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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| 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
