The Impact of Robot Tutor Nonverbal Social Behavior on Child Learning

Abstract

Several studies have indicated that interacting with social robots in educational contexts may lead to greater learning than interactions with computers or virtual agents. As such, an increasing amount of social human-robot interaction research is being conducted in the learning domain, particularly with children. However, it is unclear precisely what social behaviour a robot should employ in such interactions. Inspiration can be taken from human-human studies; this often leads to an assumption that the more social behaviour an agent utilises, the better the learning outcome will be. We apply a nonverbal behaviour metric to a series of studies in which children are taught how to identify prime numbers by a robot with various behavioural manipulations. We find a trend which generally agrees with the pedagogy literature, but also that overt nonverbal behaviour does not account for all learning differences. We discuss the impact of novelty, child expectations, and responses to social cues to further the understanding of the relationship between robot social behaviour and learning. We suggest that the combination of nonverbal behaviour and social cue congruency is necessary to facilitate learning.