Stereotype Threat in Virtual Learning Environments: Effects of Avatar Gender and Sexist Behavior on Women's Math Learning Outcomes.

Abstract

Women in math, science, and engineering (MSE) often face stereotype threat: they fear that their performance in MSE will confirm an existing negative stereotype-that women are bad at math-which in turn may impair their learning and performance in math. This research investigated if sexist nonverbal behavior of a male instructor could activate stereotype threat among women in a virtual classroom. In addition, the research examined if learners' avatar representation in virtual reality altered this nonverbal process. Specifically, a 2 (avatar gender: female vs. male) × 2 (instructor behavior: dominant sexist vs. nondominant or nonsexist) between-subjects experiment was used. Data from 76 female college students demonstrated that participants learned less and performed worse when interacting with a sexist male instructor compared with a nonsexist instructor in a virtual classroom. Participants learned and performed equally well when represented by female and male avatars. Our findings extend previous research in physical learning settings, suggesting that dominant-sexist behaviors may give rise to stereotype threat and undermine women's learning outcomes in virtual classrooms. Implications for gender achievement gaps and stereotype threat are discussed.