June 24, 2009 to June 27, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CASoN.2009.34
The growth of eLearning systems popularity motivates researchers to study these systems intensively. Users of eLearning systems form social networks through the different activities performed by them (sending emails, reading study materials, chat, taking tests, etc.). This paper focuses on searching of latent social networks from eLearning systems data. This data consists of students activity records where latent ties among actors are embedded. The social network studied in this paper is represented by groups of students who have similar contacts, and interact in similar social circles, where the interest in performing similar tasks among users determines the groups with similar interactions. Different methods of data clustering analysis were applied to these groups and the findings show the existence of latent ties among the group members. The second part of this paper focuses on social network visualization. Graphical representation of social network can describe its structure very efficiently. It can enable social network analysts to determine the network degree of connectivity. Analysts can easily determine individuals with a small or large amount of relationships and determine the amount of independent groups in a given network.
log analysis, eLearning system, social network
Pavla Dráždilová, Katerina Slaninová, Jan Martinovic, Gamila Obadi, Václav Snášel, "Creation of Students' Activities from Learning Management System and their Analysis", CASON, 2009, Computational Aspects of Social Networks, International Conference on, Computational Aspects of Social Networks, International Conference on 2009, pp. 155-160, doi:10.1109/CASoN.2009.34