Applying multilevel modelling to content analysis data: Methodological issues in the study of role assignment in asynchronous discussion groups

This study focuses on the process, output, and interpretation of multilevel analyses on quantitative content analysis data derived from asynchronous discussion group transcripts. The impact of role assignments on the level of knowledge construction reflected in students' contributions and the relation between message characteristics and these levels of knowledge construction is studied. Results show that summarisers' contributions and contributions focussing on theory, content moderating, or summaries result in significantly higher levels of knowledge construction. Multilevel modelling handles the hierarchical nesting, interdependency, and unit of analysis problem and is presented as a suitable technique for studying content analysis data from CSCL-environments.