The impact of AI-assisted composition tools on cultivating creativity among music students in Guangdong province - Wang, Yi; Panicker, Chandra Mohan Vasudeva (Edelweiss Applied Science and Technology, 2025)
To investigate the impact of AI-assisted composition tools on cultivating creativity among music students in Guangdong Province, a quasi-experimental design was employed with 120 music students divided into experimental and control groups. Data were collected through pre-test and post-test assessments and analyzed using entropy weight methodology. The experimental group significantly outperformed the control group across nine compositional dimensions, with substantial improvements in cultural integration (d=2.08), creative fluency (d=1.87), and expressive range (d=1.58). Entropy weight analysis identified cultural integration (16.52%) and creative fluency (15.47%) as the most discriminative dimensions. Fifty-one point seven percent of experimental group compositions exceeded the excellence threshold compared to only 3.3% in the control group. AI-assisted composition tools effectively balance technical development with creative exploration, enhancing students’ compositional abilities while strengthening the integration of cultural heritage with technological innovation. The findings suggest that integrating AI-assisted tools in music education can significantly improve students’ creative capabilities, particularly in preserving and innovating with traditional cultural elements.