Analyzing almost 2,000 peer comments, Wu and Schunn found that feedback quality and feedback frequency — how often multiple reviewers independently flag the same issue — each separately predict whether a person implements the feedback.
Wu, Y., & Schunn, C. D. (2020). "When peers agree, do students listen? The central role of feedback quality and feedback frequency in determining uptake of feedback." Contemporary Educational Psychology, 62, 101897.
Getting feedback and acting on it are two different things — most feedback research stops at the first and assumes the second follows. Wu and Schunn examined what actually predicts uptake: does the quality of a single piece of feedback matter more, or does it matter that multiple reviewers, working independently, flag the same issue?
The researchers analyzed almost 2,000 peer comments received by 107 students in a secondary writing course, tracking which comments students accurately identified as valid and which ones they acted on in their revisions.
Feedback quality and feedback frequency — the number of independent reviewers who raised the same point — each predicted uptake on their own, with no interaction effect between them; they operate as two separate signals rather than reinforcing or canceling each other. Comments correctly identified as high quality were more likely to be implemented once quality was accounted for. Repetition works as a signal in its own right: when several reviewers independently land on the same issue, that agreement carries weight beyond the quality of any one comment.
A single manager's feedback, however well-crafted, is one signal. When three colleagues independently flag the same gap in a deliverable, that agreement is a second, separate signal that increases the odds the person actually fixes it — and it's a signal a single reviewer, however senior, cannot produce alone. This is the direct rationale for assigning each piece of work to multiple reviewers rather than one: it's not redundancy, it's a second mechanism for driving uptake that operates independently of comment quality.
Chris Schunn co-authored this study on how reviewer agreement drives real behavior change in response to feedback. 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.
