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Black women remain severely underrepresented in computing despite ongoing efforts to diversify the field. Given that Black women exist at the intersection of both racial and gendered identities, tailored approaches are necessary to address the unique barriers Black women face in computing. However, it is difficult to quantitatively evaluate the efficacy of interventions designed to retain Black women in computing, since samples of computing students typically contain too few Black women for robust statistical analysis. Using about a decade of student survey responses from an National Science Foundation–funded Broadening Participation in Computing alliance, we use regression analyses to quantitatively examine the connection between different types of interventions and Black women’s intentions to persist in computing and how this compares to other students (specifically, Black men, white women, and white men). This comparison allows us to quantitatively explore how Black women’s needs are both distinct from—and similar to—other students. We find that career awareness and faculty mentorship are the two interventions that have a statistically significant, positive correlation with Black women’s computing persistence intentions. No evidence was found that increasing confidence or developing skills/knowledge was correlated with Black women’s computing persistence intentions, which we posit is because Black women must be highly committed and confident to pursue computing in college. Last, our results suggest that many efforts to increase the number of women in computing are focused on meeting the needs of white women. While further analyses are needed to fully understand the impact of complex intersectional identities in computing, this large-scale quantitative analysis contributes to our understanding of the nuances of Black women’s needs in computing.
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Increasing Women's Persistence in Computer Science by Decreasing Gendered Self-Assessments of Computing Ability
the dearth of women in computing by causing women to experience gender bias. These gender stereotypes are doubly disadvantaging to women because they create gender differences in self-assessments of computing ability, decreasing the likelihood that women will persist in Computer Science (CS). This is because students need to believe they have sufficient ability in a field in order to pursue it as a career. Building on decades of Sociological theory, we hypothesized that increasing top-performing women’s self-assessments of computing ability would increase those women’s intentions to persist in computing. To test this hypothesis, we conducted a field experiment in a CS1 class in which the top 50% of students were given additional performance feedback from their instructor via email. The intervention increased these women’s and men’s self-assessed CS ability but only increased the women’s CS persistence intentions. In sum, sending a single email increased top-performing women’s intentions to persist in CS by 18%. A mediation analysis found evidence for the proposed causal path; namely, that the intervention increased the women’s self-assessments of computing ability, which then increased their intentions to persist in computing. This research furthers our knowledge of the processes around self-assessments of ability and career choice that contribute to the dearth of women in CS. It also provides evidence for a lightweight intervention that may increase the number of women in computing, as prior research finds that intentions to persist are highly predictive of actual persistence in STEM fields.
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- Award ID(s):
- 2021330
- PAR ID:
- 10258046
- Date Published:
- Journal Name:
- ITiCSE: Innovation and Technology in Computer Science Education
- Volume:
- 1
- Page Range / eLocation ID:
- 464-470
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript
- Conference Paper:
- https://doi.org/https://doi.org/10.1145/3430665.3456374
