Towards a recommendation system for the learner from a semantic model of knowledge in a collaborative environment. Mediani, C.; Abel, M.; and Djoudi, M. In IFIP Advances in Information and Communication Technology, volume 456, pages 315-327, 2015.
Towards a recommendation system for the learner from a semantic model of knowledge in a collaborative environment [pdf]Website  abstract   bibtex   
© IFIP International Federation for Information Processing 2015. Collaboration is a common work between many people which generates the creation of a common task. A computing environment can foster collaboration among peers to exchange and share knowledge or skills for succeeding a common project. Therefore, when users interact among themselves and with an environment, they provide a lot of information. This information is recorded and classified in a model of traces to be used to enhance collaborative learning. In this paper, we propose (1) the refinement of a semantic model of traces with indicators calculated according to Bayes formulas and (2) the exploitation of these indicators to provide recommendations to the learner to reinforce learning points with learners, of his/her community of collaboration, identified as "experts".
@inproceedings{
 title = {Towards a recommendation system for the learner from a semantic model of knowledge in a collaborative environment},
 type = {inproceedings},
 year = {2015},
 identifiers = {[object Object]},
 keywords = {Learner Modeling},
 pages = {315-327},
 volume = {456},
 websites = {http://djoudi.online.fr/publications/files/2015_05_20_CIIA2015_Saida_Mediani.pdf},
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 abstract = {© IFIP International Federation for Information Processing 2015. Collaboration is a common work between many people which generates the creation of a common task. A computing environment can foster collaboration among peers to exchange and share knowledge or skills for succeeding a common project. Therefore, when users interact among themselves and with an environment, they provide a lot of information. This information is recorded and classified in a model of traces to be used to enhance collaborative learning. In this paper, we propose (1) the refinement of a semantic model of traces with indicators calculated according to Bayes formulas and (2) the exploitation of these indicators to provide recommendations to the learner to reinforce learning points with learners, of his/her community of collaboration, identified as "experts".},
 bibtype = {inproceedings},
 author = {Mediani, Chehrazed and Abel, Marie-Hélène and Djoudi, Mahieddine},
 booktitle = {IFIP Advances in Information and Communication Technology}
}
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