A recent recruitment campaign for a tech company featuring female platform engineer Isis Wenger sparked a barrage of scrutiny on social media concerning whether or not Wenger was actually an engineer – this outcry resulted in the #ILookLikeAnEngineer movement on Twitter. A few months earlier, esteemed Nobel laureate and biochemist Tim Hunt, made a public statement that the “trouble with girls” who work in research laboratories is that they “fall in love with you and when you criticize them, they cry”. These are but two recent examples that have received significant media attention, reflecting a pervasive cultural belief system that questions women’s aptitude and “fit” in technical fields. One troubling ramification of these cultural stereotypes is that they can make their way into women’s personal belief system, which may damage their beliefs about their own ability and “fit” in technical fields.
In the current work, we assessed the impact of women’s negative gender stereotypic beliefs on their own self-conceptions in computing that are linked with academic persistence and success: self-efficacy, sense of belonging, and identification with computing. Self-efficacy refers to beliefs about one’s ability to plan for and execute steps necessary for future success , and is know to promote academic performance and motivation . A sense of belonging is defined as the subjective feeling of fitting in and being included as a valued and legitimate member of an academic discipline, and is a predictor of academic persistence and achievement . Finally, domain identification refers to one’s self-definition, or the degree to which one feels that their academic pursuits are an important element of “who they are”. Domain identification is important because when it is high, positive outcomes are self-relevant and rewarding, thereby motivating achievement .
We found that women computing majors who personally endorse negative gender stereotypes about women’s ability in computing reported weaker computing self-efficacy, a lower sense of belonging in computing, and less identification with computing. We then examined whether common collaborative learning methods in computing (pair programing; supplemental instruction) can erase the negative relationship between women’s endorsement of negative gender stereotypes and their self-conceptions. Indeed, longitudinal survey data indicated that prior participation in collaborative learning activities cancelled out the negative impact of gender stereotype endorsement on women’s self-conceptions in computing. These findings suggest that although women are at risk of leaving technical fields when they believe cultural stereotypes about women in technical fields, collaborative learning activities may increase the likelihood that these “at risk” women will instead persist and thrive.
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