Personalizing HRI in Musical Instrument Practicing: The Influence of Robot Roles (Evaluative

child–robot interaction learning stages motivation for musical instrument practicing robot roles robots for personalized education robots in music education

Journal

Frontiers in robotics and AI
ISSN: 2296-9144
Titre abrégé: Front Robot AI
Pays: Switzerland
ID NLM: 101749350

Informations de publication

Date de publication:
2021
Historique:
received: 23 04 2021
accepted: 19 08 2021
entrez: 18 10 2021
pubmed: 19 10 2021
medline: 19 10 2021
Statut: epublish

Résumé

Learning to play a musical instrument involves skill learning and requires long-term practicing to reach expert levels. Research has already proven that the assistance of a robot can improve children's motivation and performance during practice. In an earlier study, we showed that the specific role (evaluative role versus nonevaluative role) the robot plays can determine children's motivation and performance. In the current study, we argue that the role of the robot has to be different for children in different learning stages (musical instrument expertise levels). Therefore, this study investigated whether children in different learning stages would have higher motivation when assisted by a robot in different supporting roles (i.e., evaluative role versus nonevaluative role). We conducted an empirical study in a real practice room of a music school with 31 children who were at different learning stages (i.e., beginners, developing players, and advanced players). In this study, every child practiced for three sessions: practicing alone, assisted by the evaluative robot, or assisted by the nonevaluative robot (in a random order). We measured motivation by using a questionnaire and analyzing video data. Results showed a significant interaction between condition (i.e., alone, evaluative robot, and nonevaluative robot) and learning stage groups indicating that children in different learning stage groups had different levels of motivation when practicing alone or with an evaluative or nonevaluative robot. More specifically, beginners had higher persistence when practicing with the nonevaluative robot, while advanced players expressed higher motivation after practicing with a robot than alone, but no difference was found between the two robot roles. Exploratory results also indicated that gender might have an interaction effect with the robot roles on child's motivation in music practice with social robots. This study offers more insight into the child-robot interaction and robot role design in musical instrument learning. Specifically, our findings shed light on personalization in HRI, that is, from adapting the role of the robot to the characteristics and the development level of the user.

Identifiants

pubmed: 34660701
doi: 10.3389/frobt.2021.699524
pii: 699524
pmc: PMC8517074
doi:

Types de publication

Journal Article

Langues

eng

Pagination

699524

Informations de copyright

Copyright © 2021 Song, Barakova, Markopoulos and Ham.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Références

Proc ACM SIGCHI. 2017 Mar;2017:137-145
pubmed: 30693352
J Pers Soc Psychol. 1968 Jul;9(3):245-50
pubmed: 5666972
Front Psychol. 2018 May 24;9:690
pubmed: 29881360
Scand J Occup Ther. 2009;16(4):247-56
pubmed: 19296400
Behav Res Methods. 2009 Aug;41(3):731-5
pubmed: 19587185
J Exp Child Psychol. 2002 Oct;83(2):111-30
pubmed: 12408958
Am Psychol. 2000 Jan;55(1):68-78
pubmed: 11392867
Science. 1965 Jul 16;149(3681):269-74
pubmed: 14300526
Br J Psychol. 2003 Nov;94(Pt 4):529-49
pubmed: 14687460
Early Child Res Q. 2011;26(4):430-441
pubmed: 21949599
J Pediatr Psychol. 2014 Apr;39(3):369-79
pubmed: 24163438
Br J Psychol. 2000 Aug;91 ( Pt 3):353-76
pubmed: 10958579

Auteurs

Heqiu Song (H)

Department of Industrial Design, Eindhoven University of Technology, Eindhoven, Netherlands.

Emilia I Barakova (EI)

Department of Industrial Design, Eindhoven University of Technology, Eindhoven, Netherlands.

Panos Markopoulos (P)

Department of Industrial Design, Eindhoven University of Technology, Eindhoven, Netherlands.

Jaap Ham (J)

Human-Technology Interaction, Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, Eindhoven, Netherlands.

Classifications MeSH