On the equivalence between bimodal and unimodal students’ collaboration networks in distance learning

Abstract

This work is aiming to contribute to the field of Distance Learning through Learning Analytics. We propose a methodological framework based on network analysis metrics to provide multiple indicators for Course Learning Analytics. Social Network Analysis is proposed for this purpose due to its capacity to provide an integrated representation of students’ interaction, where individual behavior is expressed within the context of a learning community. We perform experimental evaluation on real-life data from anonymized forum posts of postgraduate students and their tutors in the School of Science and Technology at the Hellenic Open University. Initially, we create and examine two-mode networks (participant-discussion) for two different modules. Subsequently, these networks are transformed into one-mode networks. Key measures are estimated and compared and the differences between their pedagogical interpretations are highlighted. We conclude that the choice between working with a bimodal network or projecting it into a unimodal one is determined by the nature of the research questions because of the distinct features that each one of them exhibits.