Social Robots in Applied Settings: A Long-Term Study on Adaptive Robotic Tutors in Higher Education

• Published in: Frontiers in robotics and AI Vol. 9; p. 831633
• Main Authors: Donnermann, Melissa, Schaper, Philipp, Lugrin, Birgit
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 15.03.2022
• Subjects: adaptive tutoring; higher education; human–robot interaction; robot-supported training; robotic tutor; Robotics and AI; technology-supported education; adaptive tutoring; technology-supported education; higher education; robot-supported training; robotic tutor; human–robot interaction
• ISSN: 2296-9144; 2296-9144
• DOI: 10.3389/frobt.2022.831633

Learning in higher education scenarios requires self-directed learning and the challenging task of self-motivation while individual support is rare. The integration of social robots to support learners has already shown promise to benefit the learning process in this area. In this paper, we focus on the applicability of an adaptive robotic tutor in a university setting. To this end, we conducted a long-term field study implementing an adaptive robotic tutor to support students with exam preparation over three sessions during one semester. In a mixed design, we compared the effect of an adaptive tutor to a control condition across all learning sessions. With the aim to benefit not only motivation but also academic success and the learning experience in general, we draw from research in adaptive tutoring, social robots in education, as well as our own prior work in this field. Our results show that opting in for the robotic tutoring is beneficial for students. We found significant subjective knowledge gain and increases in intrinsic motivation regarding the content of the course in general. Finally, participation resulted in a significantly better exam grade compared to students not participating. However, the extended adaptivity of the robotic tutor in the experimental condition did not seem to enhance learning, as we found no significant differences compared to a non-adaptive version of the robot.