Abstract
The success of peer feedback approaches to instruction depends upon students contributing in-depth feedback to their peers. Prior researchers have examined the role of general attitudes towards peer feedback, but how experiences, especially the performance information during peer feedback, influence the subsequent amount of feedback that students provide to peers has received little attention. This study investigated what experience factors from one assignment predicted growth or declines in the amount of peer feedback provided on the next assignment in a course with many peer feedback assignments. Data on peer feedback experiences and behaviors across multiple assignments were taken from students across two programming courses (N = 149). Negative binomial regression analyses reveal three experiences in the prior assignment predicted growth in length of comments provided to peers: receiving more comments, doing well on the task, and receiving recognition for good reviewing (when not doing well). Implications for practice are presented.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes on contributors
Zheng Zong, a doctor candidate in the School of Management, Harbin Institute of Technology, China. His research interests included peer assessment, text mining, education management and natural language processing.
Dr. Christian D. Schunn, a professor and senior cognitive scientist working with Learning Research & Development Center (LRDC) at the University of Pittsburgh. His research interest extends to a wide range of cognitive studies involving STEM reasoning and learning, web-based peer interaction and instruction, neuroscience of complex learning, and engagement and learning. He is the founder of an online peer review system (SWoRD), which is widely used in USA, China, and some European countries.
Dr. Yanqing Wang, an associate professor working with the School of Management, Harbin Institute of Technology, China. He is the founder of an information system (EduPCR), which is dedicated to peer code review in educational contexts. His recent research interests include peer assessment, peer code review, reviewer assignment problem, gamification of peer learning, and integer linear programming.