During the last decades, social and computer scientists have been focusing their efforts to study the effectiveness of collaboration in both working and learning environments. The main contributions clearly identify the importance of interactivity as the determinant of positive performances in learning communities where the supportive dimension of exchanges is balanced by the interactive one. In this chapter, authors describe a method based on social network metrics to recognize the stages of development of learning communities. The authors found that the evolution of social network metrics - such as density, betweenness centrality, contribution index, core/periphery structure - matched the formal stages of community development, with a clear identification of the forming, norming, and storming phases.
Observing the Evolution of a Learning Community Using Social Network Analysis
CORALLO, Angelo;DE MAGGIO, MARCO;GRIPPA, FRANCESCA
2011-01-01
Abstract
During the last decades, social and computer scientists have been focusing their efforts to study the effectiveness of collaboration in both working and learning environments. The main contributions clearly identify the importance of interactivity as the determinant of positive performances in learning communities where the supportive dimension of exchanges is balanced by the interactive one. In this chapter, authors describe a method based on social network metrics to recognize the stages of development of learning communities. The authors found that the evolution of social network metrics - such as density, betweenness centrality, contribution index, core/periphery structure - matched the formal stages of community development, with a clear identification of the forming, norming, and storming phases.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
