graduating from technology and computing fields has become the norm, with diversity positioned as the only measurement. Stated differently, postsecondary schools recognize and are applauded when they can illustrate an increase of Black and Brown individuals diversifying their student pools or faculty. The committee found this assumption to be problematic for a few reasons.
First, institutions of higher education tend to use “diversity” as the gold star rather than focus on inclusion as a core principle for equity. To assume that a more diverse set of bodies will automatically lead to more equitable ends diminishes the significance of structural barriers and systemic oppression. There are a host of stories from women of color who recognize their staunch oppressors as people belonging to their same race and/or gender social groups. Conversely, there are just as many stories in which women of color attribute their success to mentors who are not women of color. Notably, the committee agreed that there should be more women of color in technology and computing, particularly in leadership roles; however, simply diversifying leadership will not nurture an inclusive environment. Race and gender are not proxies for behavior. Context also involves cultural standards and culture refers to behaviors and expectations. Higher education leaders (e.g., president, provosts, and deans) set the tone for inclusion through their own behaviors and expectations. Without fully unpacking and addressing the complexity of diversity and inclusion, systemic change will remain elusive. The invisibility of microaggressions is what allows white supremacist actions to prevail. Inequity and inequality will be overshadowed by the simple fact that few are willing to name it.
Second, increasing the number of women of color does not necessarily mean a diminishing of the hostile environments they may endure. Without careful attention to understanding the context as well as the variables that inhibit or foster success for women of color, missed opportunities for scaling best practices continue. Take, for example, an analysis by Daily and colleagues (2020), which identified four-year institutions of higher education by various categories (e.g., public, private, non-profit, minority-serving) to chronicle the graduation rate between of various groups of women of color. Using data from IPEDS,7 their analysis reveals how certain all-women colleges that are predominantly white institutions have impressive rates graduating certain groups of women of color with a computer science degree (Daily et al., 2020).
7 IPEDS is the Integrated Postsecondary Education Data System. It is a system of interrelated surveys conducted annually by the U.S. Department of Education’s National Center for Education Statistics (NCES). IPEDS gathers information from every college, university, and technical and vocational institution that participates in the federal student financial aid programs.
Lack of Disaggregated Data
Throughout this report, the committee has discussed the lack of data that are specific to women of color in tech, and more specifically to women of color in tech in the United States. In many cases, data are condensed across categories and presented with all women grouped together or with all women of color grouped together. The small number of women of color is often cited as not sufficient for statistical analysis and serves as the rationale for this aggregation. Privacy concerns are also often cited; however, when these data are not available, women of color lose an opportunity to learn from the experiences of other women who may be facing similar challenges and their strategies for persisting (Begay, 2020; Pawley, 2020). The fear of exposing the few women of color in a technology department or work environment shapes how social science researchers plan and manage their work. When numbers are small enough that women may be identifiable, the push is to aggregate. Stated differently, researchers interested in examining any and all aspects of women of color in higher education typically receive caveats to avoid disaggregating data. The statement “the sample size is too small and risks a reader identifying the subjects” is too often chorused by review committees. “Personally identifiable data” is a phrase meant to protect the few women of color navigating what this report has revealed as hostile non-supportive contexts. But in reality, not reporting the number allows for the maintenance of structures to ignore the issues disproportionately affecting women of color in tech.
Institutions of higher education may also sometimes choose not to disaggregate data based on students’ nationalities. As a consequence, non-U.S.-born students of color are often placed within the “underrepresented” category. This strategy leads to claims of “more students of color” entering technology and computing majors, and the fact that the increase is often due to foreign-born students is overlooked. This grouping also obscures where improvements and systemic changes may be needed to attract and retain women of color since non-U.S.-born students of color may need different supports than U.S.-born students or may leave the U.S. tech and computing workforce after completing their education. This narrative presents a partial truth that further troubles the use of the phrase “underrepresented.”
IMPROVING THE REPRESENTATION OF WOMEN OF COLOR IN HIGHER EDUCATION
Although women of color face significant obstacles along the multiple paths they may follow to a career in tech, recognition of these structural barriers provides an opportunity to mitigate or eliminate roadblocks that can stymie their trajectories and implement policies and practices that allow women of color to thrive and reach their full potential. While there is no one-size-fits-all approach to the
recruitment, retention, and advancement of women of color in higher education that can be used for all women belonging to any one group, research and practice can elevate promising strategies. An important approach to alter the course for women of color in tech is the creation of inclusive environments supported by policies and practices that are informed by systematic data collection and analysis along with leadership, assessment, and the implementation of effective strategies to promote their advancement (see Chapter 5 for more discussion on federal programs that can shed light on practices to address the underrepresentation of women of color in the sciences).
Provide Early Exposure and Encouragement
In an analysis of experiences of Black women in computing, Ashford (2016) discusses six main themes that emerged in her examination of the experiences of Black women faculty who have persisted in the field of computing education. The first two relate to early exposure, encouragement, and validation:
- “I am set apart”: Participants described feeling encouraged and receiving positive reinforcement from parents, teachers, and school administrators. The women also described having been identified as smart and talented in school and set apart in classroom settings as a result. This early reinforcement fostered confidence in their abilities to succeed in computing.
- “I am holding my own”: Participants described experiences during their earlier education experiences that allowed them to demonstrate their abilities and where their sense of belonging was positively reinforced.
Along the trajectory from early exposure through career persistence, Ashford’s analysis suggests that this exposure and encouragement provides a foundation for women to understand the assets they bring to their work, to make an impact, to feel that they belong and can persist in a doctoral program, and ultimately that they have had significant achievement in their career (Ashford, 2016; Branch, 2020; Gates, 2020; McMullen, 2020).
Lack of family encouragement was mentioned above in this chapter’s discussion of assumptions related to why girls and women may not pursue tech degrees. In the face of challenging contexts, parents are an “untapped resource” for recruiting more girls of color into STEM careers in general (Harackiewicz et al., 2012). In her dissertation, Ashley Robinson highlighted the role a mother had in influencing the perception of computing in middle-school African American girls (Robinson, 2015). If a girl’s mother had knowledge of information technology careers, she was more likely to consider such a career. Early encouragement notwithstanding, Robinson also reported that a summer workshop exposing middle-school African American girls to human-computer interaction was enough to give
participants a positive perception of the discipline and lead them to consider a career in tech (Robinson and Pérez-Quiñones, 2014). The findings in that study are similar to those reported in Denner (2011) where one of the strongest predictors of interest in computing for women was simply “technological curiosity.”
