Endowing a Robotic Tutor with Empathic Qualities: Design and Pilot Evaluation

Abstract

As increasingly more research efforts are geared towards creating robots that can teach and interact with children in educational contexts, it has been speculated that endowing robots with artificial empathy may facilitate learning. In this paper, we provide a background to the concept of empathy, and how it factors into learning. We then present our approach to equipping a robotic tutor with several empathic qualities, describing the technical architecture and its components, a map-reading learning scenario developed for an interactive multitouch table, as well as the pedagogical and empathic strategies devised for the robot. We also describe the results of a pilot study comparing the robotic tutor with these empathic qualities against a version of the tutor without them. The pilot study was performed with 26 school children aged 10–11 at their school. Results revealed that children in the test condition indeed rated the robot as more empathic than children in the control condition. Moreover, we explored several related measures, such as relational status and learning effect, yet no other significant differences were found. We further discuss these results and provide insights into future directions.

“Danger, Will Robinson!” The challenges of social robots for intergroup relations

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Trouble and Repair in Child–Robot Interaction: A Study of Complex Interactions With a Robot Tutee in a Primary School Classroom

“…Over the past decades, research has explored the possibility of using social robots in a range of educational roles, including as teachers and tutors, peers, and novices (Belpaeme et al, 2018 ). For instance, the EMOTE project developed a robot with empathic qualities, which could tutor primary school students on tasks related to geography and sustainable development (Serholt and Barendregt, 2016 ; Obaid et al, 2018 ; Alves-Oliveira et al, 2019 ), the L2TOR project developed a robot that could tutor preschool children on second language learning (Vogt et al, 2019 ), whereas the CoWriter project developed a robot in the role of a novice, which children could teach handwriting skills to (El-Hamamsy et al, 2019 ). The motivations behind these efforts range from explorations of robots as technologies for supporting children's learning [e.g., language learning (Kory-Westlund and Breazeal, 2019 )] and the development of targeted skills [e.g., self-regulated learning (Jones and Castellano, 2018 )], to a conception of robots as solutions to various educational challenges, such as teachers' workload (Movellan et al, 2005 ) and a global teacher shortage (Edwards and Cheok, 2018 ).…”

From Affect Theoretical Foundations to Computational Models of Intelligent Affective Agents

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