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

TL;DR

This paper presents AI Craftsmanship, a framework and tool embedding craftsmanship values into AI-assisted design education to promote reflection, responsibility, and iterative learning.

Contribution

It introduces a value-oriented AI tool for design learning, emphasizing craftsmanship principles like risk, rhythm, and care within AI-integrated creative coding.

Findings

Risk and rhythm influence early learning stages.

Care emerges through reflective practices.

Emergent values like aesthetic judgment motivate learners.

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.