Generative AI in Design Education: Post-digital Pedagogies Toolkit
Researcher
Kate Geck and Emma Luke
Published
26 September 2024
Funding
Design Thinking Grant
This project explores how generative machine learning (ML) models like MidJourney, ArkoAI and Chat GPT can be woven critically into design education for collaboration, ideation and design development. It has asked how lecturers and students can work with these tools as early adopters.
Generative machine learning (ML) models are becoming increasingly relevant to design educators. Text to image generators like MidJourney create convincing architectural and product renders in seconds. Language generators like Chat GPT produce natural text in minutes. As educators, Kate Geck and Emma Luke are exploring new ways on how to critically locate these tools and contextualise them for students.
Developing a pedagogical response to these emerging technologies is critical to the future of Australian design. We prepare the next generations of design practitioners to move out into a rapidly changing world. It is vital that educators explore and test ways of contextualising these ML tools for students in a practical and design-oriented way to future-proof Australian design industries.
Leveraging the expertise of design educators is an excellent way to understand how ML tools can be used within design education. The learnings gathered dually benefit students and educators. Students become better equipped to respond to changing industry demands and expectations, while educators develop a deeper understanding of how ML tools might enhance their teaching practice.
Operating within the University has provided ethical assurance where appropriate research ethics procedures were followed and grounded the research responsibly. This has ensured that the ML toolkit is ethical, sustainable and as useful as possible to educators and students in other institutions. For these reasons, this project has great potential to be a valuable resource for design educators across Australia, responding to the emerging complexity of generative ML tools. It could offer ways to incorporate these generative ML tools in design education.
The report includes insights, challenges, and potential ways of working with generative machine learning models.
It also offers a suite of design class activities that educators can use with their students. The activities have been tested and evaluated in these design studio classes and are also shared on Instagram.
