Understanding student viewpoints: sentiment and thematic insights from course feedback

Abstract

This study addresses the challenge of interpreting qualitative student feedback from the course experience surveys (CES). Traditional feedback analysis is labor-intensive and not easily scalable. We combine sentiment and thematic analysis to enhance the depth of qualitative insights, uncovering deeper perspectives in student comments. The obtain, scrub, explore, model, and interpret (OSEMN) framework guided data collection, cleaning, exploration, and modeling. The analysis showed that over 70% of student feedback was positive, reflecting high satisfaction with educational experiences. Key findings included a long-tailed distribution of comment lengths, with shorter comments more prevalent. Interestingly, longer comments showed a weak negative correlation with sentiment scores, indicating that length does not necessarily reflect more positive or negative sentiment. Nuanced feedback patterns emerged; higher counts of positive words sometimes decreased sentiment scores, while negative words correlated positively, suggesting complex sentiment expression. We identified five primary themes, they are: i) educational engagement; ii) classroom dynamics; iii) appreciative learning; iv) educational excellence; and v) instructional effectiveness. The study underscores the value of student feedback in driving educational improvements and offers actionable insights for administrators. It demonstrates the potential of automated analysis to transform qualitative data into strategic enhancements, ultimately improving student outcomes and institutional effectiveness. Future research should examine the long-term impacts of feedback-driven interventions and strategies to increase survey engagement.