—E-Learning students can benefit from proper class formation process based on the student needs. In particular, Online Social Networks make available data concerning users’ interactions, as skills and trust relationships, that are behind the dynamics of thematic social network groups, and can be exploited to form e-Learning classes. To this aim, we propose a model based on such information, which are properly combined to support the dynamics of e-Learning classes on Online Social Networks. The approach provide a way to give suggestions to users about the best classes to join with and to class adminastrors the best students to accept. The proposed approach has been tested by simulating an e-Learning scenario within a large social network by showing its capability to satisfy all the actors.
Supporting Learners-to-Learners Interactions Using Online Social Network Information / DE MEO, P; Messina, F; Rosaci, D; Sarne', G. - 1664:(2016), pp. 10.51-10.56. (Intervento presentato al convegno 17th edition of the International Workshop "From Objects to Agents" tenutosi a Catania (Italy) nel 25-29 July 2016).
Supporting Learners-to-Learners Interactions Using Online Social Network Information
ROSACI D;SARNE' G
2016-01-01
Abstract
—E-Learning students can benefit from proper class formation process based on the student needs. In particular, Online Social Networks make available data concerning users’ interactions, as skills and trust relationships, that are behind the dynamics of thematic social network groups, and can be exploited to form e-Learning classes. To this aim, we propose a model based on such information, which are properly combined to support the dynamics of e-Learning classes on Online Social Networks. The approach provide a way to give suggestions to users about the best classes to join with and to class adminastrors the best students to accept. The proposed approach has been tested by simulating an e-Learning scenario within a large social network by showing its capability to satisfy all the actors.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.