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Children's learning-by-teaching with a social robot versus a younger child: Comparing interactions and tutoring styles.
University West, School of Business, Economics and IT, Division of Media and Design. Department of Education, Communication and Learning, University of Gothenburg, Gothenburg (SWE). (LINA)ORCID iD: 0000-0002-5996-7668
University West, School of Business, Economics and IT, Division of Media and Design.ORCID iD: 0000-0002-9399-0159
Division of Learning, Communication and IT, Department of Applied IT, University of Gothenburg, Gothenburg (SWE).
2022 (English)In: Frontiers in Robotics and AI, E-ISSN 2296-9144, Vol. 9, article id 875704Article in journal (Refereed) Published
Abstract [en]

Human peer tutoring is known to be effective for learning, and social robots are currently being explored for robot-assisted peer tutoring. In peer tutoring, not only the tutee but also the tutor benefit from the activity. Exploiting the learning-by-teaching mechanism, robots as tutees can be a promising approach for tutor learning. This study compares robots and humans by examining children's learning-by-teaching with a social robot and younger children, respectively. The study comprised a small-scale field experiment in a Swedish primary school, following a within-subject design. Ten sixth-grade students (age 12-13) assigned as tutors conducted two 30 min peer tutoring sessions each, one with a robot tutee and one with a third-grade student (age 9-10) as the tutee. The tutoring task consisted of teaching the tutee to play a two-player educational game designed to promote conceptual understanding and mathematical thinking. The tutoring sessions were video recorded, and verbal actions were transcribed and extended with crucial game actions and user gestures, to explore differences in interaction patterns between the two conditions. An extension to the classical initiation-response-feedback framework for classroom interactions, the IRFCE tutoring framework, was modified and used as an analytic lens. Actors, tutoring actions, and teaching interactions were examined and coded as they unfolded in the respective child-robot and child-child interactions during the sessions. Significant differences between the robot tutee and child tutee conditions regarding action frequencies and characteristics were found, concerning tutee initiatives, tutee questions, tutor explanations, tutee involvement, and evaluation feedback. We have identified ample opportunities for the tutor to learn from teaching in both conditions, for different reasons. The child tutee condition provided opportunities to engage in explanations to the tutee, experience smooth collaboration, and gain motivation through social responsibility for the younger child. The robot tutee condition provided opportunities to answer challenging questions from the tutee, receive plenty of feedback, and communicate using mathematical language. Hence, both conditions provide good learning opportunities for a tutor, but in different ways.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2022. Vol. 9, article id 875704
Keywords [en]
child–robot interaction, comparative study, learning-by-teaching, mathematics game, peer tutoring, robot tutee, robot versus human, video analysis
National Category
Human Aspects of ICT
Research subject
Work Integrated Learning
Identifiers
URN: urn:nbn:se:hv:diva-19421DOI: 10.3389/frobt.2022.875704ISI: 000885048100001PubMedID: 36388256Scopus ID: 2-s2.0-85142005734OAI: oai:DiVA.org:hv-19421DiVA, id: diva2:1721691
Note

This work was partially supported by the Marcus and Amalia Wallenberg Foundation through the project START (Student Tutorand Robot Tutee) MAW 2016.0117 and partially by the Swedish Research Council through the national research school GRADE (GRAduate school for Digital technologies in Education), grant 2017-03687. The authors are solely responsible for the content ofthis publication. It does not represent the opinion of the funders, andthe Wallenberg Foundation and Swedish Research Council are not responsible for any use that might be made of data appearing therein.

This is an open-access articledistributed under the terms of the Creative Commons Attribution License(CC BY).

Available from: 2022-12-22 Created: 2022-12-22 Last updated: 2022-12-22

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Pareto, LenaEkström, Sara

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