CNRS, 8 mars 2018 : "Les chercheuses de demain". Anne Boring, Erasmus University Rotterdam

Value of the Information & Strength of the Argument

The talk provides valuable insights into a subtle but significant bias in academia. The argumentation is solid, based on multiple studies with different methodologies (experiments, natural experiments, qualitative analysis). The speaker clearly explains the limitations of each study, such as the difficulty of finding counterfactuals. She also connects the findings to broader implications for women’s careers, making a compelling case for the importance of addressing these biases.

Scientific Rigor, Source Quality, Title Accuracy

The presentation is scientifically rigorous, citing peer-reviewed studies and clearly describing their methods. The speaker does not overstate conclusions and acknowledges cultural variations. The title accurately reflects the content, which focuses on a specific obstacle for women in academia. The talk is part of a CNRS conference on women in science, adding institutional credibility.

The title accurately reflects the content, which focuses on gender biases in student evaluations of teaching, a key obstacle for women in academia.

8/10

The presentation is based on peer-reviewed research and rigorous experimental designs, including randomized experiments and natural experiments. The speaker clearly explains methodologies and caveats. The content is well-supported by academic literature, though it is a conference talk rather than a formal publication.

Markers derived by PSI from the transcript: the creator did not define chapters.

• 00:00Introduction and overview of the talk on gender biases in student evaluations.
• 02:00Discussion of the 2003 US experiment with a virtual lecturer and random gender assignment.
• 05:00Presentation of the online course experiment where instructors swapped identities.
• 08:00Results from her own study in France using natural experiment data.
• 10:00Analysis of qualitative evidence and text analysis of RateMyProfessors.
• 12:00Implications for women's careers and conclusion.

• Study on gender bias in student evaluations (2003) — Referenced as a 2003 US study using a virtual lecturer with random gender assignment.
• Online course experiment with identity swapping — Referenced as an experiment where instructors swapped identities, leading to higher ratings for perceived male instructors.
• Anne Boring's own study in France — Referenced as a natural experiment using data from a French university.
• RateMyProfessors text analysis by Ben Schmitt — Referenced as a text analysis of words used to describe male and female instructors.

• MacNell et al. (2015) - What's in a Name: Exposing Gender Bias in Student Ratings of Teaching — Similar findings from an online course experiment.
• Boring, Ottoboni, Stark (2016) - Student Evaluations of Teaching (Mostly) Do Not Measure Teaching Effectiveness — Peer-reviewed study by the speaker and colleagues showing SETs are biased and not correlated with learning.

• Studies showing no gender bias in SETs — Some studies have found no significant gender bias in student evaluations, suggesting that the effect may vary by context or methodology.