Forecasting the student–professor matches that result in unusually effective teaching

BACKGROUND: Two important influences on students' evaluations of teaching are relationship and professor effects. Relationship effects reflect unique matches between students and professors such that some professors are unusually effective for some students, but not for others. Professor effects reflect inter-rater agreement that some professors are more effective than others, on average across students. AIMS: We attempted to forecast students' evaluations of live lectures from brief, video-recorded teaching trailers. SAMPLE: Participants were 145 college students (74% female) enrolled in introductory psychology courses at a public university in the Great Lakes region of the United States. METHODS: Students viewed trailers early in the semester and attended live lectures months later. Because subgroups of students viewed the same professors, statistical analyses could isolate professor and relationship effects. RESULTS: Evaluations were influenced strongly by relationship and professor effects, and students' evaluations of live lectures could be forecasted from students' evaluations of teaching trailers. That is, we could forecast the individual students who would respond unusually well to a specific professor (relationship effects). We could also forecast which professors elicited better evaluations in live lectures, on average across students (professor effects). Professors who elicited unusually good evaluations in some students also elicited better memory for lectures in those students. CONCLUSIONS: It appears possible to forecast relationship and professor effects on teaching evaluations by presenting brief teaching trailers to students. Thus, it might be possible to develop online recommender systems to help match students and professors so that unusually effective teaching emerges.