Other studies have shown that family support is an influence on Latinx women and women in general (Cohoon, 2001; Denner, 2009). Early findings from Ong and colleagues found that women of color who pursued computing in higher education often entered college with high academic achievement and had early exposure to computing through summer camps, high school programs, or relatives that introduce them to computing. These findings also showed women of color embracing some of the identities that are frequently associated with computing (e.g., that it is for nerds or is geeky), which may help support a sense of belonging (Ong et al., 2020). Therefore, even in the absence of family support, a positive view of the discipline and early encouragement can impact the students’ desire to pursue a computing discipline and their ability to persist in tech fields. Higher education institutions have an opportunity to help create opportunities where women of color can engage with computing at an early age—for example, by creating outreach programs, camps during summer or other school vacations, and after-school programs. Such programs can foster positive environments where girls and women of color are able to challenge stereotypical views of success and gain access and experiences in computing prior to entering postsecondary education.
Early encouragement at the undergraduate level in tech disciplines is important in the decision making to continue onto graduate school. The BRAID initiative (Building, Recruiting, And Inclusion for Diversity)8 is conducting a mixed-methods longitudinal study of computer science departmental changes across 15 institutions. Data are collected from “students, faculty, staff, department chairs, and administrators in order to answer a variety of research questions related to attracting and retaining women and underrepresented minority students in computing majors.” Research from this effort has found that building students’ academic confidence in introductory courses is key in shaping graduate school plans, but confidence may be moderated by gender, race/ethnicity, or other identities (Wofford, 2021). The BRAID initiative may be a useful evidence-based source for promising institutional practices to increase the number of women of color majoring in computer science.
8 The BRAID initiative is co-led by AnitaB.org and Harvey Mudd College. The effort was launched in September 2014 in partnership with 15 universities across the nation. Since 2014, 15 CS departments (“BRAID Schools”) under the leadership of their department chairs have committed to implementing a combination of four commitments in efforts to increase the participation of students from underrepresented groups—racial/ethnic minorities and women—in their undergraduate CS programs. https://anitab.org/braid/ (accessed October 8, 2021).
Pay Attention to Transition Points
As previously discussed, many students face obstacles in their academic career and in particular at transition points—including transitions from community college to a four-year college, from undergraduate to graduate or graduate to faculty, and in promotion and tenure—that can hinder their progress. Women of color also often do not follow the same trajectory to a career in technology that many dominant group members (e.g., white men) follow, for myriad reasons. It is up to academic programs to find a way to increase the support to address the obstacles faced by this group if they want to increase retention with special attention given to the transition points.
Raquel Hill, associate professor and chair of the computer and information sciences department at Spelman College, gave a presentation to the committee in April 2020 highlighting some examples of programming that Spelman has implemented to help equip incoming students with the support they need to thrive and navigate their undergraduate career. For example, Spelman’s Women in STEM program is a seven-week summer bridge program for first-year students planning to major in science, engineering, or mathematics. The program includes for-credit coursework, interdisciplinary research projects, enrichment activities, targeted mentoring from student peers and STEM professionals, and academic advising from program staff. The program also covers the full cost of student participation and provides a stipend. Programs such as these help students get hands-on experience in research, engage faculty, and help build relationships between students and faculty (Hill, 2020).
As also discussed above, it is critical to understand the contexts of students and the choices that have shaped their trajectories—for example, whether family obligations, financial issues, or geographic access to community colleges or minority-serving institutions have influenced the track of their academic career (Gates, 2020). It is equally important to recognize that many community colleges and minority-serving institutions are uniquely positioned to provide supports to women of color that can allow them to persist in tech. Tribal colleges and universities, for example, are not only accessible to their communities, but also able to provide students with culturally relevant opportunities and interactions that are targeted to their needs and support their studies. These institutions are also building pathways and partnerships with larger institutions to provide students with opportunities while allowing them to stay in their communities (Baker, 2020).
Transitions from community colleges to four-year institutions or from minority-serving institutions to predominantly white institutions are two further examples of opportunities to target supports for women of color. For example, at Florida International University, the fourth-largest university in the nation and the largest Hispanic-serving institution, 75 percent of students come from community college. Monique Ross, assistant professor in the School of Computing and Information, presented to the committee in April 2020 and provided insights on supports that may help students thrive, such as strengthening peer networks,
addressing the digital divide, supporting student organizations that help build community, advocating for diverse hires, providing computing opportunities that are interdisciplinary and allowing students to make a social impact, and funding targeted, culturally relevant programming along the entire academic trajectory from K-12 through career (Ross, 2020). Similar findings were also highlighted in a presentation from Nizhoni Chow-Garcia (2020).
Lastly, academic advisors can play a significant role in the success of students who are women of color, including increasing their sense of belonging (Museus and Ravello, 2010). There are opportunities for academic advisors to facilitate transitions for students at transition points to help women of color successfully navigate higher education systems—especially if they are attuned to the students’ needs. More studies are needed to study academic advising using an intersectional lens.
Create Supportive Inclusive Environments
While the number of women of color in academic programs in technology and computing is low, this is not due to lack of qualification or interest in pursuing careers in tech. Reducing obstacles in the academic environment fosters an environment where women of color succeed.
Cultivating Intentional Leadership
This report outlines numerous factors that present challenges for increasing diversity, equity, and inclusion in higher education; however, there are many opportunities to support and drive changes to institutional frameworks and cultures. Institutional leaders have an opportunity to shape the climate of the institutions they lead and to model the inclusivity they are trying to cultivate. During her presentation to the committee, Anna Branch, senior vice president for Equity at Rutgers University, provided questions that the leadership of higher education institutions can consider when evaluating organization culture and climate in order to better understand where exclusionary norms may be impacting women of color. These questions included:
- Who feels included or excluded?
- Who is thriving or not thriving?
- Who is not equitably represented within the institution?
- How do people treat each other?
- What is the historical context for this environment?
Understanding the answers to these questions can help leaders develop intentional strategies (e.g., crediting diversity work toward tenure and promotion or documenting committee service in annual reviews) to shift organizational
climate to more inclusive models that can increase the persistence of women of color (Branch, 2020).
