Artificial Intelligence in Music Education
Abstract
Abstract Music education exists at the intersection of philosophy, psychology, and praxis, and the emergence of artificial intelligence (AI) has introduced both opportunities and challenges in these domains. This chapter examines the integration of AI in music education, analyzing its influence on pedagogical approaches, cognitive development, and the evolving role of educators. Historically, technological advancements in music, from the phonograph to synthesizers, have faced skepticism yet ultimately expanded musical accessibility and innovation. Similarly, AI in music education requires careful implementation to ensure it complements rather than replaces traditional methodologies. This chapter explores AI’s alignment with major educational philosophies, including John Dewey’s experiential learning, Lev Vygotsky’s scaffolding, and David Elliott’s praxial music education. Psychologists, such as Howard Gardner’s multiple intelligences and Jerome Bruner’s generative learning, provide a framework for understanding AI’s impact on musical cognition. AI’s integration into music teaching methodologies, including Orff-Schulwerk, Kodály, Dalcroze Eurhythmics, and Gordon’s Music Learning Theory, presents both benefits and limitations. While AI enhances accessibility and personalized learning, ethical concerns about data bias and the risk of diminishing human artistic expression are topics for educators to address. Ultimately, AI’s role in music education should be guided by pedagogical goals, ensuring that technology augments rather than substitutes for human creativity and musical engagement.
