Enhancing Complex Clinical Reasoning through AI-Driven Adaptive Learning for Allied Health Professionals

Apply and key information

This project is funded by:

Department for the Economy (DfE)
Vice Chancellor's Research Scholarship (VCRS)

Summary

Artificial Intelligence (AI) is transforming healthcare, not only in clinical settings but also in the education of healthcare professionals. Allied Health Professionals (AHPs) are increasingly taking on advanced practice and first contact roles that demand high-level clinical reasoning, diagnostic skills, and adaptability. Arguably, traditional educational methods may lack the flexibility and personalisation required to effectively develop these competencies. This PhD project proposes the development of an AI-driven adaptive learning platform that will enhance the decision-making skills of physiotherapists, with potential for scalability across other AHP professions.

Proposed Methods:

Systematic Review: A systematic review of AI applications in healthcare education will be conducted with an aim of identifying effective strategies and current gaps in AI-driven learning tools.

Competency Mapping: Competencies required for advanced practice or first contact roles will be mapped to professional standards. These will then be used to guide the content and design of the learning platform.

Platform Development: A prototype of an AI-driven adaptive learning platform that adjusts to each learner’s progress, creating personalized learning pathways will be developed, incorporating dynamic, case-based scenarios that simulate complex clinical decisions and allow users to experience the consequences of their choices.

Pilot Study: The platform will be piloted with physiotherapy students working towards advanced practice, assessing its impact on clinical reasoning and adaptability, quantitative and qualitative feedback will be collected to refine the platform.

Refinement and Study Protocol: The platform will be refined based on pilot feedback and developed into a study protocol for a larger, definitive trial, with potential for expansion to other AHP groups.

This PhD project aims to support AHP training by developing a scalable, AI-enhanced learning tool that develops critical decision-making skills essential for advancing practice.

Essential criteria

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.

Experience using research methods or other approaches relevant to the subject domain

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

Masters at 65%
Experience using research methods or other approaches relevant to the subject domain
Relevant professional qualification and/or a Degree in a Health or Health related area

Equal Opportunities

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.

Funding and eligibility

This project is funded by:

Department for the Economy (DfE)
Vice Chancellor's Research Scholarship (VCRS)

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.

Due consideration should be given to financing your studies.