The Network Structure of Interactions in Online Social Learning Environments

The widespread use of computing and communications technologies has also arrived at the education field, an area where general and custom-designed online social networking software platforms are being increasingly employed in formal course offerings at all education levels. Despite the widespread use of open online social networks (OSN), the relationship between the social ties among students and their academic performance is not yet well understood. In this chapter, we report on a longitudinal experiment with a purpose-specific OSN run at the graduate level and apply a structural analysis of the students’ network. We show that some of the basic structural properties in these networks (e.g., centrality, community structure, reciprocity, egonetworks) are correlated with the final outcome and grades of the students. Thus, social network analysis during the instruction period can be effectively used to classify, rank and identify types of students according to the intensity, quality and engagement into the OSN. These features and the network structure are plausible variables to predict their ultimate academic achievements, too. Our analysis contributes to the understanding of the role of social learning among highly educated students.