SETSum: Summarization and Visualization of Student Evaluations of Teaching

TL;DR

SETSum is a novel system that enhances the interpretation of Student Evaluations of Teaching by organizing, summarizing, and visualizing both quantitative and qualitative feedback, thereby improving instructional insights.

Contribution

The paper introduces SETSum, a system that combines sentiment analysis, aspect extraction, summarization, and visualization to improve SET report interpretation.

Findings

Professors found SETSum more efficient for interpreting SET results.

Majority of instructors preferred SETSum over traditional static reports.

System demonstrates potential to change SET reporting practices.

Abstract

Student Evaluations of Teaching (SETs) are widely used in colleges and universities. Typically SET results are summarized for instructors in a static PDF report. The report often includes summary statistics for quantitative ratings and an unsorted list of open-ended student comments. The lack of organization and summarization of the raw comments hinders those interpreting the reports from fully utilizing informative feedback, making accurate inferences, and designing appropriate instructional improvements. In this work, we introduce a novel system, SETSum, that leverages sentiment analysis, aspect extraction, summarization, and visualization techniques to provide organized illustrations of SET findings to instructors and other reviewers. Ten university professors from diverse departments serve as evaluators of the system and all agree that SETSum helps them interpret SET results more efficiently; and 6 out of 10 instructors prefer our system over the standard static PDF report (while the remaining 4 would like to have both). This demonstrates that our work holds the potential to reform the SET reporting conventions in the future. Our code is available at https://github.com/evahuyn/SETSum