One of the reasons for the renewed interest in addressing systemic barriers to women in STEM (Science, Technology, Engineering and Mathematics) is a plethora of recent social sciences peer-reviewed research into implicit or unconscious bias, stereotype threat, and the Dunning Kruger Effect.
I think that Ben Schmidt has created the most compelling data visualization tool for illustrating systemic gender bias in higher education. His tool shows the gender differences in how students use certain words to describe their professors, on the website, RateMyProfessors.com.
— Dawn Bazely (@dawnbazely) January 8, 2016
Last week, Grunspan et al. (2016) published their study of how undergraduate biology students nominate and rank the most knowledgeable (smartest?) students in the class, in PLOS One. These nominations turn out to be heavily biased in favour of males rating males the highest, regardless of a student's actual academic standing. This effect not only persisted across different cohorts of the same course, but increased from week 1 to 7 in the semester. The gender effect didn't exist amongst female students.
Grunspan et al. 2016. Males Under-Estimate Academic Performance of Their Female Peers in Undergraduate Biology Classrooms. PLOS One: DOI: 10.1371/journal.pone.0148405
Naturally, this study was widely discussed in the biology twitterverse, with anecdotes concerning both how people have observed this phenomenon, and what they do to try and prevent these kinds of gendered prejudices from forming. Ironically, last Thursday was the first international day of women and girls in science, so Dr. Victoria Metcalf blogged both about that and Grunspan et al.'s study!
Given the concern, I suggested that we might have some kind of tweet chat, and before I knew it, had signed up to moderate a #ProfChat session on Tuesday February 16th at 8pm EST.
Here are 6 questions for the Biology college and university community, and the broader higher education community to consider during Tuesday 16 February 2016's tweet chat at 8pm EST. @philosophypaul offered questions 2 & 4 over twitter:
- Were the results of Grunspan et al.'s study a surprise to you? "Males Under-Estimate Academic Performance of Their Female Peers in Undergraduate Biology Classrooms"
- How early, do you think, that gender bias in STEM develops?
- Do you generally consider gender bias in science and tech more likely to be observed amongst older people?
- Do you think that gender bias feeds into race or class bias? If yes, why?
- Have you ever taken implicit bias training?
- Do you discuss the research literature on systemic gender and racial bias in your (STEM or otherwise) courses?
- What are some examples of gender bias that you have observed in your courses?
- How do you counter bias in your teaching?
Here's the storify of the tweets about the article: