Motivation through gamification: A Self-Determination Theory perspective for the design of an adaptive reward system
Publication date
2022
Editors
Barbosa, Simone
Lampe, Cliff
Appert, Caroline
Shamma, David A.
Drucker, Steven
Williamson, Julie
Yatani, Koji
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Supervisors
DOI
Document Type
Part of book
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Abstract
Research on the nature and origins of human motivation has addressed the role of rewards in learning and behaviour. Gamification finds its raison d'être in being able to leverage motivational theories, to foster motivation in users through the use of game elements. One of the main criticisms moved to the use of gamification for learning purposes is related to the one-size-fits-all approach that tends to characterize many gamified applications. In this paper we explore the possibilities that can arise from the convergence of Self-Determination Theory principles and machine learning, to improve the efficacy of gamification reward systems.
Keywords
Human-centered computing, Human Computer Interaction, HCI theory, concepts and models, Gamification, Self-Determination Theory, Adaptive rewards
Citation
Botte, B, Aarts, H, Bakkes, S C J & Veltkamp, R C 2022, Motivation through gamification : A Self-Determination Theory perspective for the design of an adaptive reward system. in S Barbosa, C Lampe, C Appert, D A Shamma, S Drucker, J Williamson & K Yatani (eds), CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery. < https://webspace.science.uu.nl/~veltk101/publications/art/chi2022-sdtws.pdf >