Project Summary: The AI Design Ed project

The aim of the project is to explore student understanding and potential application of generative image AI tools in design education. The pedagogical goal is to assess if the tools could improve ideation and/or visual communication skills and inclusivity in design and related interdisciplinary subjects.

AI image generation software is used as a tool in Design and Innovation industry to speed up time consuming tasks https://www.ideo.com/journal/inviting-algorithms-to-the-design-team. Design students are familiar with AI tools; however, they are largely discouraged from utilising them creating a punitive approach and lack of transparency. Students lack skills to use these tools effectively, as observed in core design modules U101, T217 and T317, and there is a lack of clear ethical usage policy due to the fast-moving technology.

Key pedagogical questions are:

· If a student generates an idea using AI image generation tools for co-ideation and to improve visual output and communication – are they recognisably the design thinker?

· Is AI-generated co-ideation/visual communication better or equal to content produced from traditional methods such as sketching or prototyping?

This project will explore student views and experiences with AI image tools compared to traditional visual presentation techniques, and review whether AI lifts a potential barrier to entry to visual communication subjects for design and interdisciplinary STEM students. The project will also touch on accessibility factors which inhibit production of visual work to explore whether AI tools can help educate and include all students with an interest in design.

Main project objectives:

· Literature review on current research and practice of using generative image tools in visual subjects to assess current thinking on AI as a tool for time poor students.

· Quantitative short questionnaire for multi-level cohorts registered on Q61 and R63 design degrees to assess student views, confidence, and current practice with visual AI software. Further qualitative section to identify students for focus group, specifically T217 enrolees academic year 24/25, using tiered engagement analysis.

· Qualitative cross level student focus group - 6/8 students from T217, to test AI tools vs traditional visual communication and ideation techniques. Combined synchronous/asynchronous visual task. Comparative results collated and reviewed for success criteria of output, time saved and benefit to process thinking.

The anticipated outcome and impacts of this project:

· Approve transparent use of AI image tools in STEM modules to support visual communication skills and ideation. Informing and future proofing curriculum decisions.

· Upskill students and enhance preparedness for a rapidly evolving human/AI co-ideation workforce and employability in line with new R63 design degree parameters, meeting industry standards.

· Enable students to enhance their visual practice in an accessible and critical manner using appropriate tools and ethical practice.

· Improve skills and confidence in visual presentation for STEM students from interdisciplinary modules.