ReaderBench: Automated evaluation of collaboration based on cohesion and dialogism

Mihai Dascalu, Stefan Trausan-Matu, Danielle McNamara, Philippe Dessus

Research output: Contribution to journalArticle

33 Scopus citations

Abstract

As Computer-Supported Collaborative Learning (CSCL) gains a broader usage, the need for automated tools capable of supporting tutors in the time-consuming process of analyzing conversations becomes more pressing. Moreover, collaboration, which presumes the intertwining of ideas or points of view among participants, is a central element of dialogue performed in CSCL environments. Therefore, starting from dialogism and a cohesion-based model of discourse, we propose and validate two computational models for assessing collaboration. The first model is based on a cohesion graph and can be perceived as a longitudinal analysis of the ongoing conversation, thus accounting for collaboration from a social knowledge-building perspective. In the second approach, collaboration is regarded from a dialogical perspective as the intertwining or synergy of voices pertaining to different speakers, therefore enabling a transversal analysis of subsequent discussion slices.

Original languageEnglish (US)
Pages (from-to)395-423
Number of pages29
JournalInternational Journal of Computer-Supported Collaborative Learning
Volume10
Issue number4
DOIs
StatePublished - Dec 1 2015

Keywords

  • Automated feedback
  • Cohesion-based discourse analysis
  • Collaboration assessment
  • Computer supported collaborative learning
  • Dialogism
  • Learning analytics

ASJC Scopus subject areas

  • Education
  • Human-Computer Interaction

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