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MusicScaffold: Bridging Machine Efficiency and Human Growth in Adolescent Creative Education through Generative AI

Published: September 12, 2025 | arXiv ID: 2509.10327v1

By: Zhejing Hu , Yan Liu , Zhi Zhang and more

Potential Business Impact:

Helps teens learn music by guiding AI.

Business Areas:
Intelligent Systems Artificial Intelligence, Data and Analytics, Science and Engineering

Adolescence is marked by strong creative impulses but limited strategies for structured expression, often leading to frustration or disengagement. While generative AI lowers technical barriers and delivers efficient outputs, its role in fostering adolescents' expressive growth has been overlooked. We propose MusicScaffold, the first adolescent-centered framework that repositions AI as a guide, coach, and partner, making expressive strategies transparent and learnable, and supporting autonomy. In a four-week study with middle school students (ages 12--14), MusicScaffold enhanced cognitive specificity, behavioral self-regulation, and affective confidence in music creation. By reframing generative AI as a scaffold rather than a generator, this work bridges the machine efficiency of generative systems with human growth in adolescent creative education.

Country of Origin
🇨🇳 🇭🇰 Hong Kong, China

Page Count
16 pages

Category
Computer Science:
Human-Computer Interaction