Impact of AI Software on Improving Learning Outcomes and Attitudes of Music Students in Chinese Vocational Schools

Authors

Keywords:

Motivation, Music Education, Artificial intelligence, SDG4, Equitable Access, Vocational Education

Abstract

This study focused on the application of AI tools in vocational music education. The objective is to determine whether the use of AI tools can help improve music listening and reading skills, thereby helping to address the challenges of access to quality music education by students in poor districts with limited access to learning resources. In a within-subjects experimental procedure involving 44 vocational school students (22 male, 22 female) aged 14-17, participants underwent 3 weeks of learning music listening and reading without technology support (condition 1) and learning with AI support (condition 2). Kimi Assistant AI tool was employed for teaching music listening while Music notation software (Laiyinzhipu) was employed for teaching music reading. Students were tested for both learning and attitude. Three (3) hypotheses were also tested to assess the impact of AI tools on music listening, reading and students’ attitudes. Findings show that using AI software specifically promoted only Melody and Structure indicators in listening skills whereas all the reading skills show marked improvement with AI tool. The implication of this is that AI software might hold more effectiveness regarding the teaching of reading skills. A significant improvement in attitude was also noted with the use of AI tools. However, more in-depth studies are needed to confirm if there are clear correlations between learning outcomes and attitudes with the use of AI software can help students improve their motivation to learn. The study is novel in its focus on music education. The study further shows that a combination of AI software and teacher-led instruction will be more significantly beneficial to students for learning music courses. Recommendations for future studies address the limitations of the study including the short experimental period, software restriction issues, an exploration of learners’ motivation, and studies adopting other designs including surveys and other experimental methods.

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Author Biographies

  • Jiuzhou Ren, Universiti Sains Malaysia

    Ren Jiuzhou (Peter Ren) holds a Bachelor of Arts from China University of Labor Relations and a Master of Arts in Cultural Industry Management from City University of Macau where he explored research on game exhibition. Peter is currently a doctoral scholar at the Centre for Instructional Technology and Multimedia, Universiti Sains Malaysia, Penang. His research focuses on game-based learning and music education.

     

  • Bosede Iyiade Edwards, Universiti Sains Malaysia

    Dr. Bosede Iyiade Edwards is a Senior Lecturer at the Center for Instructional Technology and Multimedia, Universiti Sains Malaysia (USM), Penang. Her research interests include emerging technologies in education and Human–Machine Interfaces in Education within the future school theme. She is a seasoned academic and industry professional with over 25 years of work experience. She holds both Masters and PhD in Educational Technology in addition to a Honours Bachelors in Chemistry, a Master in Organic Chemistry, and a PGD in Education. This multidisciplinary background enriches her perspectives in research and teaching. She has a proven track record in research leadership, and trans-disciplinary approaches to academic research. She has authored and co-authored several journal and conference papers, and has been recognized with the IEEE Frontiers in Education 'Faculty Fellow' Award. She is passionate about SDG4, and how educational technologies can be leveraged for promoting equitable education.

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Published

24-12-2024

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Section

Articles

How to Cite

Ren, J., Edwards, B. I., & Jamiat, N. . (2024). Impact of AI Software on Improving Learning Outcomes and Attitudes of Music Students in Chinese Vocational Schools. Journal of Technical Education and Training, 16(3), 132-146. https://penerbit.uthm.edu.my/ojs/index.php/JTET/article/view/19544

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