Online team-based game development discussions patterns summarised using probabilistic models

Akiko Teranishi, Minoru Nakayama, Theodor Wyeld, Eid A. Mohamad

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

Abstract

Communications between team members sent as messages about collaboration strategies during online game development were analysed to extract contributions to the discussion of their online activity and their reflections. The task was the collaborative development of online games by a team of university students. Their social media communications were classified into four functions: Proposal, Permission, Encouragement, and Acknowledgement based on the participant's frequency of contribution of reflections and the frequency of their communication activity. In the results, some significant relationships between participant's reflections and communication frequencies of the four categories were extracted in the later discussion cycles. Also, the appearance probabilities of communication activity in each of the four categories were calculated using Bayesian networks and the scores of participant's characteristics, such as personality and information literacy.

Original languageEnglish (US)
Title of host publicationProceedings of the 33rd Annual ACM Symposium on Applied Computing, SAC 2018
PublisherAssociation for Computing Machinery
Pages234-239
Number of pages6
ISBN (Electronic)9781450351911
DOIs
StatePublished - Apr 9 2018
Event33rd Annual ACM Symposium on Applied Computing, SAC 2018 - Pau, France
Duration: Apr 9 2018Apr 13 2018

Publication series

NameProceedings of the ACM Symposium on Applied Computing

Other

Other33rd Annual ACM Symposium on Applied Computing, SAC 2018
CountryFrance
CityPau
Period4/9/184/13/18

Keywords

  • Computer based learning
  • Discourse analysis
  • Self assessment
  • Transitional analysis

ASJC Scopus subject areas

  • Software

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  • Cite this

    Teranishi, A., Nakayama, M., Wyeld, T., & Mohamad, E. A. (2018). Online team-based game development discussions patterns summarised using probabilistic models. In Proceedings of the 33rd Annual ACM Symposium on Applied Computing, SAC 2018 (pp. 234-239). (Proceedings of the ACM Symposium on Applied Computing). Association for Computing Machinery. https://doi.org/10.1145/3167132.3167169