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Summary of Detecting Gender Bias in Course Evaluations, by Sarah Lindau and Linnea Nilsson


Detecting Gender Bias in Course Evaluations

by Sarah Lindau, Linnea Nilsson

First submitted to arxiv on: 2 Apr 2024

Categories

  • Main: Machine Learning (cs.LG)
  • Secondary: Computation and Language (cs.CL)

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GrooveSquid.com Paper Summaries

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Summary difficulty Written by Summary
High Paper authors High Difficulty Summary
Read the original abstract here
Medium GrooveSquid.com (original content) Medium Difficulty Summary
In a machine learning and NLP-focused master’s thesis, researchers investigate gender bias in course evaluations. The study employs various methods to analyze data and uncover differences in student feedback based on the instructor’s gender. A comparison of English and Swedish courses aims to capture nuanced gender biases. This summary presents preliminary findings from an ongoing project.
Low GrooveSquid.com (original content) Low Difficulty Summary
Researchers explored gender bias in course evaluations using machine learning and NLP. They analyzed student feedback and found that students write about courses differently depending on the instructor’s gender. The study compared English and Swedish courses to better understand this bias.

Keywords

» Artificial intelligence  » Machine learning  » Nlp