Impacts of Artificial Intelligence in Music Education
A Scoping Review of Instructional Strategies and Student Learning Outcomes
Bibliographic Data
| ID | 21684535 |
|---|---|
| Authors | Kristian Tverli Iversen (0009-0008-9191-1761, Western Norway University of Applied Sciences, Bergen, Norway, corresponding author) |
| Year | 2026 |
| Publication date | 2026-06-24 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Research Studies in Music Education (JOURNAL) |
| Journal identifiers | ISSN: 1321-103X • E-ISSN: 1834-5530 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/1321103x261453265 |
| OpenAlex | W7165814061 |
| Language | EN |
| References cited | 48 |
The increasing integration of artificial intelligence (AI) into music education raises important pedagogical, creative, and ethical questions. This scoping review synthesises recent empirical research on the use of AI in classroom-based music education, with a particular focus on student learning outcomes and creativity. Reviewed studies included 22 peer-reviewed empirical studies published between January 2023 and March 2025, identified from 1,274 records through systematic searches in major academic databases, revealing a strong geographical concentration of studies in East Asia, particularly China, with most research employing experimental designs and focusing on higher education contexts. Studies examined a range of AI applications, including adaptive learning systems, intelligent tutoring tools, AI-supported composition and arrangement technologies, and large language model chatbots. Across these contexts, AI use was generally associated with positive outcomes related to student motivation, self-efficacy, technical skill development, and aspects of musical creativity. At the same time, recurring concerns were raised regarding authorship, artistic authenticity, emotional depth, and teacher preparedness for AI integration. Methodologically, the literature is dominated by short-term quantitative measures, limiting insight into creative processes and classroom practices. Overall, the review suggests that AI may support music education when used alongside human guidance, while highlighting the need for qualitative and longitudinal research on creativity, pedagogy, and ethical considerations
Academic achievement · Educational research · Empirical evidence · Empirical research · Limiting · Music education · Preparedness · Qualitative research · Diverse Music Education Insights · Music Technology and Sound Studies · Neuroscience and Music Perception
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| Highly cited | No |
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