Using Collaboration Engineering to Mitigate Low Participation, Distraction, and Learning Inefficiency to Support Collaborative Learning in Industry

Xusen Cheng, Shixuan Fu, Gert Jan de Vreede, Yuanyuan Li

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Computer-supported collaborative learning (CSCL) is widely adopted in industry learning, but it still faces challenges, including low participation, distraction, and learning inefficiency. In our study, we follow the design science research method to develop artifacts (a process and discussion platform) to address these CSCL challenges. Collaboration engineering was used as our design theory. A Discussion Platform was designed as a tool to help non-expert practitioner instruct collaborative learning process. We carried out evaluations on the two designed artifacts through 81 managers working in various industries through a mixed-method approach, including survey and qualitative interviews. We find that our designed artifacts receive high satisfaction in industry CSCL and reduce problems of low participation, distraction, and learning inefficiency. We identified several factors that contribute to the problem solving of low participation, distraction and inefficiency in industry CSCL, including usability, expression affordance, process guidance, goal clarity, flexibility affordance, thinkLet instruction, and flow experiences.

Original languageEnglish
Pages (from-to)171-190
Number of pages20
JournalGroup Decision and Negotiation
Volume30
Issue number1
DOIs
StatePublished - Feb 2021

Keywords

  • Attention
  • Collaboration engineering
  • Collaboration support system
  • Computer-supported collaborative learning
  • Efficiency
  • Participation

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