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You win, I lose

Towards adapting robot's teaching strategy

Bibliographic Data

ID8103238
AuthorsSerik Meiirbekov (corresponding author), Kairat Balkibekov, Zhandarbek Jalankuzov, Anara Sandygulova (0000-0001-9299-5700)
Year2016
Publication date2016-03-01
Open AccessNo
TypeARTICLE
Venue2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI (CONFERENCE)
PublisherIEEE (PUBLISHER)
DOI10.1109/hri.2016.7451813
OpenAlexW4250471039
ISBN9781467383707
LanguageEN
Citations received7
References cited5

This paper presents a study that aims to address the challenges of creating effective educational robots. To this end, we developed a social educational robot which acts as a peer that is also a learner of a foreign language rather than a tutor teaching it. Children engage in a game with a peer robot which is programmed to either always win or always lose. The purpose of this study is to investigate whether children would learn more if they were winning or losing the game to the robot. The conducted study compares children's responses and children's improvements of English vocabulary after a game with the robot. Results indicate that children improve their English after playing with the robot, however which depends on the robot's adapting strategy

Human–computer interaction · Linguistics · Mobile robot · Multimedia · Robot · Robot control · Social robot · TUTOR · Vocabulary · AI in Service Interactions · Computer Science · Robotics and Automated Systems · Social Robot Interaction and HRI · Artificial Intelligence

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Citations per year0.88
Citation span2018 - 2025 (8)
Highly citedNo

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