Using physiological responses to capture unique idea creation in team collaborations

Kira Furuichi, Marcelo Worsley

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

2 Scopus citations

Abstract

The rise of multimodal learning analytics (MMLA) gives opportunity to learn about teamwork and collaboration through detailed physiological responses, with the aid of multimodal tools. The primary goal of this study is to determine if unique idea creation, or secondary agreement to unique ideas, in group collaboration can be distinguished through one’s physiological responses. In this pilot study participants who presented new ideas demonstrated higher levels of galvanic skin response, indicative of engagement, emotional arousal or cognitive load.

Original languageEnglish (US)
Title of host publicationCSCW 2018 Companion - Companion of the 2018 ACM Conference on Computer Supported Cooperative Work and Social Computing
PublisherAssociation for Computing Machinery
Pages369-372
Number of pages4
ISBN (Electronic)9781450360180
DOIs
StatePublished - Oct 30 2018
Event21st ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2018 - Jersey City, United States
Duration: Nov 3 2018Nov 7 2018

Publication series

NameProceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW

Other

Other21st ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2018
CountryUnited States
CityJersey City
Period11/3/1811/7/18

Keywords

  • Idea creation
  • Multimodal learning analytics
  • Skin conductance
  • Team collaboration

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Human-Computer Interaction

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  • Cite this

    Furuichi, K., & Worsley, M. (2018). Using physiological responses to capture unique idea creation in team collaborations. In CSCW 2018 Companion - Companion of the 2018 ACM Conference on Computer Supported Cooperative Work and Social Computing (pp. 369-372). (Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW). Association for Computing Machinery. https://doi.org/10.1145/3272973.3274099