Critical Thinker: Supporting Collaborative Argumentation with Structure and Awareness

Na Sun, Chien Wen Yuan, Mary Beth Rosson, Yu Wu, John Carroll

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Collaborative learning technology has been widely applied in various disciplines in support of dialectical discourse and argumentation. Technologies not only allow multiple users to concurrently analyze and edit documents in the same virtual space but also present richer cues for collaboration awareness. However, researchers still know very little about how the synching mechanisms work together to support small group collaborative argument creation. This study investigates the experiences of 14 dyads that worked together in Critical Thinker, a web application that enables learners to collaborate on an argumentative task with a juxtaposed argumentation structure and multiple synchronous collaboration affordances. Our qualitative data showed that the learners are able to leverage different synching mechanisms in a complementary manner and appropriate the dialectic structure for collaborative argumentation.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages406-410
Number of pages5
ISBN (Electronic)9781538638705
DOIs
StatePublished - Aug 3 2017
Event17th IEEE International Conference on Advanced Learning Technologies, ICALT 2017 - Timisoara
Duration: Jul 3 2017Jul 7 2017

Other

Other17th IEEE International Conference on Advanced Learning Technologies, ICALT 2017
CityTimisoara
Period7/3/177/7/17

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All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Education

Cite this

Sun, N., Yuan, C. W., Rosson, M. B., Wu, Y., & Carroll, J. (2017). Critical Thinker: Supporting Collaborative Argumentation with Structure and Awareness. In Proceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017 (pp. 406-410). [8001818] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICALT.2017.61