The dynamics of an online knowledge building community: A 5‐year longitudinal study

Abstract

AbstractThis paper reports a 5‐year design experiment on cumulative knowledge building as part of an international project. Through a longitudinal study and analysis of cumulative research data, we sought to answer the question, ‘what happened and why in knowledge building?’ Research data constitute messages which participants have written into a shared knowledge building database. A multi‐method approach combing quantitative and qualitative data was adopted which integrated analysis of message generation, content analysis, network analysis, structure of message threads, discourse analysis and interviews. Conclusions are based on analysis of almost 2000 messages. Qualitative content analysis reveals 14 main categories of data. When the content of the messages are analysed, quantitatively cumulative trends emerge. When the frequencies of messages are plotted against time, peaks and troughs of message writing are revealed. The explanations for these patterns and variations are sought through interviews. Social network analysis shows that the network is centralised. The research literature suggests that decentralised networks are ideal, but in this particular case, the expert centralisation was beneficial for knowledge building in the collaborative and associated professional networks. The reasons for this are discussed.