Some student-professor pairings lead to "unusually effective teaching" (and it’s possible to predict which ones)

Video trailers can be used to predict which
lecturers are the best teachers, and which
students they are especially suited to.

In the near future, students could be presented with a series of video trailers of different professors at their university. Based on their ratings of these videos, the students will be paired with the professors who provide the best fit. The outcome will be superior learning, and greater student satisfaction.

That’s the promise of a new study that asked 145 psychology undergrads to rate 6-minute teaching videos of 10 different professors, and then to rate their experience of an actual 40-minute live lecture with those same professors taken several weeks later. The students were also quizzed on the content of those lectures to see how well they’d learned.

Jennifer Gross and her colleagues explain that student evaluations of professors are made up of three key factors: each professor’s actual ability (this component tends to correlate across ratings given by different students); each student’s rating bias (this component correlates across the ratings given by the same student to different professors – for example, some students are more lenient in their ratings than others); and relationship effects.

This last component that is one of the key points of interest in the new study. It pertains to the specific fit, or not, between a professor and a student. When there is a good fit, this leads to unusually high ratings by that student for the professor, above and beyond what you’d expect given the student’s usual rating bias, and given the level of ratings the professor usually attracts.

To zoom in on these relationship effects simply requires factoring out each student’s rating bias, and each professor’s average rating across students.

The exciting finding is that the researchers were able to use the students’ ratings of, and their mood during, the 6-minute trailers to forecast how they later rated the actual lectures, including predicting which professors got the highest average ratings after the lectures, and predicting relationship effects.

This result is important, the researchers explained, because the students’ memory for material taught in a given lecture was independently related both to that lecturer’s average ratings (some lecturers are better than others), but also to the specific relationship effects (i.e. whether the student in question had given that lecturer unusually high ratings – the sign of a good professor/student fit).

“These findings support the possibility of developing online systems that would provide personalised recommendations that specific students take courses from specific professors,” the researchers said.

However, they acknowledged that their results need to be replicated, and they also outlined some limitations of the study. This included the fact they’d carefully compiled the 6-minute trailers to showcase each professor’s teaching style (a time-consuming endeavour); that the live evaluations involved just one lecture rather than an entire course; and that the professors’ teaching skills were confounded with the topics they taught.

  ResearchBlogging.orgGross, J., Lakey, B., Lucas, J., LaCross, R., R. Plotkowski, A., & Winegard, B. (2015). Forecasting the student-professor matches that result in unusually effective teaching British Journal of Educational Psychology, 85 (1), 19-32 DOI: 10.1111/bjep.12049

further reading
Engaging lecturers can breed overconfidence
Is it time to rethink the way university lectures are delivered?

Post written by Christian Jarrett (@psych_writer) for the BPS Research Digest.

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