Suchergebnisse

Evidence shows that emotions critically influence human decision-making. Therefore, emotion-regulation using biofeedback has been extensively investigated. Nevertheless, serious games have emerged as a valuable tool for such investigations set in the decision-making context. This review sets out to investigate the scientific evidence regarding the effects of practicing emotion-regulation through biofeedback on the decision-making performance in the context of serious games. A systematic search of five electronic databases (Scopus, Web of Science, IEEE, PubMed Central, Science Direct), followed by the author and snowballing investigation, was conducted from a publication's year of inception to October 2018. The search identified 16 randomized controlled experiment/quasi-experiment studies that quantitatively assessed the performance on decision-making tasks in serious games, involving students, military, and brain-injured participants. It was found that the participants who raised awareness of emotions and increased the skill of emotion-regulation were able to successfully regulate their arousal, which resulted in better decision performance, reaction time, and attention scores on the decision-making tasks. It is suggested that serious games provide an effective platform validated through the evaluative and playtesting studies, that supports the acquisition of the emotion-regulation skill through the direct (visual) and indirect (gameplay) biofeedback presentation on decision-making tasks. ; open access

Research on financial decision-making shows that traders and investors with high emotion regulation capabilities perform better in trading. But how can the others learn to regulate their emotions? 'Learning by doing' sounds like a straightforward approach. But how can one perform 'learning by doing' when there is no feedback? This problem particularly applies to learning emotion regulation, because learners can get practically no feedback on their level of emotion regulation. Our research aims at providing a learning environment that can help decision-makers to improve their emotion regulation. The approach is based on a serious game with real-time biofeedback. The game is settled in a financial context and the decision scenario is directly linked to the individual biofeedback of the learner's heart rate data. More specifically, depending on the learner's ability to regulate emotions, the decision scenario of the game continuously adjusts and thereby becomes more (or less) difficult. The learner wears an electrocardiogram sensor that transfers the data via Bluetooth to the game. The game itself is evaluated at several levels. ; open access