Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/90967
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Title: Robot tutoring of multiplication : over one-third learning gain for most, learning loss for some
Authors: Hoorn, JF 
Huang, IS
Konijn, EA
van, Buuren, L
Issue Date: Mar-2021
Source: Robotics, Mar. 2021, v. 10, no. 1, 16, p. 1-24
Abstract: In the design of educational robots, it appears to be undecided as to whether robots should show social behaviors and look human-like or whether such cues are insignificant for learning. We conducted an experiment with different designs of social robots built from the same materials, which is unique in robotics research. The robots rehearsed multiplication tables with primary school children in Hong Kong, which is a user group not easily or often accessed. The results show that affective bonding tendencies may occur but did not significantly contribute to the learning progress of these children, which was perhaps due to the short interaction period. Nonetheless, 5 min of robot tutoring improved their scores by about 30%, while performance dropped only for a few challenged children. We discuss topics, such as teaching language skills, which may be fostered by human likeness in appearance and behaviors; however, for Science, Technology, Engineering, and Mathematics (STEM)-related subjects, the social aspects of robots hardly seem to matter.
Keywords: Experience design
Multiplication
Robot tutelage
Social robots
Publisher: Molecular Diversity Preservation International (MDPI)
Journal: Robotics 
EISSN: 2218-6581
DOI: 10.3390/robotics10010016
Rights: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
The following publication Hoorn, J.F.; Huang, I.S.; Konijn, E.A.; van Buuren, L. Robot Tutoring of Multiplication: Over One-Third Learning Gain for Most, Learning Loss for Some. Robotics 2021, 10, 16 is available at https://doi.org/10.3390/robotics10010016
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