Investigating Course Level Effects on Student Evaluations of Teaching in Higher Education

Abstract

Although student evaluations of teaching (SET) in higher education have recently gained considerable interest, little is known about whether course level influences these evaluations. Accordingly, two datasets, obtained from a large public university in the U.S. Midwest, were analyzed to investigate whether course level makes a difference in SET. The first dataset included 25,306 evaluations across eight course levels collected using the SET questionnaire. A one-way multivariate analysis of variance (MANOVA), followed by univariate analyses of variance (ANOVAs), was conducted to test whether course level makes a difference in SET scores. To cross-validate the results and ensure generalizability, the same analyses were conducted using a second, smaller dataset (N = 444). MANOVA results revealed a statistically significant effect for course level on the combined SET dimensions across both campuses. All univariate ANOVAs were also significant across both campuses. Follow-up post hoc comparisons, with level 1 as the reference group, were statistically significant, especially for level 8. Overall, these results underscore the importance of accounting for course level when interpreting SET and encourage researchers to include key covariates (e.g., class size, discipline, instructor experience, and student composition) to identify the factors driving course-level differences.