Using Social Network Analysis to Evaluate Individual Contributions in Online Collaborative Learning Communities: A Case Study of Reading Groups

Abstract

Research on online collaborative learning communities still faces the challenge of evaluating individual contributions. Social Network Analysis (SNA) has been proposed as an innovative method to facilitate teachers observing group members’ social interaction and assessing their learning engagement and performance in collaborative learning activities. Accordingly, adopting a case study approach, this study employed SNA to evaluate individual contributions in online collaborative reading groups. New algorithms were put forward to help identify opinion leaders and detect group polarization in small group reading. The results revealed that the proposed method can be used to successfully recognize opinion leaders and group polarization phenomenon which serves as important information source for teachers to orchestrate and regulate collaborative learning groups. This study provides new insight into using SNA to evaluate individual contributions in online collaborative learning communities.