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Designing and Evaluating Iconic Gestures for Child-Robot Second Language Learning
Department of Communication and Cognition, Tilburg University, Tilburg, the Netherlands.
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.ORCID iD: 0000-0003-2140-0612
Department of Cognitive Science and Artificial Intelligence, Tilburg University, Tilburg, the Netherlands.
Department of Development of Youth and Education in Diverse Societies, Utrecht University, Utrecht, the Netherlands; Section Leadership in Education and Development, Windesheim University of Applied Sciences, Almere, the Netherlands.
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2021 (English)In: Interacting with computers, ISSN 0953-5438, E-ISSN 1873-7951, Vol. 33, no 6, p. 596-626Article in journal (Refereed) Published
Abstract [en]

In this paper, we examine the process of designing robot-performed iconic hand gestures in the context of a long-Term study into second language tutoring with children of approximately 5 years old. We explore four factors that may relate to their efficacy in supporting second language tutoring: The age of participating children; differences between gestures for various semantic categories, e.g. measurement words, such as small, versus counting words, such as five; the quality (comprehensibility) of the robot's gestures; and spontaneous reenactment or imitation of the gestures. Age was found to relate to children's learning outcomes, with older children benefiting more from the robot's iconic gestures than younger children, particularly for measurement words. We found no conclusive evidence that the quality of the gestures or spontaneous reenactment of said gestures related to learning outcomes. We further propose several improvements to the process of designing and implementing a robot's iconic gesture repertoire.

Place, publisher, year, edition, pages
Oxford University Press (OUP) , 2021. Vol. 33, no 6, p. 596-626
Keywords [en]
Human-robot interaction, Nonverbal communication, Second language learning, Social robotics
National Category
General Language Studies and Linguistics Human Computer Interaction
Identifiers
URN: urn:nbn:se:kth:diva-329052DOI: 10.1093/iwc/iwac013ISI: 000811056300001Scopus ID: 2-s2.0-85136619318OAI: oai:DiVA.org:kth-329052DiVA, id: diva2:1768066
Note

QC 20230614

Available from: 2023-06-14 Created: 2023-06-14 Last updated: 2023-07-23Bibliographically approved

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Willemsen, Bram

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