Tuesday, September 12, 2017
Friederike Mengel, Jan Sauermann, Ulf Zolitz, Gender Bias in Teaching Evaluations
This paper provides new evidence on gender bias in teaching evaluations. We exploit
a quasi-experimental dataset of 19,952 student evaluations of university faculty [in the Netherlands] in a context where students are randomly allocated to female or male instructors. Despite the fact that neither students’ grades nor self-study hours are affected by the instructor’s gender, we find that women receive systematically lower teaching evaluations than their male colleagues. This bias is driven by male students’ evaluations, is larger for mathematical courses and particularly pronounced for junior women. The gender bias in teaching evaluations we document may have direct as well as indirect effects on the career progression of women by affecting junior women’s confidence and through the reallocation of instructor resources away from research and towards teaching.
From the paper:
Our results show that female faculty receive systematically lower teaching evaluations than their male colleagues despite the fact that neither students’ current or future grades nor their study hours are affected by the gender of the instructor. The lower teaching evaluations of female faculty stem mostly from male students, who evaluate their female instructors 21% of a standard deviation worse than their male instructors. While female students were found to rate female instructors about 8% of a standard deviation lower than male instructors.
When testing whether results differ by seniority, we find the effects to be driven by junior instructors, particularly PhD students, who receive 28% of a standard deviation lower teaching evaluations than their male colleagues. Interestingly, we do not observe this gender bias for more senior female instructors like lecturers or professors. We do find, however, that the gender bias is substantially larger for courses with math-related content. Within each of these subgroups, we confirm that the bias cannot be explained by objective differences in grades or student effort. Furthermore, we find that the gender bias is independent of whether the majority of instructors within a course is female or male. Importantly, this suggests that the bias works against female instructors in general and not only against minority faculty in gender-incongruent areas, e.g., teaching in more math intensive courses.
The gender bias against women is not only present in evaluation questions relating to the individual instructor, but also when students are asked to evaluate learning materials, such as text books, research articles and the online learning platform. Strikingly, despite the fact that learning materials are identical for all students within a course and are independent of the gender of the section instructor, male students evaluate these worse when their instructor is female. One possible mechanism to explain this spillover effect is that students anchor their response to material-related questions based on their previous responses to instructor-related questions.