Robots educate in style: The effect of context and non-verbal behaviour on children's perceptions of warmth and competence

Abstract

Social robots are entering the private and public domain where they engage in social interactions with nontechnical users. This requires robots to be socially interactive and intelligent, including the ability to display appropriate social behaviour. Progress has been made in emotion modelling. However, research into behaviour style is less thorough; no comprehensive, validated model exists of non-verbal behaviours to express style in human-robot interactions. Based on a literature survey, we created a model of non-verbal behaviour to express high/low warmth and competence — two dimensions that contribute to teaching style. In a perception study, we evaluated this model applied to a NAO robot giving a lecture at primary schools and a diabetes camp in the Netherlands. For this, we developed, based on expert ratings, an instrument measuring perceived warmth, competence, dominance and affiliation. We show that even subtle manipulations of robot behaviour influence children's perceptions of the robot's level of warmth and competence.