It is also important to note that women of color are underrepresented in positions of leadership in higher education institutions. Programs such as HERS9 and ELATES at Drexel®,10 which focus on advancing women in higher education leadership, can serve as useful examples in tackling this underrepresentation. Research shows that increased diversity in organizational leadership can increase the sense of belonging and lead to more positive outcomes for women of color, and that organizations and institutions with women of color in the leadership may be more likely to support initiatives that are effective at increasing success for other women of color. However, as discussed earlier in the chapter, women of color of faculty often wear many institutional hats; these initiatives (e.g., networking and creating support networks and cohorts) should come with a caution to not overburden the few women of color who reach leadership roles leading these efforts.
Going Beyond Unconscious Bias Training
Often efforts to encourage the decision makers in higher education to be more culturally responsive and nurture an inclusive environment for women of color to succeed focus on unconscious bias training. While some initiatives can yield positive effects (Moss-Racusin et al., 2016; NRC, 2013), and improvements in awareness of diversity issues and reduced gender bias are heartening outcomes, they are, by themselves, insufficient. Bias trainings will “put folks on notice” of the significance of this topic and educate faculty of risk of misbehavior and benefits. However, effective diversity interventions must also encourage participation by students, faculty, and staff and increase participants’ readiness to engage in behaviors that promote gender parity and change the policies and procedures that establish the power structures that sustain these biases. An individual administrator may attend an ally camp, learn to be an effective mentor, identify macroaggressions, and/or explore the distinction between sponsorship and mentoring, yet these approaches fail to consider how power operates in situ.
Fostering Supportive Networks and Relationships
Formal and informal networking provides women of color with opportunities to build relationships, share information and experiences, learn about work and research opportunities, and receive guidance from peers and mentors. For example, a lack of senior female mentors can mean that junior faculty have less guidance on the unstated rules for promotion and tenure hindering their chances
10 For more information see https://drexel.edu/provost/initiatives/elates/about/ (accessed October 7, 2021).
of moving upward (NRC, 2013). In addition to helping students and faculty navigate the higher education environment, mentors and peers can help women of color recognize the assets they bring to the table—cultural capital, for example. These networks (such as student groups for women of color and campus chapters of professional organizations) and relationships (such as tenured faculty role models) allow women of color to build social capital and feel confidence in their competencies that can help them thrive and persist in tech and provide safe spaces where they feel supported (Carpenter, 2020; McMullen, 2020; Ong et al., 2020; NRC, 2013). Furthermore, the gender of a role model appears to be less important than the person’s ability to challenge stereotypes. The counter-stereotypical male role model can be just as helpful as a female role model in promoting women’s beliefs about success in STEM (Cheryan et al., 2011). Encouraging the adoption of counter-stereotypical signals among male faculty may be an actionable step to help foster women’s self-confidence in STEM (Charlesworth and Banaji, 2019). Ultimately, students and faculty from underrepresented groups who do not have access to these types of mentorship and/or guidance are more likely to feel excluded by peers in tech and other STEM environments, and ultimately leave the sciences (NASEM, 2019a; NRC, 2013).11
Beena Sukumaran, professor of civil and environmental engineering and vice president for research at Rowan University, provided the committee with numerous examples at its May 2020 workshop of the holistic approach that the College of Engineering at Rowan University is taking to improve diversity, equity, and inclusion (DEI) practices to help students thrive. Practices implemented as part of this approach included changing admissions standards (e.g., changing the evaluation process for transfer students, making the SAT optional for admission); increasing understanding of DEI among students, faculty, and administrators to create a culture of “collective intentionality” across departments; developing an “Advocates and Allies” program for incoming freshmen and transfer students to facilitate transition, retention, and graduation; transforming existing sophomore and junior level curriculum and providing faculty with guidance on how to design an inclusive curriculum; and working to strengthen students’ aspirations and identities as engineers by inviting speakers who are “role models of difference” and who have impacted society and policy in their professional careers (Sukumaran, 2020).
In 2013, testimony from academic women of color in computing, heard at a National Academies of Sciences, Engineering, and Medicine meeting, urged institutions to provide structures for mentoring and “provide resources for establishing virtual and in-person networks of academic women of color in computing to allow for the needed “sticking together” and “blending in”12 mentoring, the
11 Mentoring underrepresented students in STEMM: A Survey and Discussion: https://www.nap.edu/resource/25568/McGee%20-%20STEMM%20Mentoring%20Identity.pdf.
12 “Blending in” means the woman of color would develop a network that includes those with power, which are often white and/or male, while “sticking together” means the woman of color would create a network consisting of those similar to herself (NRC, 2013).
sharing of best practices, and for senior academic women of color in computing to be visible role models to junior academic women of color as well as women students of color” (NRC, 2013). The push for virtual communities in fostering networks for women of color is especially salient now given the remote environment created by COVID-19 where students and faculty are less physically tied to their campus environments. One example is the non-profit organization Rewriting the Code,13 a virtual community whose mission is to support college, graduate, and early career women in tech through intersectional communities, mentorship, industry experience, and educational resources. The organization has created subgroups that members may join, including for Black women, Latinx women, and international students, that have a stated goal to build a sense of inclusion and belonging by offering a place for sharing experiences and advice with a familiar community.
It is also worth reiterating that best practices can be developed from further study into why certain sub-disciplines in computing have been better at mentoring and supporting women, and whether strategies that attract women of color to these sub-disciplines could be applied to other technical sub-disciplines where women of color are less represented.
Cultivating Partnerships to Develop and Implement Best Practices
A number of speakers at the committee’s public workshops discussed the value of learning from peer institutions, colleagues, and communities that have created environments, programs, and practices that support the success of women of color in tech disciplines. Many minority-serving institutions have created strong computing programs that are graduating women of color at significantly higher rates than predominantly white institutions. Leadership at colleges and universities that are looking to improve outcomes can learn from other institutions that are succeeding to learn more about the policies, programs, and climate that foster success for women of color (Adams, 2020). Ashley Carpenter, assistant professor at Appalachian State University,14 also underscored the role that minority-serving institutions can play by sharing insights on how to support women of color. Carpenter encouraged higher education institutions to work to build supportive and safe communities of practice on campus, provide career guidance and professional development, and facilitate connections with potential mentors (Carpenter, 2020; Pinkston, 2020). HBCUs, for example, have shown disproportionate success in graduating African American students, particularly in the STEM fields, which has been attributed in part to their strong academic and social support networks and culturally responsive teaching approaches (NASEM,
14 Carpenter is listed in the workshop meeting agenda found in Appendix C with her previous affiliation as University Center for Exemplary Mentoring and Diversity Initiatives Program Coordinator at Massachusetts Institute of Technology.
