Designing a Multi-agent Architecture based on Clusterization for Collaborative Learning Sessions
نویسندگان
چکیده
collaboration between learners can have a positive impact in a learning session only if learners can exchange efficiently. Discussions, advices given by a colearner are good means to help a learner in knowledge understanding. One of the main problems in a collaborative learning activity is to create coherent groups among students. In this paper, we present an architecture that aims to address this question. We use a neural network algorithm to obtain homogenous groups. An architecture based on several agents is then able to select the more relevant group and provide the learning session with information related to the subject.
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