Leveraging AI and Machine Learning to Personalise Music Education

Abstract

Information technology contributes to the transformation of the learning process because it changes the traditional system of teaching, based on outdated methodologies. The paper examined the current technologies used in music education in the context of learning process improvements in China. A sociological survey was conducted using the Stapel scale to determine the effectiveness of each application. The highest average ratings were achieved by the Musicfy app (4.5) and Stable Audio (4.2), indicating their high effectiveness. Group comparison of the applications demonstrated a high level of equivalence among most applications, allowing for their interchangeable use in the learning process. Average ratings for each quarter within the two groups revealed varying results across different periods of study. ANOVA analysis confirmed statistically significant differences between the groups, indicating a positive impact of ICT technologies on learning effectiveness. The research findings have practical implications for instructors who are looking for new ways to improve music education, both for instrumentalists and vocalists, through the use of a variety of cutting-edge technologies. Further research might focus on the selection of additional technologies that affect the improvement of music education.