The incorporation of AI in Higher Education is not some distant future; it is already here. Internet searches use complex AI models to rank the most relevant content. AI writing and design support is built into standard tools such as Microsoft Word and PowerPoint. Services such as Grammarly, an AI typing assistant, can not only review spelling, punctuation, and grammar, but provide suggestions around clarity, engagement, tone, and style.
In late 2022 generative AI tools based on Large Language Models, such as ChatGPT, caught the attention of Higher Education professionals because of their generative nature. That is, they have the ability to generate coherent and fluent human-like text in response to an input prompt. Generative AI models are trained on a large dataset of existing data and then generate new, previously unseen data statistically based on the training data.
The primary concern for Higher Education that has arisen around generative AI is in regards to student assessment, but this has opened up a great many other, often deeper, questions about practices in higher education–and even the purpose of teaching in universities. There are no easy answers to these questions, but, like all HEIs, Durham have been working to guide and support students and staff in the journey to address these questions as generative AI and its uses evolve.
The following is a collection of resources that have been developed for University members, and in some cases the wider HE community, and further information on training and support.
Resources
A student guide to generative AI
Explores how and whether generative AI tools can be used in learning, module assessments, and exams, the risks and ethical issues associated with it and prompt engineering
Assessment and marking in light of generative AI
A discussion of approaches that are consistently recommended in the literature, and which have begun to prove successful in practice
Generative AI in Higher Education: professional and accrediting body responses
A collection of discipline-specific responses to generative AI
ChatGPT, Generative AI and Large Language Models in HE Learning & Teaching
Curated research, insights and resources
Resources internal to Durham University
- Institutional Policy on Generative Artificial Intelligence for Learning, Teaching and Assessment, June 2025
- Guidance on writing a departmental Generative AI policy, December 2023
- Guidance on Generative AI in Learning, Teaching and Assessment, March 2023
- Briefing Paper on Generative Artificial Intelligence in Higher Education, March 2023
- Other University policies: Learning and Teaching Handbook 6.2.4.1 Academic Misconduct: Plagiarism (see sub-section 2); CIS Generative AI policy; Guidance on Generative AI in Research
Events, research and scholarship
Integrating an AI Chatbot for enhanced student learning in a laboratory module
Durham University case study
Exploring the impact of Generative AI on Modern Language Learning in Higher Education
Durham University case study
Understanding student experiences and attitudes towards Generative AI
Durham University case study
Queen’s University Belfast and Durham University Joint Symposium on Generative AI in Learning and Teaching
Recordings from event on 11 September 2024
Events internal to Durham University
- 2024 Durham Learning & Teaching Conference, 19 September 2024 (featuring multiple strands on generative AI): recordings
- 2025 Durham Learning & Teaching Conference, 15 September 2025 (featuring multiple strands on generative AI): recordings
Training and support for Durham University colleagues
- Search Inkpath for ‘GenAI’ to find upcoming hands-on sessions
- See Teaching and Learning Workshops for pedagogy-focused sessions
- Contact the Learning Design Team for bespoke support
Support for Durham University students
- A student guide to generative AI
- Using Generative AI to support learning (videos created by the Biosciences department)
- Careers & Enterprise AI Resources