Learning to monitor and regulate collective thinking processes

In this paper, we propose a conceptual framework to guide the design of a computer-supported collaborative learning intervention to help students learn how to improve collaborative knowledge building discourse at the level of the small group. The framework focuses on scripting individual and collective regulatory processes following collaboration. Individuals are required to evaluate their team’s chat transcripts against rubrics to score discussion quality. These theoretically supported rubrics provide individuals with concrete examples of desired communication processes. After this individual assessment, the team is prompted to discuss their individual scores, identify strengths and weaknesses of their collaborative discourse processes, and select strategies to improve the quality of their collaborative discussion in a future discussion session. To evaluate our framework, we created a prototype of an online system and asked students to use it over ten weeks as part of five discussion sessions. Participants included 37 students, divided into 13 teams, from an undergraduate online course in information sciences. We used quantitative and qualitative analysis techniques to examine students’ collaborative processes over time, with teams as the main unit of analysis. All teams followed the same general activities, but there were two different conditions for scripting individual reflections that preceded the collective sense-making activity: one (Future-thinking) focused on pushing individuals to pay attention to advice on how to improve existing processes in future sessions and another (Evidence-Based) pushed individuals to pay closer attention to the chat transcripts to provide evidence for their group process scores. Our results suggest (1) use of the framework can help students’ monitor and regulate collaborative processes and improve collaborative discourse over time and (2) the Evidence-Based condition can help students engage in higher quality reflective analysis.