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.
@article{arxiv.2509.10327,
title = {MusicScaffold: Bridging Machine Efficiency and Human Growth in Adolescent Creative Education through Generative AI},
author = {Zhejing Hu and Yan Liu and Zhi Zhang and Gong Chen and Bruce X. B. Yu and Junxian Li and Jiannong Cao},
journal= {arXiv preprint arXiv:2509.10327},
year = {2025}
}