2019a, 2019b). However, it is important to note that HBCUs are not devoid of structural barriers to the success of women of color in technology and computing. Given the low numbers of female faculty and women of color faculty in computing, campus and departmental climate issues can still persist.
Joan Reede, dean for diversity and community partnership at Harvard University Medical School, presented to the committee in February 2020 and underscored the importance of leadership in shaping organizational culture. Reede highlighted the importance of integrating diversity and inclusion into the mission and values of institutions and leadership that works to ensure that efforts to increase success of women of color are adequately resourced, consistent, and long enough for sustainable outcomes to be achieved. Reede pointed to examples of how Harvard Medical School is working within communities as well as within the institution to create opportunities for future student success—for example, by offering out-of-school programming to high school students during the academic year and summer and offering supplemental programming to high schools that do not have or cannot offer advanced placement coursework. For students already at Harvard, opportunities exist to participate in summer research programs, externships, and postdoctoral fellowships. Commitment as an institution to prioritizing continuity of programming to foster development along the academic trajectory is helping to create multiple points of access to opportunities for women of color.
Regarding partnerships between higher education and industry, presenters to the committee discussed the importance of symbiotic relationships. Higher education institutions have a unique opportunity in these partnerships not only to learn from industry and help to shape curriculum that can help students to succeed, but also to help equip industry with a better understanding of their students and the training and supports needed to help women of color successfully transition from higher education into the workforce (Gates, 2020; Washington, 2020).
Systems of accountability play a critical role in setting institutional goals for attracting and retaining women of color as students and faculty. Leadership at all institutional levels needs metrics in order to create strategic goals to strive for and to track, monitor, and evaluate whether those efforts have been successful (Adams, 2020; Reede, 2020). Adequate data collection and disaggregation plays a critical role in increasing transparency and informing evidence-based decisions. Kaye Husbands Fealing, chair and professor in the School of Public Policy at Georgia Tech, presented data from Leggon (2018), which highlights evaluation criteria for effective initiatives that increase participation and improve target group experiences and which can be used at the program and institutional level, initiatives such as increasing the diversity of the professoriate, developing culturally inclusive curricula, or increasing community engagement (Husbands Fealing, 2020) (Table 3-1).
|Program Level||Institutional Level|
SOURCE: Leggon (2018).
Widen Recruitment Efforts
Changing recruitment efforts to access a broader pool of candidates is a key strategy for addressing the low numerical representation of women in STEM fields. Increasing the number of women in these fields can attract future generations of girls and women to STEM. Broadening the pool of STEM talent would help address the shortage of qualified STEM educators, which, in turn, would introduce more students to and increase students’ excitement about STEM topics (Diekman et al., 2017).
Evidence suggests that in many STEM fields, disparities in the number of women in STEM tenure-track positions cannot be explained by a lack of qualified candidates. Even after earning a doctoral degree in a STEM field, more women than men opt out of applying for research-intensive academic positions. One study found that, across six scientific disciplines, the proportion of female degree holders was larger than the proportion of female applicants for research-intensive tenure-track positions (NRC, 2010). An analysis of approximately 3,000 faculty from 14 universities (Kaminski and Geisler, 2012) found that although men are more likely to be hired into faculty positions, women who are hired tend to be retained at similar rates to men. Therefore the authors of this analysis concluded that when women are hired they are likely to persist. Thus, the key stage to increase representation of women in academic positions in the sciences appears to be during recruitment (Diekman et al., 2017).
Juan Gilbert, professor and chair of the Computer and Information Science and Engineering Department at the University of Florida, provided insights to the committee in July 2020 on effective strategies for proactively increasing the recruitment of women of color at both the student and faculty level (Gilbert, 2020). Gilbert’s approach to proactive recruiting, which is grounded in research and
practice, emphasizes a number of methods for improving outcomes for women of color by leveraging innovative recruitment methods and implementing strategies to build support from leadership, foster community, provide guidance and mentorship, and promote professional development. In examining the characteristics of groups who were persisting both as students and faculty, Gilbert noted strategies for success and applied them to his own efforts to increase diversity in computing. A primary strategy is building communities of practice by recruiting in cohorts. In his own work, Gilbert had seen how peers with similar experiences were able to provide support and strategic guidance that helped members of their cohort to persist in the field. This was true both at the student and the faculty level. In cases where a single department does not have the resources to hire a cohort, higher education institutions can facilitate the coordination of hiring across departments or colleges to create cohorts of women of color who can support one another across the institution.
When cohort hiring is not possible at all, institutions can still leverage faculty of color to create peer support networks. Gilbert also highlighted the possibility of expanding the types and number of technology and computing disciplines to increase diversity. As previously discussed in this chapter, there may be more women of color in specific computing sub-disciplines. Institutions with the capacity to do so could consider adding new areas of research to their computing departments in order to expand opportunities to recruit more women of color into technology and computing fields (Gilbert, 2020).
Naturally, in the case of student admissions and hiring of faculty, the question arises of how to recruit cohorts of qualified women of color who, like all applicants, must compete for a limited number of openings. Although many institutions have undertaken efforts to diversify slates of candidates, personal networks and recommendations from non-diverse hiring committees or admissions panels often influence the demographic composition of the groups of candidates that are considered. Gilbert discussed one strategy to address this. “Application’s Quest,” a technology he has invented and patented uses artificial intelligence to holistically evaluate and compare applications with the goal of diversifying recommendations for admissions and hiring by reducing bias. This type of holistic evaluation broadens networks for recruitment and increases the diversity of qualified candidate pools from which to admit students or hire faculty. Gilbert has found that the results of using this technology is a slate of diverse candidates with equal achievement outcomes without a reduction in candidate achievement outcomes (Gilbert, 2020). Furthermore, research on the rates at which women of color faculty are offered tenure vs. non-tenure track positions, startup packages, and competitive salaries, among others recruitment factors, would help to build evidence on how best to recruit this group.
It is important to note that while surging enrollments in computer science can be seen as positive growth, they can also trigger institutions to put screens in place to manage enrollment demands which has the potential to negatively impact
diversity in tech disciplines. This reasoning has been used to explain the sudden drop in the participation of women in computing in the 1980s. It has been proposed that the practices put in place at many universities created an inhospitable and sometimes hostile climate that female students found to be uninviting and off-putting (CRA, 2015; NASEM, 2018b).
