– Girls’ self-reported interest in enrolling in an introductory computer science course was significantly increased when the classroom environment was altered so that it did not fit high school students’ current stereotypes of computer science. In contrast, boys’ self-reported interest in computer science did not differ across the two classrooms.
– A computer science classroom that did not project current computer science stereotypes caused girls, but not boys, to express more interest in taking computer science than a classroom that made these stereotypes salient. The gender difference was mediated by girls’ lower sense of belonging in the course, even beyond the effects of negative stereotype concerns, expectations of success, and utility value.
– Girls’ lower sense of belonging could be traced to lower feelings of fit with computer science stereotypes. Individual differences in fit with stereotypes predicted girls’ belonging and interest in a stereotypical, but not a nonstereotypical, classroom.
– High-school girls’ interest in enrolling in classes can thus be influenced by the design of classrooms, providing evidence for the ability of classroom environments to signal who belongs.
– Girls who felt that they fit the computer science stereotypes reported greater interest in enrolling in the stereotypical classroom, but there was no relationship for the nonstereotypical classroom.
– Experiment 2 revealed that girls reported more interest in enrolling in an introductory computer science course when the physical environment was nonstereotypical compared with stereotypical. In contrast, boys’ self-reported interest in the course did not depend on the classroom environment.
– Girls may avoid computer science courses because current prevailing stereotypes of the field signal to them that they do not belong. However, providing them with an educational environment that does not fit current computer science stereotypes increases their interest in computer science courses and
could provide grounds for interventions to help reduce gender disparities in computer science enrollment.