Exploring end-point use and identifying predictors of overall ratings in student evaluations of teaching (SETs)

The present study examines student evaluations of teaching (SETs) at a large, public university. We evaluate end-point use across different scales and examine how well evaluation items predict overall instruction and course ratings among several majors. We find that students use the upper endpoints of scales more often when rating female professors compared to male professors. We also find that students use endpoints more often when using a 10-point 4-letter grading scale compared to a 7-point Likert-type scale. Hierarchical Bayesian regressions reveal, at the population level, that items pertaining to the instructor's clarity, engagement, knowledge, and fairness of grading best predict the rating of the instructor, while items pertaining to the course’s usefulness in developing future skills and the match between course objective and outcomes best predict the rating of the overall value of the course.