Workmanship of Learning: Embedding Craftsmanship Values in AI-Integrated Educational Tools

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Huang, Tuan-Ting, Huang, Janet Yi-Ching, Wensveen, Stephan
Natura: Preprint
Pubblicazione: 2026
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866917391904014336
author Huang, Tuan-Ting
Huang, Janet Yi-Ching
Wensveen, Stephan
author_facet Huang, Tuan-Ting
Huang, Janet Yi-Ching
Wensveen, Stephan
contents Generative AI's emphasis on automation and efficiency challenges design education, where learning is grounded in exploration, reflection, and responsibility. This work introduces AI Craftsmanship, a value-oriented framework drawing on craftsmanship traditions that emphasize risk, rhythm, and care as central to learning through making. Through a Research through Design (RtD) approach, we designed an AI-integrated creative coding tool embedding these values into interactions and interface rather than outcomes. The tool supports designers learning generative pattern-making with p5.js by constraining AI, encouraging iterative experimentation, and foregrounding reflection. We studied the tool with five design practitioners through one-hour sessions and semi-structured interviews. Findings show craft values manifest unevenly: risk and rhythm shape early sense-making, while care emerges through reflective practices. Emergent values -- such as aesthetic judgment and confidence -- also motivated learning. AI Craftsmanship mediates values, tools, and materials, offering a value-driven perspective on designing AI systems for reflective, responsible, craft-informed learning in design education.
format Preprint
id arxiv_https___arxiv_org_abs_2604_07118
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Workmanship of Learning: Embedding Craftsmanship Values in AI-Integrated Educational Tools
Huang, Tuan-Ting
Huang, Janet Yi-Ching
Wensveen, Stephan
Human-Computer Interaction
Generative AI's emphasis on automation and efficiency challenges design education, where learning is grounded in exploration, reflection, and responsibility. This work introduces AI Craftsmanship, a value-oriented framework drawing on craftsmanship traditions that emphasize risk, rhythm, and care as central to learning through making. Through a Research through Design (RtD) approach, we designed an AI-integrated creative coding tool embedding these values into interactions and interface rather than outcomes. The tool supports designers learning generative pattern-making with p5.js by constraining AI, encouraging iterative experimentation, and foregrounding reflection. We studied the tool with five design practitioners through one-hour sessions and semi-structured interviews. Findings show craft values manifest unevenly: risk and rhythm shape early sense-making, while care emerges through reflective practices. Emergent values -- such as aesthetic judgment and confidence -- also motivated learning. AI Craftsmanship mediates values, tools, and materials, offering a value-driven perspective on designing AI systems for reflective, responsible, craft-informed learning in design education.
title Workmanship of Learning: Embedding Craftsmanship Values in AI-Integrated Educational Tools
topic Human-Computer Interaction
url https://arxiv.org/abs/2604.07118