The impact of AI-assisted composition tools on cultivating creativity among music students in Guangdong province

Yi Wang () and Chandra Mohan Vasudeva Panicker ()

Edelweiss Applied Science and Technology, 2025, vol. 9, issue 6, 2790-2814

Abstract: 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.

Keywords: AI-assisted composition; Creativity cultivation; Entropy weight method; Guangdong musical traditions; Music education. (search for similar items in EconPapers)
Date: 2025
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