The Optimizing Role and Future Prospects of AI in Traditional Piano Classrooms

Abstract

Artificial intelligence technology is gradually entering piano classrooms in higher normal universities, offering multidimensional possibilities for optimizing traditional piano teaching. This paper systematically explores the optimizing effects of AI on traditional piano classrooms from five dimensions: teaching efficiency, personalized guidance, collaborative ability cultivation, teaching evaluation, and teacher role transformation. The study argues that the core value of integrating AI into piano teaching lies not in replacing tradition, but in compensating for the long-standing structural shortcomings of traditional models—such as the lack of feedback in after-class practice, the scarcity of ensemble experience, and the difficulty of storing and analyzing teaching data. On this basis, the paper envisions the future of deep integration between AI and piano teaching, proposing the construction of a new teaching model characterized by “human-machine collaboration and complementary strengths,” enabling AI to evolve from an auxiliary tool into a teaching partner, and offering new ideas for the reform of piano education in higher normal universities.