Exploration on the Implementation Path of AI-Enabled Personalized Music Teaching in Primary Schools

Abstract

To address the problems of “one-size-fits-all” music teaching in primary schools and the difficulty in meeting students’ differentiated needs, this study focuses on the deep integration of artificial intelligence (AI) technology and primary school music teaching, and explores the implementation path of personalized teaching. It establishes three basic guarantees: teaching hardware, teachers’ competence, and teaching resources. The core strategies are implemented through accurate diagnosis of students’ music literacy, personalized content recommendation, and real-time guidance and feedback. The optimization directions are clarified from three dimensions: evaluation system, application norms, and implementation path, providing feasible support for the practice of personalized music teaching in primary schools and helping improve teaching quality and students’ core music literacy.