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The Status of Women of Color in Computer Science

Addressing the challenges of increasing the number of women of color in computing and ensuring their success.
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  1. Introduction
  2. The "Inside the Double Bind" Study
  3. Policy Implications and Future Directions for Research
  4. References
  5. Author
  6. Footnotes
  7. Figures
  8. Tables
Spelman College women computer science students
The Spelman College Spelbots provide hands-on robotics education and research for women computer science students by competing in U.S. and International RoboCup 4-Legged competitions.

To remain economically and globally competitive, the U.S. needs to increase its advanced domestic science and technology work force.1 As U.S. colleges are already majority female and are increasingly enrolling more minority students, women of color represent a growing potential source of domestic talent to meet the needs of the country. Thus, it is in the interest of all of us to ensure that women of color are well represented in science, technology, engineering, and mathematics (STEM) fields.

There is also the social justice argument for promoting women of color in STEM. The history of exclusion in science and technology fields and in the U.S. at large has resulted in an unfortunate outcome of underrepresentation that should be actively addressed. It is important to continue to recognize and challenge sexism and racism that remains pervasive—though perhaps more subtle than 30 years ago—and which is experienced by women of color in multiplicative ways. Moreover, women of color are often the breadwinners, main supporters of children, and community leaders, so their successes and failures in a well-paid and well-respected field such as computer science could have significant impacts on more general community issues.

As the accompanying table shows, the current outlook presents challenges for addressing the need of attracting and retaining women, especially women of color, into computing. Among U.S. citizens and permanent residents receiving 2008 degrees in the computer sciences, women of color fared worse compared to their White female counterparts at both the bachelor’s and Ph.D. levels. Within every racial group, men outearned women in terms of CS degrees awarded, with two exceptions: Blacks at the Ph.D. level, where both men and women both earned 12 degrees, and American Indian/Alaska Natives at the Ph.D. level, where men and women both earned no degrees.2

Of serious concern is the decline of Hispanic women earning Ph.D.s in CS. An examination of doctorate attainment over the past decade reveals that their numbers peaked in 2004 at nine Ph.D.s but have declined since, and they received only two of the CS Ph.D.s awarded in 2008. Of continuing disquiet is the status of American Indian/Alaska Native women in CS. Between 2000 and 2008 this group has only earned a total of seven Ph.D.s.2

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The “Inside the Double Bind” Study

Policies aimed at increasing women of color in computing should be based on empirical research on this population. Unfortunately, not much research exists. While there have been many studies since 1970 on the experiences of women in STEM and on those of minorities in STEM, the unique experiences of women of color, who encounter the challenges of race and gender simultaneously, are often excluded from the research agenda. Studies that do exist have been difficult to find because they are scattered throughout journals, book chapters, reports, and unpublished dissertations.

The NSF-funded project, “Inside the Double Bind: A Synthesis of Empirical Literature on Women of Color in STEM,” aimed to gather, analyze, and synthesize empirical research that had been produced between 1970 and 2008. The project team, co-led by Gary Orfield (UCLA) and myself, identified 116 works of empirical research literature produced since 1970 on women of color in STEM higher education and careers. The resulting “Inside the Double Bind” synthesis3,4 highlights general empirical findings and identifies research gaps in STEM. Specific findings on women of color in computer science are summarized here.

We identified 19 sources on women of color in computer science—not many at all, considering that our search covered nearly 40 years’ worth of literature. Studies in computing are relatively new: 16 of the works have been produced since 2002. Most of the literature focuses on higher education, and the research covers an array of topics, including the “digital divide” that separates girls and women of color from others, social challenges for women of color students, the roles of minority-serving institutions, and nontraditional pathways to CS degrees. The reader should be forewarned that our searches were thorough but not exhaustive, and with only 19 identified works, there are many gaps and incomplete descriptions about the status and experiences of women of color in computing. Some policy implications and future directions for research in this area are discussed later in this column.

Preparation and the “digital divide.” Several research studies pointed to the “digital divide” that leaves girls and women of color underexposed to technology and basic computer skills in their upbringing. The underexposure, researchers claim, may be due to a number of factors, including socioeconomic inequalities and gendered beliefs that females lack potential for technical fluency. This divide can put them at a disadvantage compared to their White and male peers in knowledge and in comfort in dealing with computers, thus hindering their entry and retention into computer science fields.

Social challenges for women of color in CS. Fields that are heavily White and male, such as physics, engineering, and computer science, pose some unique social challenges for women of color students. At predominantly White institutions (PWIs), they often experience being the only woman or minority—or, at most, one of a few—in their class or laboratory. Research suggests that in CS, their sense of isolation is often heightened by what they perceive as an unwelcoming environment and others’ lowered expectations of them. In my current study, a comment by a young professional woman of color who had majored in computer science provides a vivid illustration of this experience: In my computer science class, a lot of the projects were group [work] and so I found two… [minority] groupmates, who were heaven-sent. And we stuck by each other and actually, after we found each other, planned all of our schedules in sync with each other, so we took the same classes in order to get through the undergraduate experience together. Because a part of being a minority is that people don’t want to work with you. They don’t look at you and sense that you are a smart person they want to work with. So finding people who believe in you and you believe in, and then sticking together, was really important. (“Serena,” in Ong and Hodari.5)

This woman’s strategy of working with other minorities helped her to persist through her undergraduate program, but sadly, the cumulative social challenges she encountered ultimately deterred her from pursuing computer science in graduate school or as a career. This story of attrition is far too common. Fortunately, though, an increasing number of organizations and CS departments are putting tremendous amounts of time and energy to establish more welcoming social environments for all of their members.

