Skip to main content Skip to secondary navigation
Journal Article

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

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. The current research investigated if sexist non-verbal behavior of a male instructor that is indicative of negative stereotypes about women could activate stereotype threat among women in a virtual classroom. Additionally, the research examined if learners’ avatar representation in VR altered this non-verbal process. Specifically, a 2 (avatar gender: female vs. male) x 2 (instructor behavior: dominant-sexist vs. non-dominant or non-sexist) between-subjects experiment was employed. Data from 76 female college students demonstrated that participants learned less and performed worse when interacting with a sexist male instructor compared to a non-sexist 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.

View PDF

F. Chang
M. Luo
G. Walton
L. Aguilar
J. Bailenson
Journal Name
Cyberpsychology, Behavior, and Social Networking
Publication Date