Abstract Book of the 9th International Conference on Advanced Research in Education
Year: 2025
[PDF]
What Do Students Care About? A Topic Analysis of Online Student Evaluations on Ratemyprofessors
Ziyue Feng, Yuhang She
ABSTRACT:
Student evaluations are essential to understanding teaching and educational quality. Yet the way students speak in public online reviews often deviates from the traditional, structured surveys used inside universities. Current study analyzes 11,088 online comments (from RateMyProfessor.com) across 1,299 instrucStudent evaluations are essential to understanding teaching and educational quality. Yet the way students speak in public online reviews often deviates from the traditional, structured surveys used inside universities. Current study analyzes 11,088 online comments (from RateMyProfessor.com) across 1,299 instructors to ask: what do students care about in their evaluations? Applying Latent Dirichlet Allocation (LDA), we identify a central–peripheral thematic structure. Four dominant topics—“Subjective Experience”, “Course Difficulty”, “Instructor Support”, and “Assignments & Essays”—account for the majority of comments, while five peripheral topics capture niche concerns such as instructors’ humor, personality, or communication issues. We further applied sentiment analysis using VADER to capture emotional tone of the identified structure. Students expressed strong negative feelings in the “Subjective Experience” category, but their comments about course difficulty, instructor support, and assignments were surprisingly positive—even when the workload was challenging. Together, these findings suggest that students value support, clarity, and fairness more than ease alone, highlighting the role of subjective feelings and emotions in evaluating teaching quality. Employing computational methods on educational psychology, the study shows how public online evaluations can complement institutional surveys. They provide a window into student subjective initiatives and emotions, offering practical implications into the teaching practice, course design, and the interpretation of non-institutional feedback in higher education.tors to ask: what do students care about in their evaluations? Applying Latent Dirichlet Allocation (LDA), we identify a central–peripheral thematic structure. Four dominant topics—“Subjective Experience”, “Course Difficulty”, “Instructor Support”, and “Assignments & Essays”—account for the majority of comments, while five peripheral topics capture niche concerns such as instructors’ humor, personality, or communication issues. We further applied sentiment analysis using VADER to capture emotional tone of the identified structure. Students expressed strong negative feelings in the “Subjective Experience” category, but their comments about course difficulty, instructor support, and assignments were surprisingly positive—even when the workload was challenging. Together, these findings suggest that students value support, clarity, and fairness more than ease alone, highlighting the role of subjective feelings and emotions in evaluating teaching quality. By combining computational methods with educational psychology, this study shows how public evaluations can complement institutional surveys. They provide a window into student subjective initiatives and emotions, offering practical implications for teaching practice, course design, and the interpretation of non-institutional feedback in higher education.
Keywords: Computational analytics, educational psychology, sentiment analysis, student evaluations, teaching quality