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A Comparison of Social Robot to Tablet and Teacher in a New Script Learning Context.
- Source :
-
Frontiers in robotics and AI [Front Robot AI] 2020 Oct 07; Vol. 7, pp. 99. Date of Electronic Publication: 2020 Oct 07 (Print Publication: 2020). - Publication Year :
- 2020
-
Abstract
- This research occurred in a special context where Kazakhstan's recent decision to switch from Cyrillic to the Latin-based alphabet has resulted in challenges connected to teaching literacy, addressing a rare combination of research hypotheses and technical objectives about language learning. Teachers are not necessarily trained to teach the new alphabet, and this could result in a challenge for children with learning difficulties. Prior research studies in Human-Robot Interaction (HRI) have proposed the use of a robot to teach handwriting to children (Hood et al., 2015; Lemaignan et al., 2016). Drawing on the Kazakhstani case, our study takes an interdisciplinary approach by bringing together smart solutions from robotics, computer vision areas, and educational frameworks, language, and cognitive studies that will benefit diverse groups of stakeholders. In this study, a human-robot interaction application is designed to help primary school children learn both a newly-adopted script and also its handwriting system. The setup involved an experiment with 62 children between the ages of 7-9 years old, across three conditions: a robot and a tablet, a tablet only, and a teacher. Based on the paradigm-learning by teaching-the study showed that children improved their knowledge of the Latin script by interacting with a robot. Findings reported that children gained similar knowledge of a new script in all three conditions without gender effect. In addition, children's likeability ratings and positive mood change scores demonstrate significant benefits favoring the robot over a traditional teacher and tablet only approaches.<br /> (Copyright © 2020 Zhexenova, Amirova, Abdikarimova, Kudaibergenov, Baimakhan, Tleubayev, Asselborn, Johal, Dillenbourg, CohenMiller and Sandygulova.)
Details
- Language :
- English
- ISSN :
- 2296-9144
- Volume :
- 7
- Database :
- MEDLINE
- Journal :
- Frontiers in robotics and AI
- Publication Type :
- Academic Journal
- Accession number :
- 33501266
- Full Text :
- https://doi.org/10.3389/frobt.2020.00099