Virtual learning communities (VLCs) are central to large-scale online education. Their interaction patterns affect the quality of social learning, learner engagement and the sustainability of online courses. Most previous studies take a static perspective, showing only snapshots of VLC structures and ignoring how interactions change over time. This study provides a holistic view of VLCs in massive open online courses (MOOCs), focusing on their dynamic evolution and the conditions that make them more supportive of social learning.
Guided by social learning theory, we conduct a fine-grained analysis of 204 VLCs and 4,385 sequential networks from MOOC forums.
Our social network analysis first identifies the main structural characteristics of MOOC forum networks, then categorizes them into eight distinct types using three key quantitative indicators and finally maps out the potential evolutionary paths these communities follow as they transition between adjacent structural categories (changing one indicator) or across multiple categories (changing two or more indicators over time). Many MOOC communities show low centralization, a high proportion of isolates and low connection density. These patterns are not conducive to social learning. However, certain paths enable their transformation into structures better suited for it.
To the best of our knowledge, this study is among the first to systematically classify VLC network structures in MOOCs and examine their temporal evolution using sequential network analysis. It shows how communities shift between configurations and identifies the pathways that lead towards more effective social learning.
