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Forming Homogeneous Classes for e-Learning in a Social Network Scenario

Contributo in Atti di convegno
Data di Pubblicazione:
2016
Citazione:
Forming Homogeneous Classes for e-Learning in a Social Network Scenario / Comi, A; Fotia, L; Messina, F; Pappalardo, G; Rosaci, D; Sarne', G. - 616:(2016), pp. 131-141. ( IX International Symposium on Intelligent Distributed Computing – IDC’2015 IX International Symposium on Intelligent Distributed Computing – IDC’2015 07-09 October 2015) [10.1007/978-3-319-25017-5_13].
Abstract:
The use of network technology to provide online courses is the latest trend in the training and development industry and has been defined as the “e-Learning revolution”. On the other hand, Online Social Networks (OSNs) represent today an effective possibility to have common and easy-to-use platforms for supporting e-Learning activities. However, as underlined by previous studies, many of the proposed e-Learning systems can result in confusion and decrease the learner’s interest. In this paper, we introduce the possibility to form e-Learning classes in the context of OSNs. At the best of our knowledge, any of the approaches proposed in the past considers the evolution of on-line classes as a problem of matching the individual users’ profiles with the profiles of the classes. In this paper, we propose an algorithm that exploits a multi-agent system to suitably distribute such a matching computation on all the user devices. The good effectiveness and the promising effciency of our approach is shown by the experimental results obtained on simulated On-line Social Networks data.
Tipologia CRIS:
4.1 Contributo in Atti di convegno
Elenco autori:
Comi, A; Fotia, L; Messina, F; Pappalardo, G; Rosaci, D; Sarne', G
Autori di Ateneo:
ROSACI Domenico
Link alla scheda completa:
https://iris.unirc.it/handle/20.500.12318/16201
Titolo del libro:
Intelligent Distributed Computing IX Proceedings of the 9th International Symposium on Intelligent Distributed Computing
Pubblicato in:
STUDIES IN COMPUTATIONAL INTELLIGENCE
Series
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URL

https://link.springer.com/chapter/10.1007/978-3-319-25017-5_13
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