The Effects of AI-Based Create Music Education on Elementary Students’ Perceptions

Purpose: This study aimed to investigate the effects of an AI-based music composition class on elementary school students’ perceptions toward Music Education. Specifically, it analyzes changes in students’ interest, self-efficacy, learning engagement, and attitudes toward participation in music classes through quantitative analysis of pre- and post-intervention surveys. Methods: The participants consisted of 191 fifth and sixth graders from an elementary school in Gyeonggi Province. A four-session music class utilizing an AI-assisted composition tool was implemented, and data were collected through pre- and post-class surveys. The survey included 30 items: six demographic questions, one multiple-response question on music activity preferences, and 23 questions using a 5-point Likert scale. Data analysis involved paired-sample t-tests, Pearson’s correlation analysis, descriptive statistics, and effect size analysis using Cohen’s d. Results: Statistically significant improvements were found in overall student perceptions following the AI-based music composition class. Particularly notable were large increases in responses to items such as “I think composing music is easy”, “I wish there were more music classes” and “I want to perform better in music class than in other subjects.” The question on composition perception (Q7) showed a very large effect size (Cohen’s d = 1.75), suggesting that AI tools effectively reduced psychological barriers to music creation and expanded students’ creative experiences. However, certain items did not show significant changes due to high pre-test scores, highlighting the need to consider initial perception levels and potential variability among students. Conclusion: The results indicate that integrating AI-based creative music education into classrooms can positively influence students’ intrinsic motivation, self-efficacy, engagement, and participation attitudes beyond mere technological incorporation. This study also highlights the educational value and potential for the expansion of AI-driven creative music instruction, providing foundational insights for developing integrated education models that bridge music, AI literacy, and other subject areas.