Design educators should strengthen primary research, foster critical verification habits, and move students from consumers to makers of GenAI tools¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article's conclusions propose educational responses to emerging GenAI practices in design education. The author asks whether educators should strengthen primary research so students collect their own data, how to prevent complacency in verifying outputs, and argues "There is a case to be made for ensuring that students become less of 'consumers' of GenAI tools and more 'makers' of their own tools" via custom GPTs, low/no-code apps and open source models. A yearly longitudinal survey is also recommended to monitor evolving practices.

Design Implications¶

Context¶

Requirements¶

• Experimenting with GenAI must be acceptable as long as it is reported, as conveyed in the Methods Course

Constraints¶

• The author frames these as open questions for design education rather than tested interventions

Target Learners¶

• undergraduate and masters design students

Target Learning Goals¶

• critical evaluation of GenAI outputs
• valuing the research phase of design
• customising GenAI tools for project needs

Related Strategies¶

• Strengthen institutional policies, ethics education, verification, disclosure, and data protection to support ethical GenAI use

Examples¶

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Key Sources¶

• Stefana Broadbent. (2026). A study of GenAI usage by Design Students: Analysis of Survey Results and Journals of AI practices at the Politecnico di Milano in 2025/2026. Department of Design, Politecnico di Milano. https://arxiv.org/abs/2607.17094