The AI Design Ed project

• Project leader(s): AnnMarie McKennaCatherine Scott
• Theme: Technologies for STEM learning
• Faculty: STEM
• Status: Current
• Dates: June 2024 to December 2025

The aim of the project is to explore student views and identify appropriate and accessible applications for generative image AI tools for co-ideation in design education. The pedagogical goal is to assess if use of these tools could improve visual communication skills and inclusivity in 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 these tools but are not using them appropriately or productively in their studies, as observed in core design modules U101, T217 and T317. There is a lack of clear ethical usage policy due to the fast-moving technology. Key questions are:

• If a student generates an idea using visual generation software as a tool for visual communication – does that diminish their contribution?
• Whether AI-generated visual content better or equal to content produced from standard presentation tools such as analogue sketching or photoshop?

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 review 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 to assess student views, confidence, and current practice with visual AI software, with qualitative section to identify students for focus group using tiered engagement analysis.
• Qualitative cross level student focus group to test AI tools and traditional techniques in asynchronous visual activity with 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 use of AI image tools in STEM modules to support visual communication skills, informing and future proofing curriculum decisions.
• Embed use of tools in module curriculum to upskill students and enhance preparedness for a rapidly evolving human/AI co-ideation workforce and employability.
• Enable students to enhance their visual practice in an accessible and critical manner using appropriate ethical tools and practice.  
• Improve skills and confidence in visual presentation for STEM students from interdisciplinary modules.