Wiring Role Taking in Collaborative Learning Environments. SNA and Semantic Web can improve CSCL script?


  • Nicola Capuano University of Salerno
  • Giuseppina Rita Mangione University of Salerno
  • Elvis Mazzoni University of Bologna
  • Sergio Miranda University of Salerno
  • Francesco Orciuoli University of Salerno




social network analysis, role management, learner profile, e-learning, learning design


Over the past years the concept of role in distance education has become a promising construct for analysing and facilitating collaborative processes and outcomes. Designing effective collaborative learning processes is a complex task that can be supported by existing good practices formulated as pedagogical patterns or scripts. Over the past years, the research on technology enhanced learning has shown that collaborative scripts for learning act as mediating artefacts not only designing educational scenarios but also structuring and prescribing roles and activities. Conversely, existing learning systems are not able to provide dynamic role management in the definition and execution of collaborative scripts. This work proposes the application of Social Network Analysis in order to evaluate the expertise level of a learner when he/she is acting, with an assigned role, within the execution of a collaborative script. Semantic extensions to both IMS Learning Design and Information Packaging specifications are also proposed to support roles management.

Author Biographies

Nicola Capuano, University of Salerno

DIEM, Scientific Officer

Giuseppina Rita Mangione, University of Salerno

DIEM, Research Assistant

Elvis Mazzoni, University of Bologna

S.E.Fo.R.A. Lab

Sergio Miranda, University of Salerno

DIEM, Scientific Officer

Francesco Orciuoli, University of Salerno

DIEM, Assistant Professor




How to Cite

Capuano, N., Mangione, G. R., Mazzoni, E., Miranda, S., & Orciuoli, F. (2014). Wiring Role Taking in Collaborative Learning Environments. SNA and Semantic Web can improve CSCL script?. International Journal of Emerging Technologies in Learning (iJET), 9(7), pp. 30–38. https://doi.org/10.3991/ijet.v9i7.3719