LDA topic modelling of 6,087 written student feedback responses yields six SET-related topics¶

Claim · All claims
Evidence · 1 study · design r2 · q2
Currency · newest study 2020 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Applying LDA topic modelling to 6,087 written student feedback responses from a Finnish university produced a six-topic model covering themes such as good content, dissatisfaction, workload and good teaching methods. → Hujala 2020

Evidence¶

Hujala 2020¶

Hujala, M., Knutas, A., Hynninen, T., & Arminen, H. (2020). Improving the quality of teaching by utilising written student feedback: A streamlined process. Computers & Education. https://doi.org/10.1016/j.compedu.2020.103965

q2 · i? · design · r2

Analysis of written student feedback collected at a Finnish university during the 2016-17 and 2017-18 academic years, restricted to responses written in Finnish, yielding a sample of 6,087 responses. The number of topics was selected by examining "local maximums in the semantic coherence results".

"After examining the local maximums in the semantic coherence results, we proceeded with a topic model with six topics."

Discussion¶

Related Claims¶

• Thematic analysis of LDA topics identifies six SET themes matching prior literature — possibly the same claim (merge candidate)
• LDA topics capture unique information not covered by Likert-scale SET questions — related
• Topic modeling of open-ended responses revealed five themes centered on ChatGPT's simplicity, speed, and role as a support tool — related
• Likert-scale SET variables predict topic probabilities for most topics in both academic years — related
• Feedback questionnaire wording affects LDA topic results, more for emotional value than content — related
• Topic 4 (dissatisfaction with workload) contradicts thematic analysis and appears invalid — related