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Contextualizing gender disparities in online teaching evaluations for professors.

Xiang Zheng1, Shreyas Vastrad1, Jibo He2

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Student evaluations of teaching (SET) show gender bias, with women professors receiving lower ratings. Analysis of 9 million reviews reveals gendered language and polarized sentiment in comments, highlighting potential biases in higher education assessments.

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Area of Science:

  • Higher Education Research
  • Gender Studies
  • Educational Psychology

Background:

  • Student Evaluation of Teaching (SET) is a critical tool for assessing teaching effectiveness in higher education.
  • Existing research suggests potential gender biases in SET, but large-scale analyses are lacking.
  • Understanding these biases is crucial for fair evaluation of professors' careers.

Purpose of the Study:

  • To investigate gender disparities in Student Evaluation of Teaching (SET) using a large dataset.
  • To examine how professor gender influences student comments and ratings.
  • To apply role congruity theory and shifting standards theory to explain observed gender gaps.

Main Methods:

  • Analysis of approximately 9 million Student Evaluation of Teaching (SET) reviews from RateMyProfessors.com.
  • Multiple linear regression to assess the impact of professor gender on numerical ratings.
  • Dunning log-likelihood test and BERTopic for analyzing textual comments and identifying key themes.
  • Sentiment analysis to compare comment polarization across genders.

Main Results:

  • Women professors received significantly lower SET numerical ratings compared to men across many fields.
  • Qualitative analysis revealed distinct language patterns in student comments based on professor gender.
  • Specific topics in SET comments were significantly associated with professor gender, aligning with societal role expectations.
  • Sentiment analysis showed more polarized comments (both positive and negative) for women professors.

Conclusions:

  • Student Evaluation of Teaching (SET) data demonstrates significant gender-based disparities.
  • Gender role expectations appear to influence student evaluations and comments.
  • Caution is advised when using SET for high-stakes decisions due to potential systematic biases against women professors.