Workmanship of Learning: Embedding Craftsmanship Values in AI-Integrated Educational Tools
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866917391904014336 |
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| 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 |