Leadership plays an important role in providing the financial and institutional support needed to implement these policies, demonstrating a willingness to shift the paradigm of how institutions of higher education adopt practices to increase the recruitment and retention of women of color, both as students and as faculty.
Capture the Experiences of Women of Color in Higher Education
An overarching finding in the committee’s examination of the research literature and evidence presented by experts at the committee’s series of public workshops is the need for data related to women of color that is disaggregated on a number of dimensions in order to better understand both their unique and shared experiences. Although the committee understands the challenges and privacy concerns that must be considered when using small datasets, there are a multitude of examples of other qualitative research methodologies that are valid alternatives to collect data on small sample sizes, such as case studies and autoethnographies. Course evaluations are another example: Institutions allow class evaluations no matter how small the sample size. Seminars with a handful of people are encouraged to be assessed. Granted, these data cannot be published, but they are often used to inform decisions on important issues such as promotion and tenure.
The same reasoning is not applied to data collection to understand the experiences of women of color in tech. However, defining and describing the problem need not be tethered to statistical significance and quantitative research—discovering the problem is more significant than replicability. In software testing one can prove the absence of bugs, but not correctness. The statement that the population of women of color in technology and computing fields is too small to study is an excuse to define a single case; however, examining qualitative data that provide more insights into the experiences of women of color can inform strategic efforts to change trajectories for student and faculty women of color using evidence-based practices, despite the limited sample size. For example, a recent paper from the Center for Inclusive Computing (CIC)15 used information from 22 site visits to identify the data to collect and questions to ask to help a university self-diagnose why equitable representation remains elusive. These questions may be helpful in demonstrating how higher education institutions can go beyond reporting on just diversity numbers to better understand structural
15 CIC is based at Northeastern University awards grants to colleges and universities to support the implementation of evidence-based approaches that increase the representation of women in computing. For more information see https://cic.khoury.northeastern.edu (accessed October 7, 2021).
barriers and systemic oppression and enable leaders to implement well-informed broadening participation strategies (Brodley et al., 2021).
The committee offers the following recommendations regarding the recruitment, retention, and advancement of women of color in higher education.
RECOMMENDATION 3-1. To foster continuous pathways for women of color in higher education, institutions at the departmental, college, and university levels should promote the collection of empirical qualitative and quantitative data that disaggregate the recruitment and graduation experiences of students, the recruitment and promotion and tenure trajectories of all faculty, and ascension to leadership positions for women of color.
These data should be used to inform the design and implementation of the following processes, but not limited to
- Culturally responsive review processes of promotion and tenure guidelines and academic review processes to ensure that the qualitative and quantitative research produced by women of color in tech is equally valued at the departmental, college, and university levels.
- Collection, analysis, and presentation of disaggregated data of tech departments and college environments to institutional leaders. Information regarding the individuals who constitute research teams, laboratories, faculty service committees, and doctoral committees could be used to determine whether one group is disproportionately receiving opportunities or assuming invisible labor. These data should also include the social categories (e.g., race/ethnicity, gender, socioeconomic status) of decision makers at departmental, college, and university levels in order to understand how power operates as an intersectional concept.
- A reward system sustained by computing and other technology-related departments and college environments which demonstrate ongoing levels of success recruiting, retaining, and maintaining an inclusive context for women of color in tech. Both disaggregated qualitative and quantitative could be used to present cases that illustrate effective strategies.
- Programs, policies, and practices that may be tailored to support the recruitment, retention, and advancement of different groups of women of color.
RECOMMENDATION 3-2. Institutions of higher education should collect and analyze disaggregated qualitative data to document the voices of women of color in tech and the narrated experiences of those who work with women of color that demonstrate how women of color fare in technology and computing courses as they navigate higher education at various levels.
To accomplish this, leaders in higher education, such as provosts, deans, and department heads, should use these data as the basis for their decisions for developing, sourcing, and evaluating initiatives for students and faculty who are women of color. Leaders in higher education should
- Regularly review and interpret these narrative data as barometers for measuring progress toward diversity, equity, and inclusion goals, and
- Identify and adopt best practices from institutions that have successfully recruited and retained women of color in tech.
RECOMMENDATION 3-3. Higher education leaders should widen recruitment efforts to identify women of color candidates to join their computer science, computer engineering, and other tech departments as students and faculty, with increased consideration of those from two-year community colleges and minority-serving institutions, and should develop retention strategies focused on supporting these students and faculty during transitions to their institutions.
Strategies should include the following:
- Developing partnerships with two-year community colleges and minority-serving institutions to identify and recruit tech students and graduates who are women of color.
- Increase access to higher education by integrating financial assistance programs with recruitment and retention strategies that target undergraduate and graduate students who are women of color.
- Providing increased social supports for incoming tech students and faculty who are women of color, such as orientations, professional development, career coaching, and peer mentoring. Individuals who provide this support should be required to maintain ongoing, regular training in culturally responsive education, racial awareness, and intersectionality.
ACE (American Council for Education). 2021. International Briefs for Higher Education Leaders: Women’s Representation in Higher Education Leadership Around the World. Vol 9. Washington, DC: American Council for Education.
Adams, S. 2020. Underrepresentation of Women of Color in Tech: Higher Education and Academia.” Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, Washington, DC, February 2020.
Adcock, T. 2014. Technology integration in American Indian education: An overview. Journal of American Indian Education 104-121.
Ashcraft, C., B. McLain, and E. Eger. 2016. Women in tech: The facts. Boulder, CO: National Center for Women and Information Technology. https://ncwit.org/resource/thefacts/.
Ashford, S. N. 2016. Our counter-life herstories: The experiences of African American women faculty in US computing education. Doctoral dissertation. University of South Florida.
Baker, T. 2020. Women of Color in Tech: A Focus on Native Americans. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, June 2020. https://www.nationalacademies.org/event/06-04-2020/addressing-the-underrepresentation-of-women-of-color-in-tech-workshop-4-day-2.
Begay, S. 2020. The Current State of STEM Education for American Indian and Alaska Native Communities. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, June 2020. https://www.nationalacademies.org/event/06-04-2020/addressing-the-underrepresentation-of-women-of-color-in-tech-workshop-4-day-2.
Bobb, K. 2020. Panel 1 Session. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, May 2020. https://www.nationalacademies.org/event/05-14-2020/addressing-the-underrepresentation-of-women-of-color-in-tech-workshop-day-1.
