A Multi-aspect Analysis of Gender Bias on Online Student Evaluations

TL;DR

This study analyzes two decades of online student evaluations to uncover gender biases in perceptions of teaching style and personality, revealing how these biases evolve over time and differ across regions.

Contribution

It provides the first comprehensive analysis of gender bias evolution in online evaluations over time and space, using large-scale data from Rate My Professors.

Findings

Gender biases influence perceptions of teaching style and personality.

Biases vary over time and across different regions.

Students' evaluations reflect sociological gender stereotypes.

Abstract

Institutions widely use student evaluations to assess the faculty's teaching performance, but underlying trends and biases can influence their interpretation. Using data from Rate My Professors, we conduct the largest and most recent quantitative data analysis to study questions related to the evaluation criteria that students have when they review the performance of their male and female professors. Our analysis spans data from two decades (1999-2019), thus taking into account recent changes on the website and in the perception of students, and demonstrates interesting insights related to how students perceive the teaching style and personality traits of their male and female professors. We also present the first analysis that investigates how gender bias evolves over time and changes over space. We believe that our results are interesting from a sociological viewpoint, as they investigate the role of gender in higher education by disclosing how students perceive and evaluate professors of different genders. In addition, we believe that our findings can be useful to educational institutions when considering possible biases that exist in the evaluations of their faculty.