A Study on Strengthening Personalized University Music Education Through AI

This study aims to propose solutions for improving the deteriorating environment of university music education by utilizing AI technology. To complete the research, relevant prior studies and international sources have been reviewed and analyzed. Recently, university music education has been facing numerous challenges, including issues related to educational infrastructure, a shortage of specialized music educators, an entrance exam-oriented education system, structural limitations in education programs, employment difficulties, declining student enrollment due to a shrinking school-age population, regional talent outflow, and the limitations of remote learning. To address these challenges, this study examines case studies from universities in the United States, Europe, and Asia. Based on these findings, several AI-driven solutions are proposed: the implementation of AI-based personalized music education systems, AI-assisted music composition and arrangement support, reinforcement of AI-driven practice and performance education, innovation in music research and educational content through AI, and the establishment of AI-supported educational environments and infrastructure.