Learning Analytics in Education: A Social Network-Based Approach for Analyzing the Interaction and Influence of Collaborative Learning Communities

Abstract

Collaborative learning is viewed as an increasingly important learning mode in higher vocational education these days. In this mode, students are no longer passive receivers of knowledge, but take the roles of creators and sharers, and figuring out the interactive and collaborative relationships between students is particularly important for understanding the pattern and structure of student interaction. With the help of social network analysis methods, this study investigated the social network features of collaborative learning communities, measured the parameters of these network features, analyzed the accessibility of community members, and revealed the influence of members in the community based on the Lead index. The findings of this paper give deeper understandings and new insights into the collaborative learning mode and provide useful evidences for the optimization of collaborative learning strategies.