Branch, A. 2020. When and Where I Enter? Exits, Pathways, and Potholes for Black Women in Tech. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, April 2020. https://www.nationalacademies.org/event/04-08-2020/addressing-the-underrepresentation-of-women-of-color-in-tech-day-2.
Brodley, C. E., C. Gill, and S. Wynn. 2021. Diagnosing why Representation Remains Elusive at your University: Lessons Learned from the Center for Inclusive Computing’s Site Visits. Respect 2021 Conference. http://respect2021.stcbp.org/wp-content/uploads/2021/05/102_Experience-Report_02_paper_13.pdf.
Canning, E. A., K. Muenks, D. J. Green, and M. C. Murphy. 2019. STEM faculty who believe ability is fixed have larger racial achievement gaps and inspire less student motivation in their classes. Science Advances 5(2):eaau4734. https://advances.sciencemag.org/content/5/2/eaau4734.
Carpenter, A. 2020. Addressing the Underrepresentation of Women of Color in Technology. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, May 2020. https://www.nationalacademies.org/event/05-14-2020/addressing-the-underrepresentation-of-women-of-color-in-tech-workshop-day-1.
Cech, E. A., and M. Blair-Loy. 2010. Perceiving glass ceilings? Meritocratic versus structural explanations of gender inequality among women in science and technology. Social Problems 57(3):371-397.
Charlesworth, T. E. S., and M. R. Banaji. 2019. Gender in science, technology, engineering, and mathematics: Issues, causes, solutions. Journal of Neuroscience 39(37):7228-7243.
Chow-Garcia, 2020. N. Native American Women and Indigenous Models for Success. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, June 2020. https://www.nationalacademies.org/event/06-04-2020/addressing-the-underrepresentation-of-women-of-color-in-tech-workshop-4-day-2.
Clauset, A., S. Arbesman, and D. B. Larremore. 2015. Systematic inequality and hierarchy in faculty hiring networks. Science Advances 1(1):e1400005.
Cohoon, J. M. 2001. Toward improving female retention in the computer science major. Communications of the ACM 44(5):108-114.
Cohoon, J. M., S. Nigai, and J. Kaye. 2011. Gender and computing conference papers. Communications of the ACM 54(8):72-80. https://doi.org/10.1145/1978542.1978561.
Collins, P. H. 2019. Intersectionality as critical social theory. Durham, NC: Duke University Press.
Corbett, C., and C. Hill. 2015. Solving the equation: The variables for women’s success in engineering and computing. Washington, DC: American Association of University Women. https://www.aauw.org/app/uploads/2020/03/Solving-the-Equation-report-nsa.pdf.
CRA (Computing Research Association). 2015. Expanding the Pipeline: Booming Enrollments – What is the Impact? Computing Research News 27(5). https://cra.org/crn/wp-content/uploads/sites/7/2015/07/CRN_May_2015.pdf.
Crenshaw, K. 1991. Mapping the margins: Identity politics, intersectionality, and violence against women. Stanford Law Review 43(6):1241-1299.
Daily, S., W. Eugene, C. Shelton, and J. Thomas. 2020, August 27. Trends in Bachelors among Women of Color in Computing. Women of Color in Computing Conference, Virtual.
DeerInWater, K. 2020. Women of Color in Tech: A Focus on Native Americans in Computing. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, June 2020. https://www.nationalacademies.org/event/06-04-2020/addressing-the-underrepresentation-of-women-of-color-in-tech-workshop-4-day-2.
Delgado-Olson, A. 2020. Addressing Underrepresentation of Women of Color in Tech: Perspectives of Native American Women in Computing. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, June 2020. https://www.nationalacademies.org/event/06-04-2020/addressing-the-underrepresentationof-women-of-color-in-tech-workshop-4-day-2.
Denner, J. 2009. The role of the family in the IT career goals of middle school Latinas. AMCIS 2009 Proceedings, p. 334.
Denner, J. 2011. What predicts middle school girls’ interest in computing? International Journal of Gender, Science and Technology 3(1):54-69.
Diekman, A. B., E. S. Weisgram, and A. L. Belanger. 2015. New routes to recruiting and retaining women in STEM: Policy implications of a communal goal congruity perspective. Social Issues and Policy Review 9:52-88. http://doi.org/10.1111/sipr.12010.
Diekman, A. B., M. Steinberg, E. R. Brown, A. L. Belanger, and E. K. Clark. 2017. A goal congruity model of role entry, engagement, and exit: Understanding communal goal processes in STEM gender gaps. Personality and Social Psychology Review 21(2):142-175.
Dotson, K. 2011. Tracking epistemic violence, tracking practices of silencing. Hypatia 26(2):236-257.
Dotson, K. 2012. A cautionary tale: On limiting epistemic oppression. Frontiers: A Journal of Women Studies 33(1):24-47.
Dotson, K. 2014. Conceptualizing epistemic oppression. Social Epistemology 28(2):115-138.
Funk, C., and K. Parker. 2018. Women and Men in STEM Often at Odds over Workplace Equity. Pew Research Center.
Gates, A. 2020. Underrepresentation of Women of Color in Tech: Higher Education and Academia. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, Washington, DC, February 2020.
Gilbert, J. E. Addressing the Underrepresentation of Women of Color in Tech. Presentation made to the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, July 2020.
Glass, J. L., S. Sassler, Y. Levitte, and K. M. Michelmore. 2013. What’s so special about STEM? A comparison of women’s retention in STEM and professional occupations. Social Forces 92(2):723-756.
Harackiewicz, J. M., C. S. Rozek, C. S. Hulleman, and J. S. Hyde. 2012. Helping parents to motivate adolescents in mathematics and science: An experimental test of a utility-value intervention. Psychological Science 23(8):899-906.
Hill, C., K. Miller, K. Benson, and G. Handley. 2016. Barriers and Bias: The Status of Women in Leadership. American Association of University Women.
Hill, R. 2020. Retention of Women of Color Students in Tech: An MSI Perspective. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, April 2020. https://www.nationalacademies.org/event/04-07-2020/addressing-the-underrepresentation-of-women-of-color-in-tech-day-1.
Holloway, B. M., T. Reed, P. K. Imbrie, and K. Reid. 2014. Research-informed policy change: A retrospective on engineering admissions. Journal of Engineering Education 103(2):274-301.
