Exploring the Reception of Artificial Intelligence-Enhanced Music Education: A Multimethod Study With Higher Education Vocal Music Students

Abstract

As music education evolves alongside advances in artificial intelligence (AI), traditional teaching models are experiencing significant transformation. This exploratory study investigates the perceived impact of an AI-enhanced music education system, particularly focusing on sound recognition technologies within university vocal music education. Employing a mixed-methods approach, data were collected from 101 university students in Jiangxi Province, China, through a 25-item questionnaire, complemented by in-depth interviews with selected participants as case studies. The findings reveal that AI integration contributes to improvements in (a) motivation for music practice, (b) confidence in singing abilities, and (c) perceived course quality. However, participants expressed skepticism regarding AI's utility in fostering artistic expression, highlighting an area requiring further development. Overall, students reported enhanced performance and positive attitudes toward AI tools, confirming their potential to enrich educational experiences while emphasizing the need for continued exploration of their limitations and broader applicability.