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Analysis and Visualization of Relations in eLearning

Pavla Drázdilová, Gamila Obadi, Kateřina Slaninová, Jan Martinovič, Václav Snásel
Zu finden in: Computational Social Network Analysis, 2009   
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The popularity of eLearning systems is growing rapidly; this growth is enabled by the consecutive development in Internet and multimedia technologies. Web-based education became wide spread in the past few years. Various types of learning management systems facilitate development of Web-based courses. Users of these courses form social networks through the different activities performed by them. This chapter focuses on searching the latent social networks in eLearning systems data. These data consist of students activity records wherein latent ties among actors are embedded. The social network studied in this chapter is represented by groups of students who have similar contacts and interact in similar social circles. Different methods of data clustering analysis can be applied to these groups, and the findings show the existence of latent ties among the group members. The second part of this chapter 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 as well as the amount of independent groups in a given network. When applied to the field of eLearning, data visualization simplifies the process of monitoring the study activities of individuals or groups, as well as the planning of educational curriculum, the evaluation of study processes, etc.
Von Pavla Drázdilová, Gamila Obadi, Kateřina Slaninová, Jan Martinovič, Václav Snásel im Buch Computational Social Network Analysis (2009) im Text Analysis and Visualization of Relations in eLearning

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