Peer feedback is only as good as the prompts that scaffold it. Mu and Schunn examined which comment-prompt features actually produce longer, more helpful feedback — and which ones backfire.
Mu, H., Schunn, C.D. (2025). "The good, bad, and ugly of comment prompts: Effects on length and helpfulness of peer feedback." International Journal of Educational Technology in Higher Education, 22, 4.
Peer feedback systems commonly scaffold reviewers with instructor-written comment prompts, but there was little research on which prompt features in actual practice help and which ones don't. Mu and Schunn asked which prompt design choices reliably produce longer, more helpful comments, and which ones look reasonable but don't move the needle, or hurt.
The researchers analyzed how instructor-generated comment prompts, and their specific scaffolding features, related to the length and helpfulness of the peer feedback students actually produced in response.
Peer feedback is highly effective for learning, but only when reviewers give detailed and helpful feedback — and prompt design measurably shapes whether that happens. Some prompt features reliably lengthen and improve comments; others show little effect despite looking like reasonable scaffolding choices.
The prompt is a lever, not decoration. A poorly worded reviewer prompt in a workplace peer-review process produces the same shallow, unhelpful comments as a poorly worded rubric in a classroom. Before assuming employees are bad at giving feedback, check whether the prompt is actually asking them the right question.
Chris Schunn co-authored this study on how prompt design shapes the quality of the feedback people actually produce. He is a Professor of Psychology, Learning Sciences and Policy, and Intelligent Systems at the University of Pittsburgh and a Senior Scientist at the University's Learning Research and Development Center (LRDC), where he has directed research projects backed by more than $80M in federal grants. As Peerceptiv's Chief Learning Scientist, his research directly shapes how the platform structures reviewer prompts, rubrics, and feedback workflows.
