Emerging Technologies for Design Education

Learning to design educational tools and materials continues to be a vibrant area of both scholarly research and professional practice. Within our own design education programs at Marsal, including the Designing for Innovation: Learning, Instruction, and Technology master's program and the Learning Experience Design graduate certificate, we are actively investigating how emerging technologies can offer new forms of intellectual and instructional support for students and instructors.

Our work explores three key applications of emerging technologies to enhance learning and instruction in design education:

(1) GenerativeAI (GenAI) as a Design Partner. This project investigates the potential of GenAI as an “intellectual partner” for students in design education. Here, we are examining how GenAI can support Learning Experience Design (LXD) students as they engage in new, complex design activity, offering tailored guidance and recommendations that fit the LXD learner's evolving design capability, without completing the work for them. 

(2) Online Learning for Design Education. Drawing on our work in massive open online courses (MOOCs) that introduce a global audience of learners to the LXD profession, this project explores how emerging technologies like GenAI are shaping current design practice. We are also testing the AI-generated instructor avatars to see if they offer a more scalable way to maintain and refresh course materials and how learners might respond to instruction from digital avatars. 

(3) Wearable Technologies for Design Education Instruction. This project examines how wearable technologies can assist instructors in real time. For example, we are testing smart glasses that incorporate heads-up displays to deliver relevant, real-time information directly to instructors while they teach, assessing both the utility and potential distraction of “in-the-moment” information. 

Our team is experimenting with custom GPTs as prototypes toward building an integrated "ready-to-hand" tool designed to fit seamlessly within students’ workflows, supporting their work within complex design spaces. To explore broader adoption of GenAI in LXD practice, we are applying quantitative ethnography methods to MOOC data to examine how practitioners perceive the benefits and drawbacks of these tools in their work. To test scalable implementation, we are designing AI-generated instructor avatar videos for selected MOOC modules to evaluate their potential for enhancing course content and gauge learner engagement. Finally, we are exploring smart glasses APIs to determine how custom, AI-driven applications might support real-time instruction within design education contexts.

External collaborators include Yuanru Tan (University of Wisconsin, Madison) and Annie Zhou,  (University of Wisconsin, Madison).

Review our recent publications

• Generative AI as a Learning Design Partner (online course series)
• Unpacking the Design of a an Online Course Series: Generative AI as a Learning Design Partner (journal article)
• How Professional Experience Shapes Reflection in a MOOC on Generative AI and Learning Design (AERA 2026 poster presentation)
• Using Affordance Analysis to Strategize the Integration of AI-Produced Instructor Avatars Within MOOCs (AERA 2026 poster presentation)