Network analysis of trace data for the support of group work: activity patterns in a completely online course

A 16-student, completely online software design course was studied using social network analysis and grounded theory techniques. Bi-directional (read and post) log data of user activity was recorded to understand how small group networks change over time with activity type (individual, peer-to-peer, and small group). Network structure was revealed through sociograms and triangulated with discussion board topics and interview data on group experience. Results show significant differences in network structure across activity types, which are supported by open coding and axial coding of the text of member discussions and editing patterns of member work products. It is also indicated that bi-directional log data, contextualized to specific activities and artifacts, revealed a more accurate and complete description of small group activity than ordinary, uni-directional log data would have. Our findings have implications for tool development revealing group structure and software design for completely online group work.

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