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Supporting Learners-to-Learners Interactions Using Online Social Network Information

Authors: DE MEO P; MESSINA F; ROSACI D; SARNE' G;

Supporting Learners-to-Learners Interactions Using Online Social Network Information

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.

Country
Italy
Keywords

Social Networks; Software Agents; Thematic Groups;, Social networks; Software agents; Thematic groups;

  • BIP!
    Impact byBIP!
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green