How to manage affective state in child-robot tutoring interactions?

Abstract

Social robots represent a fruitful enhancement of intelligent tutoring systems that can be used for one-to-one tutoring. The role of affective states during learning has so far only scarcely been considered in such systems, because it is unclear which cues should be tracked, how they should be interpreted, and how the system should react to them. Therefore, we conducted expert interviews with preschool teachers, and based on these results suggest a conceptual model for tracing and managing the affective state of preschool children during robot-child tutoring.