Artificial intelligence applications and pedagogical challenges in music education
Mazlan C.A.N. Hanafi H.F. Sarifin M.R. Md Noor A.R. Sadykova S.A. Hidayatullah R. Jamnongsarn S.
December 2026Discover
Discover Education
2026#5Issue 1
This mini review synthesizes recent advancements in the integration of artificial intelligence (AI) within instrumental music education, emphasizing both computational methods and pedagogical frameworks. Drawing from the top 50 highly cited Scopus-indexed documents, the review identifies dominant AI techniques such as deep learning, transformer architectures, and generative models. These technologies enhance practice efficiency, personalize instruction, and improve assessment objectivity. However, challenges persist, including dataset bias, limited cultural sensitivity, and constraints in expressive feedback. Thematic and technical analyses reveal a strong focus on composition and performance domains, with creativity and feedback as key pedagogical impacts. The review integrates pedagogical models such as TPACK, SAMR, and Bloom’s taxonomy to contextualize AI adoption. Findings suggest that hybrid models combining AI analytics with human instruction offer the greatest educational value. Future research should prioritize culturally adaptive systems, ethical transparency, and inclusive design to ensure equitable and meaningful integration of AI in music pedagogy.
Artificial intelligence , Assessment methodologies , Music education , Pedagogical efficacy , Technological integration
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Music and Music Education Department, Faculty of Music and Performing Arts, Sultan Idris Education University, Perak, Tanjung Malim, 35900, Malaysia
Music Faculty, National Academy of Arts, Culture and Heritage, 464, Jalan Tun Ismail, Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, 50480, Malaysia
Faculty of Computing & Meta-Technology, Sultan Idris Education University, Perak, Tanjung Malim, 35900, Malaysia
Faculty of Human Sciences, Sultan Idris Education University, Perak, Tanjung Malim, 35900, Malaysia
Faculty of Music, MARA University of Technology, 11, Menara SAAS, Selangor, Shah Alam, 40450, Malaysia
K. Zhubanov Aktobe Regional University, 34, A.Moldagulova St, Aktobe, 030000, Kazakhstan
Program Studi Pendidikan Musik, Jurusan Pendidikan Bahasa Dan Seni, Fakultas Keguruan Dan Ilmu Pendidikan, Lampung University, Jl. Prof. Dr. Soemantri Brodjonegoro, No. 1 Gedongmeneng, Rajabasa Bandar Lampung, 35145, Indonesia
Director of Graduate Program in Thai and Asian Music, Faculty of Fine Arts, Srinakharinwirot University, Khlong Toei Nuea, 114 Soi Sukhumvit 23, Watthana, Bangkok, 10110, Thailand
Music and Music Education Department
Music Faculty
Faculty of Computing & Meta-Technology
Faculty of Human Sciences
Faculty of Music
K. Zhubanov Aktobe Regional University
Program Studi Pendidikan Musik
Director of Graduate Program in Thai and Asian Music
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