Exploring the nature of peer feedback: An epistemic network analysis approach

Background Study: Peer feedback has been used as an effective instructional strategy to enhance students' learning in higher education. Objectives: This paper reports on the findings of an explorative study that aimed to increase our understanding of the nature and role of peer feedback in the students' learning process in a computer-supported collaborative learning (CSCL) setting. Exploring what types of feedback are used, and how they relate to each other and are related to academic performance has important implications for students and teachers. Methods: This study was conducted in the higher education setting. It used a dataset consisting of student peer feedback messages (N = 2444) and grades from 231 students who participated in a large engineering course. Using qualitative methods, peer feedback was coded inductively. Epistemic network analysis (ENA) was used to analyse the relation between peer feedback types and performance. Results: Based on the five types of peer feedback (i.e., ‘management’, ‘cognition’ ‘affect’, ‘interpersonal factors’ and ‘suggestions for improvements’), the results of the ENA showed that student feedback categories ‘management’, ‘cognition’ and ‘affect’ were positively related to student performance at the formative assessment phase. Conclusions: The findings and the ENA visualizations also show that ‘suggestions for improvement’ and ‘interpersonal factors’ were not a significant part of student learning in peer assessment and feedback in the studied context.