Hunt, D. I., and B. Nicodemus. 2014. Gatekeeping in ASL-English interpreter education programs: Assessing the suitability of students for professional practice. In D. J. Hunt and S. Hafer (Eds.) Proceedings from CIT 2014: Our roots: The essence of our future. Pp. 44-60. Portland, OR: Conference of Interpreter Trainers.
Hunt, J. 2010. Why do women leave science and engineering? NBER working paper no. 15853. Cambridge, MA: National Bureau of Economic Research.
Hurtado, S., D.F. Carter, and A. Spuler. 1996. Latino student transition to college: Assessing difficulties and factors in successful college adjustment. Research in Higher Education 37(2):135-157.
Hurtado, S., O. S. Cerna, J. C. Chang, V. B. Saenz, L. R. Lopez, C. Mosqueda, L. Oseguera, M. J. Chang, and W. S. Korn. 2006. Aspiring scientists: Characteristics of college freshmen interested in the biomedical and behavioral sciences. Los Angeles, CA: Higher Education Research Institute. https://heri.ucla.edu/PDFs/NIH/Summer%20Report.PDF.
Hurtado, S., J. C. Han, V. B. Sáenz, L. L. Espinosa, N. L. Cabrera, and O. S. Cerna. 2007. Predicting transition and adjustment to college: Biomedical and behavioral science aspirants’ and minority students’ first year of college. Research in Higher Education 48(7):841-887.
Husbands Fealing, K. 2020. What Can Leadership Do? Effective practices within organizations to retain and advance women of color in STEM. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, April 2020. https://www.nationalacademies.org/event/04-08-2020/addressing-the-underrepresentation-of-women-of-color-in-tech-day-2.
Jaschik, S. 2010. Different paths to full professor. Inside Higher Ed. https://www.insidehighered.com/news/2010/03/05/different-paths-full-professor.
Jaschik, S. 2016. Unintended Help for Male Professors. Inside Higher Ed. https://www.insidehighered.com/news/2016/06/27/stopping-tenure-clock-may-help-male-professors-more-female-study-finds.
Kaminski, D., and C. Geisler .2012. Survival analysis of faculty retention in science and engineering by gender. Science 335:864-866. doi:10.1126/science.1214844.
Kang, S. K., and S. Kaplan. 2019. Working toward gender diversity and inclusion in medicine: Myths and solutions. The Lancet 393(10171):579-586.
Kidd, I. J., and H. Carel. 2017. Epistemic injustice and illness. Journal of Applied Philosophy 34(2):271-190.
Kim, T., D. Peck, and B. Gee. 2018. Race, Gender & the Double Glass Ceiling: An Analysis of EEOC National Workforce Data. The Ascend Foundation.
Leggon, C. B. 2018. Reflections on broadening participation in STEM: What do we know? What do we need to know? Where Do We Go From Here? American Behavioral Scientist 62(5):719-726.
Malcom, L. E., and S. M. Malcom. 2011. The double bind: The next generation. Harvard Educational Review 81(2):162-172.
Malcom, S. M., P. Q. Hall, and J. W. Brown. 1976. The double bind: The price of being a minority woman in science. Publication 76-R-3. Washington, DC: American Association for the Advancement of Science. http://web.mit.edu/cortiz/www/Diversity/1975-DoubleBind.pdf.
McAlear, F., A. Scott, K. Scott, and S. Weiss. 2018. Women of color in computing. Data brief.
McCullough, T. 2016. The myth women in tech need to stop believing. Forbes, February 6. https://fortune.com/2016/02/06/myth-women-tech/.
McGee, E. O. 2020. Interrogating structural racism in STEM higher education. Educational Researcher 49(9):633-644.
McGee, E. O. 2021. The agony of stereotyping holds Black women back. Nature Human Behaviour, 5(1), 3.
McMullen, K. 2020. Increasing the Representation of Women of Color in Technology. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, Washington, DC, February 2020.
Metoyer, R., M. A. Pérez-Quiñones, A. Bazerianos, and J. Woodring. 2019. Retention. In Diversity in visualization, edited by R. Metoyer and K. Gaiter. San Rafael, CA: Morgan and Claypool Publishers. Pp. 39-52. https://www.morganclaypool.com/doi/10.2200/S00894ED1V01Y201901VIS010.
Moss-Racusin, C. A., J. F. Dovidio, V. L. Brescoll, M. J. Graham, and J. Handelsman. 2012. Science faculty’s subtle gender biases favor male students. Proceedings of the National Academy of Sciences of the United States of America 109(41):16474-16479.
Moss-Racusin, C. A., J. van der Toorn, J. F. Dovidio, V. L. Brescoll, M. J. Graham, and J. Handelsman. 2016. A “scientific diversity” intervention to reduce gender bias in a sample of life scientists. CBE—Life Sciences Education 15(3):ar29.
Museus, S. D., and J. N. Ravello. 2010. Characteristics of academic advising that contribute to racial and ethnic minority student success at predominantly white institutions. NACADA Journal 30(1):47-58.
NAS, NAE, and IOM (National Academy of Sciences, National Academy of Engineering, and Institute of Medicine). 2011. Expanding underrepresented minority participation: America’s science and technology talent at the crossroads. Washington, DC: The National Academies Press. https://doi.org/10.17226/12984.
NASEM (National Academies of Sciences, Engineering, and Medicine). 2013. Seeking solutions: Maximizing American talent by advancing women of color in academia. Washington, DC: The National Academies Press.
NASEM. 2016. Barriers and opportunities for 2-year and 4-year STEM degrees: Systemic change to support students’ diverse pathways. Washington, DC: The National Academies Press. https://doi.org/10.17226/21739.
NASEM. 2018a. Sexual harassment of women: Climate, culture, and consequences in academic sciences, engineering, and medicine. Washington, DC: The National Academies Press. https://doi.org/10.17226/24994.
NASEM. 2018b. Assessing and responding to the growth of computer science undergraduate enrollments. Washington, DC: The National Academies Press. doi: 10.17226/24926.
NASEM. 2019a. The science of effective mentorship in STEMM. Washington, DC: The National Academies Press. https://doi.org/10.17226/25568.
NASEM. 2019b. Minority serving institutions: America’s underutilized resource for strengthening the STEM workforce. Washington, DC: The National Academies Press. https://doi.org/10.17226/25257.
NASEM. 2020. Promising practices for addressing the underrepresentation of women in science, engineering, and medicine: Opening doors. Washington, DC: The National Academies Press. https://doi.org/10.17226/25585.
