Using self-determination theory in social robots to increase motivation in L2 word learning

P. van Minkelen; C. Gruson; P. van Hees; M. Willems; J. de Wit; R. Aarts; J.J.A. Denissen; P. Vogt

doi:10.1145/3319502.3374828

Using self-determination theory in social robots to increase motivation in L2 word learning

P. van Minkelen, C. Gruson, P. van Hees, M. Willems, J. de Wit, R. Aarts, J.J.A. Denissen, P. Vogt

Tilburg University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

This study presents a second language word learning experiment using a social robot with motivational strategies. These strategies were implemented in a social robot tutor to stimulate preschool children's intrinsic motivation. Subsequently, we investigated their effect on children's task engagement and word learning performance. The strategies were derived from the Self-Determination Theory, a well-known psychological theory that assumes that intrinsic motivation is strongly related to the fulfilment of three basic human needs, namely the need for autonomy, competence, and relatedness. We found an increase in the strength and duration of task engagement when all three psychological needs were supported by the robot. However, no significant results for learning gains were observed. Our intervention appears a promising method for improving child-robot interactions in educational settings, especially to sustain in long-term interactions.

Original language	English
Title of host publication	HRI '20: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction
Place of Publication	New York
Publisher	Association for Computing Machinery
Pages	369-377
ISBN (Electronic)	9781450367462
DOIs	https://doi.org/10.1145/3319502.3374828
Publication status	Published - 2020
Externally published	Yes
Event	15th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2020 - Cambridge, United Kingdom Duration: 23 Mar 2020 → 26 Mar 2020

Conference

Conference	15th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2020
Country/Territory	United Kingdom
City	Cambridge
Period	23/03/20 → 26/03/20

Funding

The authors would like to thank Mirjam de Haas for providing her scheme and training to code task engagement, all reviewers for their valuable feedback, and all participating children, their parents, and the schools for their contribution to this experiment. The first author was supported by a research trainee grant provided by Tilburg University.

Keywords

Human-robot interaction
Motivation
Robot tutor
Second language learning
Self-determination theory
Task engagement

Access to Document

10.1145/3319502.3374828

Cite this

van Minkelen, P., Gruson, C., van Hees, P., Willems, M., de Wit, J., Aarts, R., Denissen, J. J. A., & Vogt, P. (2020). Using self-determination theory in social robots to increase motivation in L2 word learning. In HRI '20: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (pp. 369-377). Association for Computing Machinery. https://doi.org/10.1145/3319502.3374828

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title = "Using self-determination theory in social robots to increase motivation in L2 word learning",

abstract = "This study presents a second language word learning experiment using a social robot with motivational strategies. These strategies were implemented in a social robot tutor to stimulate preschool children's intrinsic motivation. Subsequently, we investigated their effect on children's task engagement and word learning performance. The strategies were derived from the Self-Determination Theory, a well-known psychological theory that assumes that intrinsic motivation is strongly related to the fulfilment of three basic human needs, namely the need for autonomy, competence, and relatedness. We found an increase in the strength and duration of task engagement when all three psychological needs were supported by the robot. However, no significant results for learning gains were observed. Our intervention appears a promising method for improving child-robot interactions in educational settings, especially to sustain in long-term interactions.",

keywords = "Human-robot interaction, Motivation, Robot tutor, Second language learning, Self-determination theory, Task engagement",

author = "{van Minkelen}, P. and C. Gruson and {van Hees}, P. and M. Willems and {de Wit}, J. and R. Aarts and J.J.A. Denissen and P. Vogt",

year = "2020",

doi = "10.1145/3319502.3374828",

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booktitle = "HRI '20: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction",

publisher = "Association for Computing Machinery",

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note = "15th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2020 ; Conference date: 23-03-2020 Through 26-03-2020",

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van Minkelen, P, Gruson, C, van Hees, P, Willems, M, de Wit, J, Aarts, R, Denissen, JJA & Vogt, P 2020, Using self-determination theory in social robots to increase motivation in L2 word learning. in HRI '20: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction. Association for Computing Machinery, New York, pp. 369-377, 15th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2020, Cambridge, United Kingdom, 23/03/20. https://doi.org/10.1145/3319502.3374828

Using self-determination theory in social robots to increase motivation in L2 word learning. / van Minkelen, P.; Gruson, C.; van Hees, P. et al.
HRI '20: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction. New York: Association for Computing Machinery, 2020. p. 369-377.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Aarts, R.

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Using self-determination theory in social robots to increase motivation in L2 word learning

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