title: Cultural stereotypes as gatekeepers: increasing girls' interest in computer science and engineering by diversifying stereotypes.
abstract: Despite having made significant inroads into many traditionally male-dominated fields (e.g., biology, chemistry), women continue to be underrepresented in computer science and engineering. We propose that students' stereotypes about the culture of these fields-including the kind of people, the work involved, and the values of the field-steer girls away from choosing to enter them. Computer science and engineering are stereotyped in modern American culture as male-oriented fields that involve social isolation, an intense focus on machinery, and inborn brilliance. These stereotypes are compatible with qualities that are typically more valued in men than women in American culture. As a result, when computer science and engineering stereotypes are salient, girls report less interest in these fields than their male peers. However, altering these stereotypes-by broadening the representation of the people who do this work, the work itself, and the environments in which it occurs-significantly increases girls' sense of belonging and interest in the field. Academic stereotypes thus serve as gatekeepers, driving girls away from certain fields and constraining their learning opportunities and career aspirations.
authors.affiliation: Department of Psychology, University of Washington Seattle, WA, USA.
authors.forename: Sapna
authors.initials: S
authors.lastname: Cheryan
authors.affiliation: Department of Psychology, University of Washington Seattle, WA, USA ; Institute for Learning & Brain Sciences, University of Washington Seattle, WA, USA.
authors.forename: Allison
authors.initials: A
authors.lastname: Master
authors.affiliation: Department of Psychology, University of Washington Seattle, WA, USA ; Institute for Learning & Brain Sciences, University of Washington Seattle, WA, USA.
authors.forename: Andrew N
authors.initials: AN
authors.lastname: Meltzoff
keywords: belonging; gender; science; stereotypes; underrepresentation