NCES (National Center for Education Statistics). 2017. Beginning college students who change their majors within 3 years of enrollment. Data Point, NCES 2018-43. Washington, DC: Institute of Education Sciences, Department of Education. https://nces.ed.gov/pubs2018/2018434.pdf.
NCES. 2020. Web Tables. A 2017 follow-up: Six-year persistence and attainment at first institution for 2011-12 first-time postsecondary students. Washington, DC: Institute of Education Sciences, Department of Education. https://nces.ed.gov/pubs2020/2020237.pdf.
NEA (National Education Council). 2021. Beyond the Bubble: Americans Want Change on High Stakes Assessments. National Education Council.
NRC (National Research Council). 2010. Gender differences in critical transitions in the careers of science, engineering, and mathematics faculty. Washington, DC: The National Academies Press. doi:10.17226/12062
NRC. 2013. Seeking solutions: Maximizing American talent by advancing women of color in academia: Summary of a conference. Appendix A-2: Women of color among STEM faculty: Experiences in academia. Washington, DC: The National Academies Press. https://doi.org/10.17226/18556.
Ong, M., N. Jaumot-Pascual, and L. T. Ko. 2020. Research literature on women of color in undergraduate engineering education: A systematic thematic synthesis. Journal of Engineering Education 109(3):581-615.
Pawley, A. 2020. Learning from Small Numbers: Theory Informed Insights on Gender and Race. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, June 2020. https://www.nationalacademies.org/event/06-04-2020/addressing-the-underrepresentation-of-women-of-color-in-tech-workshop-4-day-2.
Peck, D. 2020. An Analysis of the Intersection of Race and Gender in San Francisco Bay Area Technology Workforce 2007-2015. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, May 2020.
Pinkston, T. 2020. The Parity Objective: Developing a ‘Framework’ Suite of Best Practices Towards Achieving It. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, May 2020. https://www.nationalacademies.org/event/05-14-2020/addressing-the-underrepresentation-of-women-of-color-in-tech-workshop-day-1.
Reede, J. 2020. Moving Beyond a Seat at the Table: Underrepresentation of Women of Color in Higher Education and Academia. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, Washington, DC, February 2020.
Reyes, M. E. 2011. Unique challenges for women of color in STEM transferring from community colleges to universities. Harvard Educational Review 81(2):241-263.
Riegle-Crumb, C., B. King, and Y. Irizarry. 2019. Does STEM stand out? Examining racial/ethnic gaps in persistence across postsecondary fields. Educational Researcher 48(3):133-144.
Robinson, A. 2015. The attitudes of African American middle school girls toward computer science: Influences of home, school, and technology use. PhD Dissertation. Virginia Tech.
Robinson, A., and M. A. Pérez-Quiñones. 2014. Underrepresented middle school girls: On the path to computer science through paper prototyping. Proceedings of the 45th ACM Technical Symposium on Computer Science Education, pp. 97-102. https://doi.org/10.1145/2538862.2538951.
Ross, M. 2020. Retention of Women of Color Students in Tech: An MSI Perspective. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, April 2020. https://www.nationalacademies.org/event/04-07-2020/addressing-the-underrepresentation-of-women-of-color-in-tech-day-1.
Rosser, V. J. 2004. Faculty member’ intentions to leave: A national study on their worklife and satisfaction. Research in Higher Education 45(3):285.
Ryan, M. K., Haslam, S. A., Morgenroth, T., Rink, F., Stoker, J., and K. Peters. 2016. Getting on top of the glass cliff: Reviewing a decade of evidence, explanations, and impact. The Leadership Quarterly 27(3):446-455.
Settles, I. H., M. K. Jones, N. T. Buchanan, and K. Dotson. 2020. Epistemic exclusion: Scholar(ly) devaluation that marginalizes faculty of color. Journal of Diversity in Higher Education. https://doi.org/10.1037/dhe0000174.
Steele, C. M. 1997. A threat in the air: How stereotypes shape intellectual identity and performance. American Psychologist 52(6):613.
Su, X., J. Johnson, and B. Bozeman. (2015). Gender diversity strategy in academic departments: Exploring organizational determinants. Higher Education 69(5):839-858.
Sukumaran, B. 2020. Revolutionizing Engineering and Technology Diversity with a focus on Undergraduate Education. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, May 2020. https://www.nationalacademies.org/event/05-14-2020/addressing-the-underrepresentation-of-women-of-color-in-tech-workshop-day-1.
Thompson, M., and D. Sekaquaptewa. 2002. When being different is detrimental: Solo status and the performance of women and racial minorities. Analyses of Social Issues and Public Policy 2(1):183-203.
Tuck, E., and M. McKenzie. 2015. Place in research: Theory, methodology, and methods. New York: Routledge.
Turner, C. S. V. 2002. Women of color in academe: Living with multiple marginality. Journal of Higher Education 73(1):74-93.
Varma, R., and V. Galindo-Sanchez. 2006. Native American women in computing. In Encyclopedia of gender and information technology (pp. 914-919). IGI Global.
Walton, G. M. 2020. Questions of Belonging: Arise from Socio-Cultural Contexts Risk Becoming Self-Fulfilling But Can Be Interrupted. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, June 2020. https://www.nationalacademies.org/event/06-04-2020/addressing-the-underrepresentationof-women-of-color-in-tech-workshop-4-day-2.
Wasburn, M. H. 2004. Appeasing women faculty: A case study in gender politics. Advancing Women in Leadership Journal 15.
Washington, G. 2020. Retention of Women of Color Students in Tech: An MSI Perspective. Presentation made at the public workshop of the Committee on Addressing the Underrepresentation of Women of Color in Tech, virtual, April 2020. https://www.nationalacademies.org/event/04-07-2020/addressing-the-underrepresentation-of-women-of-color-in-tech-day-1.
Whitecraft, M. A., and W. M. Williams. 2010. Why aren’t more women in computer science. In Making software: What really works, and why we believe it. Pp. 221-238. O’Reilly Media, Inc.
Williams, J. C. 2014. Double jeopardy? An empirical study with implications for the debates over implicit bias and intersectionality. Harvard Journal of Law & Gender, 37, 185.
Wofford, A. M. 2021. Modeling the pathways to self-confidence for graduate school in computing. Research in Higher Education 62(3):359-391.
This page intentionally left blank.