Detecting Gender Bias in Course Evaluations
This addresses potential gender bias in academic assessments, but it is incremental as it applies existing methods to new data.
The study investigated gender bias in course evaluations using machine learning and NLP, finding differences in student feedback based on the examiner's gender across English and Swedish courses.
An outtake from the findnings of a master thesis studying gender bias in course evaluations through the lense of machine learning and nlp. We use different methods to examine and explore the data and find differences in what students write about courses depending on gender of the examiner. Data from English and Swedish courses are evaluated and compared, in order to capture more nuance in the gender bias that might be found. Here we present the results from the work so far, but this is an ongoing project and there is more work to do.