Social network analysis used for modelling collaboration in Distance Learning groups

Christophe Reffay , Thierry Chanier

We describe a situation of distance learning based on collaborative production occurring within groups over a significant time span. For such a situation, we suggest giving priority to monitoring and not to guiding systems. We also argue that we need models which are easily computable in order to deal with the heterogeneous and the large scale amount of data related to interactions, i.e. models relying on theoretical assumptions which characterise the structures of groups and of interactions. Social Network Analysis is a good candidate we applied to our experiment in order to compute communication graphs and cohesion factors in groups. This application represents an essential part of a system which would enable tutors to detect a problem or a slowdown of group interaction.

Mots clés: Education—Data processing ; Computer-assisted instruction ; Distance education; Educational technologies ; Information and communications technology ; Distance education; Education/ Computer-assisted education ; Education/ Distance education

Mots clés: Education et informatique ; Enseignement assisté par ordinateur ; Nouvelles technologies de l'information et de la communication ; Enseignement à distance

Domaines: Education

Christophe Reffay, Thierry Chanier. Social network analysis used for modelling collaboration in Distance Learning groups. Intelligent Tutoring System, Jun 2002, Biarritz and San Sebastian, France. pp.31-40. ⟨edutice-00000056⟩