Interindividual differences in the relationship of emotion and performance in safety-critical systems
Lecturer: Alina Schmitz-Hübsch (University of Stuttgart, Institute of Educational Science)
Date: 15.03.2022, 14:00-15:00
Abstract: Affect-adaptive systems detect the emotional user state, assess it against the current situation, and adjust interaction accordingly. Safety-critical systems, in which wrong decisions and behavior can have fatal consequences, may particularly benefit from affect-adaptive systems because accounting for affecting responses may help promote high performance of the human-machine-system. Effective adaptation, however, can only be accomplished when knowing which emotions benefit high performance in such systems. The results of preliminary studies indicate interindividual differences in the relationship between emotion and performance that require consideration by an affect-adaptive system. To that end, this talk introduces the concept of Affective Response Categories (ARCs) that can be used to categorize learners based on their emotion-performance relationship. In an experimental study, N = 50 subjects (33% female, 19-57 years, M = 32.75, SD = 9.8) performed a simulated airspace surveillance task. Emotional valence was detected using facial expression analysis, and pupil dilation was used to indicate emotional arousal. A cluster analysis was performed in order to group subjects into ARCs based on their individual correlations of valence and performance as well as arousal and performance. Three different clusters were identified, one of which showed no correlations between emotion and performance. The performance of subjects in all other clusters benefited from negative arousal and differed only in the valence-performance correlation, which was positive or negative. Implications for the larger context of the field of adaptive systems as well as potential benefits of the proposed concept will be discussed.