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Using indirect blockmodeling for monitoring students roles in collaborative learning networks
Univ Politecn Cataluna, Dept Comp Architecture, Barcelona, Spain.
Univ Politecn Cataluna, Dept Comp Architecture, Barcelona, Spain.
Univ Politecn Cataluna, Dept Comp Architecture, Barcelona, Spain.
Coventry Univ, Dept Aerosp Elect & Elect Engn, Coventry, W Midlands, England.
Vise andre og tillknytning
2016 (engelsk)Inngår i: 2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design (CSCWD) / [ed] Shen, W; Liu, X; Yang, C; Barthes, JP; Luo, J; Chen, L; Yong, J, 2016, s. 164-169Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Collaborative learning activities have shown to be useful to address educational processes in several contexts. Monitoring these activities is mandatory to determine the quality of the collaboration and learning processes. Recent research works propose using Social Network Analysis techniques to understand students' collaboration learning process during these experiences. Aligned with that, this paper proposes the use of the indirect blockmodeling network analytic technique for monitoring the behaviour of different social roles played by students in collaborative learning scenarios. The usefulness of this technique was evaluated through a study that analysed the students' interaction network in a collaborative learning activity. Particularly, we tried to understand the structure of the interaction network during that process. Preliminary results suggest that indirect blockmodeling is highly useful for inferring and analysing the students' social roles, when the behaviour of roles are clearly different among them. This technique can be used as a monitoring service that can be embedded in collaborative learning applications.

sted, utgiver, år, opplag, sider
2016. s. 164-169
Serie
International Conference on Computer Supported Cooperative Work in Design
Emneord [en]
Indirect blockmodeling, collaborative learning, learning monitoring, role detection, social network analysis
HSV kategori
Identifikatorer
URN: urn:nbn:se:uu:diva-310044ISI: 000389305700033ISBN: 9781509019151 (tryckt)OAI: oai:DiVA.org:uu-310044DiVA, id: diva2:1054765
Konferanse
2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design (CSCWD), Nanchang, PEOPLES R CHINA, MAY 04-06, 2016
Tilgjengelig fra: 2016-12-09 Laget: 2016-12-09 Sist oppdatert: 2018-01-13bibliografisk kontrollert

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