A Group Recommender System for Avatars in Exergames to Increase Physical Activity

Abstract

This research investigates the potential effect of a group recommender system for avatars on users’ physical activity during the gameplay of an exergame. This study aims to counteract the effects of the increase in sedentary time and decrease of physical activity in people by trying to increase physical activity during the gameplay of an exergame while maintaining or even increasinging engagement and satisfaction of the users with the game. The research questions in this research test the influence of a group recommender system on participants’ heart rate, perceived experience, perceived fairness, and perceived difference in the ability of the avatars while playing the game Mario Tennis Aces on the Nintendo Switch console. The group recommender system aims to link a group of users with avatars by recommending avatars that best represent the users’ abilities. The results indicate that the group recommender system increases participants’ heart rate compared to a setting where the users chose the avatar themselves, indicating higher physical activity during gameplay. Moreover, no significant differences in perceived experience, fairness, or difference in ability can be found, which suggests that the recommender system does not affect participants’ engagement and satisfaction with the game.