Among the earliest empirical evidence for a principle now central to Peerceptiv's research: the way someone reviews a peer's work changes the quality of their own writing afterward.
Wooley, R., Was, C., Schunn, C.D., Dalton, D.W. (2008). "The Effects of Feedback Elaboration on the Giver of Feedback." Proceedings of the Annual Meeting of the Cognitive Science Society.
This study asked a question that later became a central thread in Peerceptiv's research program: does the way someone reviews a peer's work — specifically, how elaborate their feedback is and whether they use concrete examples — affect the reviewer's own subsequent writing, independent of anything the person they reviewed does?
Run on SWoRD, the online peer review system built at the University of Pittsburgh that was later commercialized as Peerceptiv, the study varied the degree of elaboration and use of prototypical examples in students' reviewing activity and measured the effect on their own later writing.
Students who provided more elaborate feedback, including feedback that used concrete examples, showed improvements in their own subsequent writing. The act of reviewing thoroughly changed the reviewer's own skill, not just the person being reviewed.
This is among the earliest evidence for a principle that now underlies how Peerceptiv structures its reviewer prompts: pushing reviewers toward elaboration and concrete examples isn't just about giving the author better feedback. It's a direct investment in the reviewer's own skill development, measurable independent of what the author does with the feedback afterward.
Chris Schunn co-authored this early study, run on the SWoRD system that became Peerceptiv, on how giving elaborate feedback builds the giver's own skill. 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.
