Online Social Networks are suitable environments for e-Learning for several reasons. First of all,there are many similarities between social network groups and classrooms. Furthermore,trust relationships taking place within groups can be exploited to give to the users the needed motivations to be engaged in classroom activities. In this paper we exploit information about users’ skills,interactions and trust relationships,which are supposed to be available on Online Social Networks,to design a model for managing formation and evolution of e-Learning classes and providing suggestions to a user about the best class to join with and to the class itself about the best students to accept. The proposed approach is validated by a simulation which proves the convergence of the distributed algorithm discussed in this paper.
De Meo, P., Fotia, L., Messina, F., Rosaci, D., Sarné, G. (2017). Forming classes in an e-Learning social network scenario. In C. Badica, A. El Fallah Seghrouchni, A. Beynier, D. Camacho, C. Herpson, K. Hindriks, et al. (a cura di), Intelligent Distributed Computing X Proceedings of the 10th International Symposium on Intelligent Distributed Computing – IDC 2016, Paris, France, October 10-12 2016 (pp. 173-182). Springer [10.1007/978-3-319-48829-5_17].
Forming classes in an e-Learning social network scenario
Sarné, GML
2017
Abstract
Online Social Networks are suitable environments for e-Learning for several reasons. First of all,there are many similarities between social network groups and classrooms. Furthermore,trust relationships taking place within groups can be exploited to give to the users the needed motivations to be engaged in classroom activities. In this paper we exploit information about users’ skills,interactions and trust relationships,which are supposed to be available on Online Social Networks,to design a model for managing formation and evolution of e-Learning classes and providing suggestions to a user about the best class to join with and to the class itself about the best students to accept. The proposed approach is validated by a simulation which proves the convergence of the distributed algorithm discussed in this paper.
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