Race Yourselves: A Longitudinal Exploration of Self-Competition Between Past, Present, and Future Performances in a VR Exergame

Alexander Michael, Christof Lutteroth

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

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Abstract

Participating in competitive races can be a thrilling experience for athletes, involving a rush of excitement and sensations of flow, achievement, and self-fulfilment. However, for non-athletes, the prospect of competition is often a scary one which affects intrinsic motivation negatively, especially for less fit, less competitive individuals. We propose a novel method making the positive racing experience accessible to non-athletes using a high-intensity cycling VR exergame: by recording and replaying all their previous gameplay sessions simultaneously, including a projected future performance, players can race against a crowd of "ghost" avatars representing their individual fitness journey. The experience stays relevant and exciting as every race adds a new competitor. A longitudinal study over four weeks and a cross-sectional study found that the new method improves physical performance, intrinsic motivation, and flow compared to a non-competitive exergame. Additionally, the longitudinal study provides insights into the longer-term effects of VR exergames.
Original languageEnglish
Title of host publicationProceedings of the 2020 CHI Conference on Human Factors in Computing Systems
Place of PublicationNew York, USA
PublisherAssociation for Computing Machinery
Number of pages17
Volume2020-April
ISBN (Electronic)9781450367080
Publication statusAcceptance date - 16 Jan 2020

Publication series

NameCHI Conference on Human Factors and Computing Systems
PublisherACM Press
ISSN (Electronic)1062-9432

Projects

Cite this

Michael, A., & Lutteroth, C. (Accepted/In press). Race Yourselves: A Longitudinal Exploration of Self-Competition Between Past, Present, and Future Performances in a VR Exergame. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Vol. 2020-April). (CHI Conference on Human Factors and Computing Systems). Association for Computing Machinery.