#561: How Do Pre-Service Teachers Integrate Multiple Peer Feedback Messages? Identifying Different Integration Patterns

Computer-supported peer feedback is a valuable approach to enhancing student learning in CSCL environments. Yet, little is known about how learners process multiple peer feedback messages. In an exploratory study with N = 100 pre-service teachers who analyzed classroom cases, provided feedback, and integrated feedback from two peers, we aimed to identify different feedback integration patterns (RQ1) and investigated how these are predicted by objective feedback features and perceived feedback quality (RQ2). A hierarchical cluster analysis yielded three integration patterns: a confirmation pattern, a conflict pattern, and a selective integration pattern. Multinomial logistic regressions revealed that objective feedback features—specifically accuracy, relevance, and implementability—predicted these integration patterns, whereas perceived feedback quality did not. These findings highlight that integrating multiple peer feedback messages is a complex, feature-dependent process. In addition, they offer implications for designing adaptive, computer-supported peer feedback systems in CSCL settings.