Family and school balance. There is a serious dearth of research about family-school and family-work balance for women of color in STEM and in CS, but what we’ve learned so far is worth noting. The few studies we identified on the topic reveal that a common challenge for women of color students involves tensions between their demanding CS programs and external pressures to manage and participate in the family structure and to contribute to the family income. Exacerbating the issue are rigid course schedules, faculty who do not understand the cultural expectations upon these students, family members who do not understand the time commitment required to pursue a computer science degree, and lack of job opportunities for students in CS-related fields.

The role of minority-serving institutions. Minority-serving institutions (MSIs), including Historically Black Colleges and Universities (HBCUs), Hispanic-serving institutions (HSIs), and Tribal Colleges and Universities (TCUs), have a strong history of producing a disproportionate number of minority female STEM majors who continue on to Ph.D.s. The field of computer science is no exception. While more research is needed in this area, especially for HSIs and TCUs, existing research attributes the persistence of women of color in CS to MSIs’ nurturing environments, faculty who believe in their students, a collaborative peer culture, and special programs such as summer research experiences. Researchers also credit the persistence of women of color in computing to the personal drive of the women themselves.


Future research needs to address educational and career choices and career trajectories of women of color.


Nontraditional pathways. More than their White female counterparts, women of color take nontraditional paths to computer science. Many come to CS education later in their lives, long after leaving school with non-CS degrees or no degree at all, and perhaps after starting a family or working full-time. Many begin their computer science education in community colleges, and while some directly transfer afterward to a four-year institution, others periodically “stop out,” taking months or years off before returning to study. Studies reveal that persistence through programs by nontraditional women of color result from a combination of individuals’ drive for economic and academic success and programs that accommodate and encourage them. More research is needed in this area to address profiles of nontraditional students, academic programs and activities that attract and retain them, and types of degrees and employment they gain.

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Policy Implications and Future Directions for Research

The existing research indicates some potential, immediate steps for institutional policy and action. To help women of color traverse the digital divide and feel they belong in CS, institutions might offer real-world opportunities to gain computer expertise—and thereby a sense of empowerment—in the classroom. They could also provide meaningful and well-paid CS-related employment, such as research and tutoring opportunities, and develop and sustain a supportive learning community that includes women of color and other marginalized students. Practices of organizations and departments that have already made great strides in this area should be documented, widely disseminated, and adapted by others. Further, institutions should explore ways to adapt some practices of MSIs and programs that successfully serve nontraditional students in computer science. To address tensions between family and academic demands, departments might offer more flexibility in their programs, including offering some online courses and scheduling courses more than once a year; allow for a fully integrated, part-time academic track; and increase the number of CS research stipends and work opportunities. Finally, high-level recognition of the many accomplishments of women of color in computing should be given, so that these women may serve as role models to girls and young women of color who may follow in their footsteps.

New research will reveal effective ways to bring more women of color into the field. Future studies should include women in all racial/ethnic groups, but especially for those groups about whom information is scarce: Latinas/Hispanics, American Indians/Alaska Natives, and Asian Americans/Pacific Islanders. Future research needs to address educational and career choices and career trajectories of women of color, and more should be learned about the paths of nontraditional students into computing careers. Many more studies on women of color in computing regarding balance between family and school or work should be conducted. Future research should highlight elements of success for women of color in CS, rather than dwelling on challenges. For example, at the institutional, departmental, and programmatic levels, effective recruitment and retention practices at MSIs, predominantly White institutions, and community colleges need to be better studied so that others may learn from them. Addressing these knowledge gaps will point us to practical solutions to increase the numbers of women of color in computing and to ensure their success.

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Figures

UF1 Figure. The Spelman College Spelbots provide hands-on robotics education and research for women computer science students by competing in U.S. and International RoboCup 4-Legged competitions.

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Tables

UT1 Table. Computer sciences degrees awarded to U.S. citizens and permanent residents (2008).

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    1. National Academies. Rising Above the Gathering Storm, Revisited: Rapidly Approaching Category 5. National Academies Press, Washington, D.C., 2010.

    2. National Science Foundation, National Center for Science and Engineering Statistics. Women, Minorities, and Persons with Disabilities in Science and Engineering: 2011, tables 5-7 and 7-7, NSF 11-309. Arlington, VA, 2011; http://www.nsf.gov/statistics/wmpd/.

    3. Ong, M., Wright, C., Espinosa, L., and orfield, G. Inside the Double Bind: A Synthesis of Empirical Research on Women of Color in Science, Technology, Engineering, and Mathematics. White Paper presented to the National Science Foundation, Washington, D.C. (NSF/REESE Project DRL-0635577), March 31, 2010; http://www.terc.edu/work/1513.html.

    4. Ong, M., Wright, C., Espinosa, E., and Orfield, G. Inside the double bind: A synthesis of empirical research on undergraduate and graduate women of color in science, technology, engineering, and mathematics. Harvard Educational Review 81, 2 (Summer 2011), 172–208.

    5. Ong, M. and Hodari, A.K. Beyond the double bind: Women of color in STEM. NSF/REESE research project funded by NSF-DRL 0909762, 2009-2012.

    The author wishes to thank the IDB Project Team, especially Christine Bath, and Richard Ladner and an anonymous reviewer. This work was supported by NSF-DRL grants # 0635577and 0909762, and NSF-REU award # 0635577. Any opinions, findings, conclusions, or recommendations are solely those of the author.

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