Gender and cultural bias in student evaluations: Why representation matters

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Abstract

Gendered and racial inequalities persist in even the most progressive of workplaces. There is increasing evidence to suggest that all aspects of employment, from hiring to performance evaluation to promotion, are affected by gender and cultural background. In higher education, bias in performance evaluation has been posited as one of the reasons why few women make it to the upper echelons of the academic hierarchy. With unprecedented access to institution-wide student survey data from a large public university in Australia, we investigated the role of conscious or unconscious bias in terms of gender and cultural background. We found potential bias against women and teachers with non-English speaking backgrounds. Our findings suggest that bias may decrease with better representation of minority groups in the university workforce. Our findings have implications for society beyond the academy, as over 40% of the Australian population now go to university, and graduates may carry these biases with them into the workforce.

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Student Evaluations of Teaching (Mostly) Do Not Measure Teaching Effectiveness

Anne Boring, Kellie Ottoboni, Philip Stark (2016)

Student evaluations of teaching (SET) are widely used in academic personnel decisions as a measure of teaching effectiveness. We show: SET are biased against female instructors by an amount that is large and statistically significant the bias affects how students rate even putatively objective aspects of teaching, such as how promptly assignments are graded the bias varies by discipline and by student gender, among other things it is not possible to adjust for the bias, because it depends on so many factors SET are more sensitive to students' gender bias and grade expectations than they are to teaching effectiveness gender biases can be large enough to cause more effective instructors to get lower SET than less effective instructors. These findings are based on nonparametric statistical tests applied to two datasets: 23,001 SET of 379 instructors by 4,423 students in six mandatory first-year courses in a five-year natural experiment at a French university, and 43 SET for four sections of an online course in a randomized, controlled, blind experiment at a US university.