Berkeley prof wants to nix student evals after white male profs score higher
- UC Berkeley history professor Brian DeLay claimed that students unfairly rated female and racial minority professors on evaluations, citing a study co-authored by a colleague.
- He suggested that schools stop using student evaluations for hiring, promotion, and tenure decisions.
A University of California, Berkeley professor suggested scrapping end-of-semester student evaluations for hiring, promotion, and tenure decisions after claiming that the grades and evaluations are biased against female instructors and people of color.
“Over the next few weeks, students will get the chance to evaluate their professors and TAs. They’re going to get it wrong,” UC Berkeley history professor Brian DeLay tweeted on Sunday. “They’ll be harder on women and people of color than on white men. Tenured white male faculty, in particular, should help their students understand this.”
The study, first published in January of 2016, addressed the effectiveness of student evaluations of teaching (SETs). DeLay asserted in his tweet that the study revealed a bias toward gender and grade expectations, such as how quickly an assignment is graded and returned with feedback, rather than a review of the professor’s educational effectiveness.
“Instructor race is also associated with SET…” DeLay said in a follow-up tweet, referencing the study’s finding that minority professors tend to receive, on average, “significantly lower” scores than their white, male counterparts. He goes on to mention the study’s claim that “age, charisma, and physical attractiveness” also factor into evaluations.
DeLay suggests that student evaluations should not be used as a standard for promotion or tenure decisions, or for hiring practices.
"[G]iven the well-documented shortcomings of SETs, we shouldn't be using them for hiring, tenure, or promotion decisions," DeLay tweeted. “In the meantime, tenured faculty - especially tenured white men - should explain this stuff to our students before each evaluation season."
"Help them understand why evals matter to peoples’ careers, & how implicit bias affects the results. They’ll listen," he added.
DeLay, Stark, and Stark’s study co-authors did not respond to requests for comment in time for publication.
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