Increasing Women's Persistence in Computer Science by Decreasing Gendered Self-Assessments of Computing Ability

Gender stereotypes about women's computing ability contribute to 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.