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

Peggy Van Minkelen; Carmen Gruson; Pleun Van Hees; Mirle Willems; Jan De Wit; Jaap Denissen; Paul Vogt

doi:10.1145/3319502.3374828

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

Peggy Van Minkelen
, Carmen Gruson
, Pleun Van Hees
, Mirle Willems
, Jan De Wit
, Jaap Denissen
, Paul Vogt

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 2020 - Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction
Publisher	IEEE Computer Society
Pages	369-377
Number of pages	9
ISBN (Electronic)	9781450367462
DOIs	https://doi.org/10.1145/3319502.3374828
Publication status	Published - 9 Mar 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

Publication series

Name	ACM/IEEE International Conference on Human-Robot Interaction
ISSN (Electronic)	2167-2148

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

Bibliographical note

Funding Information:
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.

Publisher Copyright:
© 2020 Association for Computing Machinery.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

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

Persistent URL (handle)

Persistent link

Cite this

Van Minkelen, P., Gruson, C., Van Hees, P., Willems, M., De Wit, J., Denissen, J., & Vogt, P. (2020). Using self-determination theory in social robots to increase motivation in L2 word learning. In HRI 2020 - Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (pp. 369-377). (ACM/IEEE International Conference on Human-Robot Interaction). IEEE Computer Society. https://doi.org/10.1145/3319502.3374828

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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.",

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note = "Funding Information: 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. Publisher Copyright: {\textcopyright} 2020 Association for Computing Machinery. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 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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doi = "10.1145/3319502.3374828",

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Van Minkelen, P, Gruson, C, Van Hees, P, Willems, M, De Wit, J, Denissen, J & Vogt, P 2020, Using self-determination theory in social robots to increase motivation in L2 word learning. in HRI 2020 - Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction. ACM/IEEE International Conference on Human-Robot Interaction, IEEE Computer Society, 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, Peggy; Gruson, Carmen; Van Hees, Pleun et al.
HRI 2020 - Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction. IEEE Computer Society, 2020. p. 369-377 (ACM/IEEE International Conference on Human-Robot Interaction).

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

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AU - Denissen, Jaap

AU - Vogt, Paul

N1 - Funding Information: 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. Publisher Copyright: © 2020 Association for Computing Machinery. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/3/9

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N2 - 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.

AB - 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.

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ER -

Van Minkelen P, Gruson C, Van Hees P, Willems M, De Wit J, Denissen J et al. Using self-determination theory in social robots to increase motivation in L2 word learning. In HRI 2020 - Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction. IEEE Computer Society. 2020. p. 369-377. (ACM/IEEE International Conference on Human-Robot Interaction). doi: 10.1145/3319502.3374828

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

Abstract

Publication series

Conference

Bibliographical note

Funding

Keywords

Access to Document

Persistent URL (handle)

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Cite this