MusicScaffold: Bridging Machine Efficiency and Human Growth in Adolescent Creative Education through Generative AI
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866915492047880192 |
|---|---|
| author | Hu, Zhejing Liu, Yan Zhang, Zhi Chen, Gong Yu, Bruce X. B. Li, Junxian Cao, Jiannong |
| author_facet | Hu, Zhejing Liu, Yan Zhang, Zhi Chen, Gong Yu, Bruce X. B. Li, Junxian Cao, Jiannong |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_10327 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | MusicScaffold: Bridging Machine Efficiency and Human Growth in Adolescent Creative Education through Generative AI Hu, Zhejing Liu, Yan Zhang, Zhi Chen, Gong Yu, Bruce X. B. Li, Junxian Cao, Jiannong Human-Computer Interaction 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. |
| title | MusicScaffold: Bridging Machine Efficiency and Human Growth in Adolescent Creative Education through Generative AI |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2509.10327 |