Seeing Beyond the Stereotypes: Gender Bias in Tertiary Student Evaluations of Teachers

Abstract This paper asks how gender bias in student evaluations of teaching evolves as students accumulate university experience. Using longitudinal administrative data from a large Italian public university, we link evaluations to students, instructors, modules, cohorts, and exam outcomes. The dataset includes 12,994 evaluations completed by 2218 students for 143 instructors between 2016/2017 and 2022/2023. Exploiting within-student variation in evaluations across instructors, we find a robust male-teacher premium in perceived teaching quality. This premium is larger among male students but declines as students accumulate university experience, suggesting that gendered evaluation patterns are strongest at the beginning of academic careers. Since true teaching quality is not directly observed, the estimates are interpreted as evidence of differential evaluation patterns consistent with gender bias. The findings suggest that SETs are not gender-neutral and should be used cautiously in high-stakes academic decisions.