A topic model analysis of students' gendered expectations using surveyed critiques of lecturers

Abstract

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Student evaluations of teaching (SET) have been examined over the years to better understand the student experience, with an increasing portion of literature exploring the presence of implicit bias in SET surveys against minority gender and ethnic lecturers. This study explores free-text comments made by students from a large public university in Australia over the period 2010–2016, using a semi-supervised statistical approach. Data were collected via surveys administered online at the end of each course to every student officially enrolled in that course via the learning management system, and completion of the surveys was voluntary. We build a probabilistic topic model which incorporates student and lecturer characteristics into the topic formation process. We make statistical inference on the effects of gender and cultural or language backgrounds based on the topic and word prevalence probabilities. The results showed clear separation of topics discussed between male and female lecturers. From a gendered perspective, our topic analyses have found that students are significantly more likely to critique female lecturers to improve on structural aspects of the course, as well as aspects of time management and control of the lecturing environment. In comparison, male lecturers were significantly more likely to be critiqued on specific aspects related to lecture delivery. Lecturers from non-English speaking backgrounds were more likely to be both critiqued and praised for the clarity of their delivery.

Keywords

• higher education
• gender bias
• text analysis
• topic models
• SET surveys