Effects of Valence and Arousal on Working Memory Performance in Virtual Reality Gaming
Proceedings of the Seventh International Conference on Affective Computing and Intelligent Interaction
Seventh International Conference on Affective Computing and Intelligent Interaction
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Gabana, D., Tokarchuk, L., Hannon, E., & Gunes, H. (2017). Effects of Valence and Arousal on Working Memory Performance in Virtual Reality Gaming. Proceedings of the Seventh International Conference on Affective Computing and Intelligent Interaction https://doi.org/10.1109/ACII.2017.8273576
The role of affective states in cognitive performance has long been an area of interest in cognitive science. Recent research in game-based cognitive training suggest that cognitive games should incorporate real-time adaptive mechanisms. These adaptive mechanisms would change the game’s difficulty according to the player’s performance in order to provide appropriate challenges and thus, achieve a real cognitive improvement. However, these mechanisms currently ignore the effects of valence and arousal on the player’s cognitive skills. In this paper we investigate how working memory (WM) performance is affected when playing a VR game, and the effects of valence and arousal in this context. To this aim, a custom video game was created for Desktop and VR. Three difficulty levels were designed to evoke different levels of arousal while maintaining the same memory load for each difficulty level. We found an improvement in WM performance when playing in VR compared to Desktop. This effect was particularly pronounced in those with a low WM capacity. Significantly higher levels of valence and arousal were self-reported when playing in VR.We explore the impact that reported affective states could have in the player’s WM performance. We suggest that high levels of arousal and positive valence can lead players to a flow state  that may have a positive impact on the player’s WM performance.
This work is supported by Queen Mary University of London and EPSRC Media and Arts Technology Doctoral Training Centre (EP/G03723X/1).
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External DOI: https://doi.org/10.1109/ACII.2017.8273576
This record's URL: https://www.repository.cam.ac.uk/handle/1810/270031