How might generative AI help us develop new and interesting ways to teach? What potential AI applications might academics want to use, but don’t have the skills or time to build? How might generative AI be used to develop creative and practical ways of doing teaching differently?
This project is about supporting and enabling creative teaching innovation through generative AI, by providing course teams with learning design and app development support to build prototypes. It aims to develop our capacity as an institution to think widely and creatively about human/machine partnerships in education innovation, while supporting staff skills development and capacity for working with AI in their teaching, assessment and feedback.
It’s part of the University's AI adoption programme of work, and a partnership between the Edinburgh Futures Institute (EFI) and the Moray House School of Education and Sport.
The project is working with ten groups in various parts of the university to create – and research the use of – custom apps for use in live teaching contexts. Projects are:
EnviroForum – Valentina Erastova, School of Chemistry
Simulating interviews with stakeholders in environmental projects, eg land managers, government advisors, environmental protection officers and engineers working on critical issues such as nuclear waste management, peatland restoration and plastic recycling.
Entrepreneurial Personas – Augusto Rocha, Business School
Developing investor personas for students to simulate and explore investor perspectives, including contexts, values and concerns.
Sura Suritaa – Nana Barker, Centre for Open Learning
Developing a fun, AI-powered storytelling app that enhances learners' writing skills in Japanese, tailored to different proficiency levels.
The Virtual Ward – Steven McCarthy, Edinburgh Medical School
Using AI to generate realistic case scenarios that stimulate clinical decision-making by students, then provide appropriate, evidence-based feedback.
Try This – Jane Alexander and Jane McKie, Creative Writing
Offering students unexpected ways of developing their creative work by prompting them to challenge their default habits as writers.
AI Learning Scenarios – Chris McKenzie, Medicine and Veterinary Medicine
Generative AI for creating interactive, customisable environments in which staff can design discipline-specific scenarios tailored to their courses.
Voices from the Past – Marc Di Tommasi, History
Using the entire writing corpus of renowned historians to create virtual personas allowing students to engage in dynamic conversation with historians of the past.
Feedback Moderation Coordinator – Pavlos Andreadis, Informatics
AI to assist with coordination of marking, moderation and feedback for assessment among a large group.
Consult-Ed – Lin Watson, School of Medicine
Developing AI chatbots for students to gain a realistic idea of patient context, and to help training for holistic assessment, diagnosis and case management.
Interviewing Law Skills Practice – Hermione Hague, Law
AI to enhance the training of law students in professional skills and responsibility, particularly in the interviewing techniques required in legal practice.
We are working with two more projects on the research dimension only:
LabBuddy – David Reid, Engineering
Creating a ‘lab assistant’ to support students during STEM laboratory activities. In particular during remote laboratory tasks that are undertaken both in-person and independently outside the classroom.
Rubricate – Ian Graham, Business School
Building a service that will use generative AI to provide assessment feedback and grades consistent with a grading rubric.
The project is led by Prof Sian Bayne (Assistant Principal Education Futures) and Javier Tejera (Senior Learning Design and Technology Advisor in EFI).
Our app developers are Anna Kapron-King, Yvonne Ding and Kokulan Thangasuthan.
