This project is funded by:
Artificial Intelligence (AI) is dramatically disrupting traditional patterns of teaching, learning and assessment in tertiary education. This PhD focuses on the impacts of Generative AI (GenAI) in Higher Education Institutions (HEIs) as applied across the spectrum of Built Environment (BE) education, where proprietary language, design, modelling, visualisation, and statistical tools are readily available and rapidly developing in sophistication. Beyond practice-focused skills, this PhD will examine impacts of integrating or excluding GenAI tools for BE student’s learning, critical development, and assessment/Quality Assurance. It will also consider the implications for including or excluding students from using these tools with education aims, and arguments for skilled human input and critical evaluation of GenAI technologies.
The PhD will connect pedagogic theory and student’s rights to be educated with intellectual, technical and interpersonal skills to enhance employability and life-long opportunities alongside the challenges for HEIs and BE educators to use the vast range of GenAI emerging for BE education and practice. Ensuring quality assurance of teaching and the inclusivity, authenticity and appropriateness of assessment will be inherent considerations as outcomes relevant for international academic communities of practice.
Proposals should consider how GenAI and associated software/hardware focused pedagogies addresses concerns over digital poverty, tools outpacing national regulatory adaptation, content usage and consent, impacts on real-world understandings, provenance of processes used to generate content, monitoring deeper deep fakes, and for student’s learning challenges to maintain a diversity of opinions, enabling students to find their voice and form their own critically aware opinions and judgements (UNESCO,2023).
Given the PhD’s pedagogic focus and supervisory team expertise across BE subjects including architecture, planning, real estate, and environmental health, applicants should have an explicit interest in BE education and be comfortable applying cross-disciplinary methodologies. Familiarisation with GenAI tools and application by industry professionals, and pedagogic theory should be illustrated in proposals.
Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.
We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.
In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.
The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.
Appointment will be made on merit.
This project is funded by:
Our fully funded PhD scholarships will cover tuition fees and provide a maintenance allowance of £19,237 (tbc) per annum for three years* (subject to satisfactory academic performance). A Research Training Support Grant (RTSG) of £900 per annum is also available.
These scholarships, funded via the Department for the Economy (DfE) and the Vice Chancellor’s Research Scholarships (VCRS), are open to applicants worldwide, regardless of residency or domicile.
Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.
*Part time PhD scholarships may be available, based on 0.5 of the full time rate, and will require a six year registration period (individual project advertisements will note where part time options apply).
Due consideration should be given to financing your studies.
Alasadi E and Baiz C (2023) ‘Generative AI in Education and Research : opportunities, concerns and solutions’ Journal of Chemical Education, 100, pages 2965-2971.
Chew, Z.X. et al. (2024) ‘Generative Design in the Built Environment’, Automation in Construction, 166
Chiu T (2023) The impact of Generative AI on practices, policies and research direction in education : a case of ChatGPT and Midjourney’ Interactive Learning Environments.
Ghanbaripour, A.N. et al. (2024) ‘A Systematic Review of the Impact of Emerging Technologies on Student Learning, Engagement, and Employability in Built Environment Education’, Buildings, 14(9).
Horne, M. and Thompson, E.M. (2008) ‘The Role of Virtual Reality in Built Environment Education’, Journal for Education in the Built Environment, 3(1), pp. 5–24.
Lane, R. et al. (2024) ‘Role of local governments and households in low-waste city transitions’, Environmental Innovation and Societal Transitions, 52
Qadir, J (2023) ‘Engineering education in the era of Chat GPT: promise and pitfalls of generative AI for education’ 2003 IEEE Global Engineering Education Conference (EDUCON) Proceedings
Rane, N., Choudhary, S. and Rane, J. (2023) ‘Integrating ChatGPT, Bard, and Leading-edge Generative Artificial Intelligence in Architectural Design and Engineering: Applications, Framework, and Challenges’. Rochester, NY:
Su J and Yang W (2023) ‘Unlocking the power of ChatGPT : A framework for applying generative AI in education’ ECNU Review of Education, Volume 6(3) pages 355-366.
Tabuenca, B. et al. (2024) ‘IoT and Generative AI Technologies to Support Urban Environmental Learning’, in 2024 IEEE Global Engineering Education Conference (EDUCON).
UNESCO (2023) ‘Guidance for generative AI in education and research’ ISBN 978-92-3-100612-8
Wu Yi (2023) ‘Integrating Generative AI in Education : How ChatGPT brings challenges for future learning and teaching’ Journal of Advanced Research in Education, Volume 2, Number 4.
Yu H and Gao (2023) ‘Generative artificial intelligence empowers educational reform, current status, issues and prospects’ Frontiers in Education, 8:1183162.
Submission deadline
Monday 24 February 2025
04:00PM
Interview Date
April 2025
Preferred student start date
15 September 2025
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