How social network analysis can help to measure cohesion in collaborative distance-learning - HAL-SHS - Sciences de l'Homme et de la Société Accéder directement au contenu
Communication Dans Un Congrès Année : 2003

How social network analysis can help to measure cohesion in collaborative distance-learning

Résumé

It has been argued that cohesion plays a central role in collaborative learning. In face-to-face classes, it can be reckoned from several visual or oral cues. In a Learning Management System or CSCL environment, such cues are absent. In this paper, we show that Social Network Analysis concepts, adapted to the collaborative distance-learning context, can help measuring the cohesion of small groups.
Working on data extracted from a 10-week distance-learning experiment, we computed cohesion in several ways in order to highlight isolated people, active sub-groups and various roles of the members in the group communication structure. We argue that such processing, embodied in monitoring tools, can
display global properties both at individual level and at group level and efficiently assist the tutor in following the collaboration within the group. It seems to be more appropriate than the long and detailed textual analysis of messages and the statistical distribution of participants' contributions.

Mots clés

SNA

Domaines

Education
Fichier principal
Vignette du fichier
reffay_chanier.pdf (192.83 Ko) Télécharger le fichier
Reffay_CSCL2003.ppt (5.23 Mo) Télécharger le fichier
Format : Autre
Loading...

Dates et versions

edutice-00000422 , version 1 (19-04-2004)

Identifiants

  • HAL Id : edutice-00000422 , version 1

Citer

Christophe Reffay, Thierry Chanier. How social network analysis can help to measure cohesion in collaborative distance-learning. Computer Supported Collaborative Learning, Jun 2003, Bergen, Norway. pp.343-352. ⟨edutice-00000422⟩
504 Consultations
3350 Téléchargements

Partager

Gmail Facebook X LinkedIn More