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• W4289731625 abstract "Are women less likely to persist in computer science because of gender differences in self-assessed computing ability? And why do gender differences exist in self-assessments among women and men who earn the same grades? We use a mixed-method research design to answer these questions, utilizing both quantitative survey data (n = 764) and qualitative interview data (n = 59) from students in introductory computing courses at a large U.S. state university. Quantitatively, we find that women self-assess their computing ability significantly lower than men who earn the same grades, and that these lower self-assessments reduce the likelihood that women enroll in future CS courses (relative to men who earn equivalent grades). Qualitatively, we explore how women and men perceive their own computing ability to understand why women self-assess their ability lower than men. Our interviews revealed that women were much less likely than men to make favorable comparative judgements about their ability relative to their classmates. Women also had higher personal performance standards than men. Lastly, women were more likely than men to experience disrespectful treatment, with an undertone of presumed incompetence, from their TAs and classmates. In sum, this research furthers our understanding of why gender differences exist in self-assessments of computing ability and how these differences can contribute to gender disparities in computing persistence. It also draws attention to the importance of feedback in computing courses and suggests that improving course feedback may reduce gender disparities in computing." @default.
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• W4289731625 date "2022-08-03" @default.
• W4289731625 modified "2023-09-23" @default.
• W4289731625 title "Gender, Self-Assessment, and Persistence in Computing: How gender differences in self-assessed ability reduce women’s persistence in computer science" @default.
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• W4289731625 doi "https://doi.org/10.1145/3501385.3543963" @default.
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