Workshop on Designing Computational Models of Collaborative Learning Interaction

During collaborative learning activities, factors such as students’ prior knowledge, motivation,roles, language, behavior and interaction dynamics interact with each other in unpredictable ways, making it very difficult to predict and measure learning effects. This may be one reason why the focus of collaborative learning research shifted in the nineties from studying group characteristics and products to studying group process. With an interest in having an impact on the group process in modern distance learning environments, the focus has recently shifted again – this time from studying group processes to identifying computational strategies that positively influence group learning. This shift toward mediating and supporting collaborative learners is fundamentally grounded in our understanding of the interaction described by our models of collaborative learning interaction. In this workshop, we will explore the advantages, implications, and support possibilities afforded by the various types of computational models of collaborative learning processes.