Human-Robot Teaming Configurations: A Study of Interpersonal Communication Perceptions and Affective Learning in Higher Education

Abstract

Technology encourages collaboration in creative ways in the classroom. Specifically, social robots may offer new opportunities for greater innovation in teaching. In this study, we combined the established literature on co-teaching teams with the developing field of machine actors used in education to investigate the impressions students had of different team configurations that included both a human and a robot. Participants (N = 215, age: M = 24, SD = 8.67, range 18–69) saw one of three teams composed of a human and a social robot with different responsibilities present a short, prerecorded lecture (i.e., human as lead teacher-robot as teaching assistant, robot as lead teacher-human as teaching assistant, human and robot as co-teachers). Overall, students rated the human-led team as more appealing and having more credibility than the robot-led team. The data suggest that participants would be more likely to take a course led by a human instructor than a social robot. Previous studies have investigated machine actors in the classroom, but the current findings are unique in that they compare the individual roles and power structures of human-robot teams leading a course.