Application of generative AI in composition assistance and creative music teaching

Abstract

This study explores the integration of generative AI into creative education and music composition through the regulated use of LSTM-based model generation in the classroom. It demonstrates how AI can enhance creativity while maintaining academic integrity by combining data-driven approaches with ethical safeguards. Findings indicate that generative AI serves effectively as both a compositional aid and a tool for fostering innovative teaching practices. AI has transformed creative domains, offering new opportunities in music-making, yet its educational application requires a balance between innovation and ethical responsibility. Prior research highlights AI’s value for both novice and experienced composers, while recent studies emphasise its growing impact on higher education. The research methodology involved data collection, preprocessing, and the development of an LSTM model, alongside safeguards ensuring responsible implementation. Achieving over 87% precision in sequence prediction, the model showed strong performance, and under controlled conditions, students displayed greater initiative and originality.