A Conceptual Framework for Collaborative Learning Systems Based on Agent Technologies


Elena Nardini  /  Elena Nardini, Matteo Casadei, Andrea Omicini, Pietro Gaffuri

Experimental studies concerning distance and blended learning have shown that forms of interaction, like those key for collaborative learning, lead to desirable cognitive activities. However, existing distance and blended learning systems provide collaboration tools (like forum, chat, Wiki, etc.) presenting some limits that reduce the effectiveness of such tools from the standpoint of collaborative learning. Accordingly, a conceptual framework is needed that bridges the gap between the interaction forms characterising collaborative learning and existing learning collaboration tools. In this context, Multi-Agent System (MAS) seems to be a suitable paradigm to engineer such systems as it promotes effective collaboration. This paper shows how the Agents and Artefacts (A&A) meta-model for MAS could be exploited to build a conceptual framework for collaborative learning systems.

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