Year: 2025
Type: article
Abstract: This paper will discuss how the hybrid AI-human music composition setting can have a pedagogical effect on the creative process and musical knowledge of undergraduate learners. They used a mixed-method research study that entailed expert analysis of student composition, system interaction logs, and reflective learner feedback. It was found that students with the hybrid system obtained much better results in the increase of harmonic coherence, melodic structure, rhythmic variation, and a general creative expression than the control group with the traditional tools. Behavioral studies indicate that AI-generated recommendations proved more helpful when composing the first ideas, and students progressively used self-refinement in the later stages of the composition. Evaluations of creativity levels and self-efficacy scores among the experimental group had a significant positive change and demonstrate the relevance of the system in increasing idea generation, decreasing creative anxiety, and enhancing critical engagement skills. The paper adds to a growing body of evidence that AI-assisted learning in a hybrid form provides useful new directions in the field of music education, helping to develop a more in-depth musical perception and more convenient creative investigation.
Authors: Paramjit Baxi, Susmita Panda, Sachin Mittal, Nidhi Tewatia, Battula Bhavya, Fariyah Saiyad
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W4417500607