Transforming Music Education Through Artificial Intelligence: A Systematic Literature Review on Enhancing Music Teaching and Learning

Abstract

The advent of artificial intelligence (AI) has brought significant and transformative alterations to traditional music education. This study examines the progress of AI technology in music education by conducting a systematic review using the PRISMA methodology. Articles were selected for inclusion based on the criterion of specifically describing the utilization of AI in the instruction and acquisition of music. The search was performed on April 9, 2024, via the Web of Science and SCOPUS databases. The search terms “music education” and “artificial intelligence” were employed to ascertain relevant scholarly research. The group of papers underwent scrutiny by various researchers to ascertain their adherence to the established criteria. The articles that were verified by a minimum of two researchers were chosen. 31 articles were finally screened, and the results were divided into two sections: the development of AI in music education and innovative music pedagogy based on AI. A key finding is that the implementation of bibliometric analyses suggests that AI research in music education is still in its infancy. Prior research has primarily concentrated on music instruction at the university level, with a particular emphasis on the integration of AI in music education in China. In addition, this study identifies four specific facets of AI through the reshaping of music pedagogy: enhancing personalized music teaching, providing timely feedback on learning, supporting interactive experiences, and providing organized digital materials.