Abstract
Some learning theories emphasize the benefits of group work and shared knowledge acquisition in the learning processes. The Computer-Supported Collaborative Learning (CSCL) systems are used to supportcollaborative learning and knowledge building, making communication tools, shared workspaces, and automatic analysis tools available to users. In this article we describe a Bayesian network automatically built from a database of analysis indicators qualifying the individual work, the group work, and the solutions built in a CSCL environment that supports a problem solving approach. This network models the relationships between the indicators that represent both the collaborative workprocess and the problem solution.
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Duque, R., Bravo, C., Lacave, C. (2007). Analyzing Collaborative Problem Solving with Bayesian Networks. In: Ellis, R., Allen, T., Tuson, A. (eds) Applications and Innovations in Intelligent Systems XIV. SGAI 2006. Springer, London. https://doi.org/10.1007/978-1-84628-666-7_3
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DOI: https://doi.org/10.1007/978-1-84628-666-7_3
Publisher Name: Springer, London
Print ISBN: 978-1-84628-665-0
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