Analyzing Gender Bias in Student Evaluations

Andamlak Terkik, Emily Prud’hommeaux, Cecilia Ovesdotter Alm, Christopher Homan, Scott Franklin


Abstract
University students in the United States are routinely asked to provide feedback on the quality of the instruction they have received. Such feedback is widely used by university administrators to evaluate teaching ability, despite growing evidence that students assign lower numerical scores to women and people of color, regardless of the actual quality of instruction. In this paper, we analyze students’ written comments on faculty evaluation forms spanning eight years and five STEM disciplines in order to determine whether open-ended comments reflect these same biases. First, we apply sentiment analysis techniques to the corpus of comments to determine the overall affect of each comment. We then use this information, in combination with other features, to explore whether there is bias in how students describe their instructors. We show that while the gender of the evaluated instructor does not seem to affect students’ expressed level of overall satisfaction with their instruction, it does strongly influence the language that they use to describe their instructors and their experience in class.
Anthology ID:
C16-1083
Volume:
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
Month:
December
Year:
2016
Address:
Osaka, Japan
Venue:
COLING
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
868–876
Language:
URL:
https://aclanthology.org/C16-1083
DOI:
Bibkey:
Cite (ACL):
Andamlak Terkik, Emily Prud’hommeaux, Cecilia Ovesdotter Alm, Christopher Homan, and Scott Franklin. 2016. Analyzing Gender Bias in Student Evaluations. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 868–876, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Analyzing Gender Bias in Student Evaluations (Terkik et al., COLING 2016)
Copy Citation:
PDF:
https://aclanthology.org/C16-1083.pdf