Abstract

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.

Highlights

  • Musical instrument learning appears to have collateral cognitive benefits (Hassler et al, 1985; Anvari et al, 2002; HietolahtiAnsten and Kalliopuska, 1990)

  • In order to investigate the impact of robots in different supporting roles on the motivation of children in different learning stages in musical instrument practicing, the following analyses were performed

  • The aim of the current research was to find out the impact of robots in different supporting roles on children’s motivation in different learning stages in musical instrument practice

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Summary

Introduction

Musical instrument learning appears to have collateral cognitive benefits (Hassler et al, 1985; Anvari et al, 2002; HietolahtiAnsten and Kalliopuska, 1990). Singing, learning to play a musical instrument, and recognizing and keeping pitches and beat could improve learner’s cognitive functions better than passive listening (Bernhard, 2002; Jausovec and Pahor, 2017). Practicing at home is an important part of the instrument learning process for children (Hallam, 1998),but it is not an enjoyable activity for most children. It is crucial for teachers and parents to understand the significance of motivation in instrument learning, which is a skill development process (Woody, 2004)

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