Problem
Research questions and friction points this paper is trying to address.
Generative AI
design education
craftsmanship
reflective learning
value-oriented design
Workmanship of Learning: Embedding Craftsmanship Values in AI-Integrated Educational Tools
🤖 AI Summary
This study addresses the tension between generative AI’s emphasis on automation and efficiency and design education’s core values of exploration, reflection, and responsibility. It proposes an “AI craftsmanship” framework that systematically integrates traditional craft values—risk, rhythm, and care—into the design of AI educational tools. Through a research-through-design approach, the authors developed an interactive interface within the p5.js creative coding platform to support iterative experimentation and reflective practice. Empirical findings from five design practitioners reveal that risk and rhythm facilitate initial comprehension, while care emerges during reflection, fostering aesthetic judgment and self-efficacy as novel learning motivations. The work underscores process-oriented learning and illuminates how values dynamically manifest in AI-assisted creative practices.
📝 Abstract
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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
AI Craftsmanship
value-oriented design
generative AI in education
creative coding
reflective learning
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