Exploring requirements and opportunities for social robots in primary mathematics education

Abstract

Robot personality design is an essential aspect in Social Robotics, where humans and robots interact in a social context. Social robots with expressive behaviors can demonstrate human-like behaviors through voice, speech, gestures, and non-verbal cues. This study focuses on designing robot personalities based on non-verbal cues. More specifically, we investigate how human experts in movement analysis perceive different personalities of robots (introvert vs. extrovert) based on the robot’s movement and other dynamic features, e.g., the position of joints, head and torso, voice pitch, speed, etc. We present our results from a thematic analysis of the data collected during the focus group with the movement analysis experts who observed designed extrovert and introvert robot personalities performed by a Pepper robot. Our findings result in guidelines on designing different robot movement features, emphasizing body symmetry, consistency and congruence during the interaction emphasized by the movement analysts. These are not found in the existing literature. Based on the focus group findings and literature study, we summarise the design guidelines for extrovert and introvert robot behaviors in a social context.