Analyzing Peer Dialogue from an Active Learning Perspective

The aim of this research is to provide an Intelligent Collaborative Learning System (ICLS) with the knowledge and skills to promote effective student interaction in a group. Students learning effectively in groups encourage each other to ask questions, explain and justify their opinions, articulate their reasoning, and elaborate and reflect upon their knowledge. The benefits of collaborative learning, however, are only achieved by active, well-functioning learning teams. The collaborative learning model described in this paper identifies the specific characteristics exhibited by effective collaborative learning teams, and based on these characteristics, suggests strategies for promoting effective peer interaction. We present the empirical evaluation of two collaborative learning tools that automate the analysis of collaborative learning interaction and activity. Results from our study confirm that effective learning teams are comprised of active participants who demand explanations and justification from their peers. We compare the distribution of conversational skills used by members of a supportive group committed to their teammates’ learning to that of an unfocused, unsupportive group. The results suggest that structured, high-level knowledge of student conversation and activity appears to be sufficient for enabling an ICLS to assess the quality of group interaction, furthering the possibility of a system that can support and enhance the group learning process.