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Creating Student Interaction Profiles for Adaptive Collaboration Gamification Design

Author

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  • Antti Knutas

    (Lappeenranta University of Technology, Lappeenranta, Finland)

  • Jouni Ikonen

    (Lappeenranta University of Technology, Lappeenranta, Finland)

  • Dario Maggiorini

    (Università di Milano, Milan, Italy)

  • Laura Ripamonti

    (Università di Milano, Milan, Italy)

  • Jari Porras

    (Lappeenranta University of Technology, Lappeenranta, Finland)

Abstract

Benefits of collaborative learning are established and gamification methods have been used to motivate students towards achieving course goals in educational settings. However, different users prefer different game elements and rewarding approaches and static gamification approaches can be inefficient. The authors present an evidence-based method and a case study where interaction analysis and k-means clustering are used to create gamification preference profiles. These profiles can be used to create adaptive gamification approaches for online learning or collaborative learning environments, improving on static gamification designs. Furthermore, the authors discuss possibilities for using our approach in collaborative online learning environments.

Suggested Citation

  • Antti Knutas & Jouni Ikonen & Dario Maggiorini & Laura Ripamonti & Jari Porras, 2016. "Creating Student Interaction Profiles for Adaptive Collaboration Gamification Design," International Journal of Human Capital and Information Technology Professionals (IJHCITP), IGI Global, vol. 7(3), pages 47-62, July.
  • Handle: RePEc:igg:jhcitp:v:7:y:2016:i:3:p:47-62
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    Cited by:

    1. Sungjin Park & Sangkyun Kim, 2022. "Learning Performance Styles in Gamified College Classes Using Data Clustering," Sustainability, MDPI, vol. 14(23), pages 1-13, November.

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