Implicit and explicit learning of socio-emotional information in a dynamic system control task
Unconscious or, implicit learning (IL) is often described as being instrumental to human social functioning. However, most of the available IL tasks have limited external validity; they use surface stimuli that are not socially relevant. Additionally, the way in which participants exchange information within most of the available tasks departs from the way in which information is being exchanged in real-life social situations. In this study, we report the validation of a novel task, inspired from Broadbent et al. (1984), assessing the implicit and explicit learning of socio-emotional information in a dynamic environment. Participants (N=115) interacted with an animated virtual avatar that displayed different levels of emotional facial expressions. Their task was to regulate the avatar’s facial expression to a specified level. Unknown to them, the relationship between their inputs and the avatar’s state was mediated by an abstract rule. Results indicate that learning occurred in the task, as participants gradually increased their ability to bring the avatar in the target state. We found evidence for both explicit (consciously knowing the appropriate response) and implicit (knowing the correct responses even when based on subjectively defined unconscious mental states) knowledge acquisition. This is one of the first studies to propose a task for studying the role of IL in interactive social situations. Implications for future research are discussed.