Predictors of Student Course Evaluations

• In Event: Poster Session 8
  In Poster Session: Division J Section 4 Poster Session 1

Abstract

This study explored the relationship between student, course, and instructor-level variables and student course ratings. Results from hierarchical linear modeling (HLM) analyses indicated that most of the statistically significant relationships were found at the student-level and that prior student course interest and the amount of student effort were statistically significant predictors of student course rating in all of the regression models. These findings were supported by previous studies and provide further evidence of such relationships. Additionally, student course rating was a statistically significant predictor of student course grade. This finding is consistent with the existing literature which posits a weak positive relationship between expected course grade and student course rating.

Authors

• Timothy Michael Sauer

• Namok Choi, University of Louisville