LICAMM Enhancing Medical Education through AI

Artificial intelligence (AI) offers significant opportunities for transforming medical education by positively impacting learning experiences, providing tutoring systems, and simulating clinical environments. This study seeks to explore how AI can reshape teaching and learning by supporting advancements in the medical curriculum. The project is a collaboration involving the School of Medicine, Computing and Education where the primary focus could be to identify the most effective AI applications, use specific AI-driven tools like chatbots, or provide evidence-based recommendations for incorporating AI into healthcare education (or other relevant areas of interest). Given the potential global relevance of AI advancements, this study will examine the impact on medical education within the University of Leeds as a case study and will shape how these tools can be applied to LICAMMs portfolio of clinical programmes to provide recommendations for AI use in healthcare training and grow the evidence base in this area.

<p>AI's integration into medical education offers an innovative way to enhance and transform learning through systems that can cater to both students’ and educators’ needs. This doctoral study is designed to investigate AI tools that will support teaching and learning in medical education, with the specific goals of identifying impactful AI applications, creating AI-based tools, and evaluate a framework for an AI-integrated curriculum in healthcare programmes.</p> <p>The project will begin with a detailed review of AI technologies that can be adapted for use in LICAMMs portfolio of clinical programmes. Applications may include virtual platforms, tutoring systems, diagnostic simulations, or personalised learning tools. These applications will be evaluated for their capacity to improve both theoretical knowledge and clinical skills, which are crucial for medical students.</p> <p>A key part of the project could evaluate the use and impact of AI-driven tools, such as chatbots (Aleedy et al 2022, Alsafari et al 2024). These tools could be trained using subject-specific data from medical courses to assist students with common queries, offer real-time feedback on assignments, or simulate medical scenarios that enhance clinical decision-making. For example, chatbots could serve as virtual tutors, and engage students to guide them through clinical questions or complex case studies (Ghorashi, et al 2023).</p> <p>To measure the effectiveness of AI applications, several methods of analysis could be conducted with both students and staff to understand their perspectives on AI’s role in medical education. These qualitative and quantitative data will provide valuable insights into the perceived benefits and potential challenges of AI integration.</p> <h5>References</h5> <ol> <li>Mir, M.M., Mir, G.M., Raina, N.T., Mir, S.M., Mir, S.M., Miskeen, E., Alharthi, M.H., and Alamri, M.M.S. (2023) 'Application of Artificial Intelligence in Medical Education: Current Scenario and Future Perspectives', Journal of Advances in Medical Education & Professionalism, 11(3), pp. 133-140.</li> <li>Ghorashi, N., Ismail, A., Ghosh, P., Sidawy, A., and Javan, R. (2023) 'AI-Powered Chatbots in Medical Education: Potential Applications and Implications', Cureus, 15(8).</li> <li>Alsafari, B., Atwell, E., Walker, A., and Callaghan, M. (2024) 'Towards effective teaching assistants: From intent-based chatbots to LLM-powered teaching assistants', Natural Language Processing Journal, 8.</li> <li>Aleedy, M., Atwell, E., and Meshoul, S. (2022) 'Towards Deep Learning-Powered Chatbot for Translation Learning', in Zaphiris, P., Ioannou, A. (eds.) Learning and Collaboration Technologies. Novel Technological Environments. HCII 2022. Lecture Notes in Computer Science, vol. 13329. Springer, Cham.</li> </ol>

<p>Please note these are not standalone projects and applicants must apply to the PhD academy directly.</p> <p>Applications can be made at any time. You should complete an <a href="https://medicinehealth.leeds.ac.uk/faculty-graduate-school/doc/apply-2">online application form</a> and attach the following documentation to support your application. </p> <ul> <li>a full academic CV</li> <li>degree certificate and transcripts of marks (or marks so far if still studying)</li> <li>Evidence that you meet the programme’s minimum English language requirements (if applicable, see requirement below)</li> <li>Evidence of funding to support your studies</li> </ul> <p>To help us identify that you are applying for this project please ensure you provide the following information on your application form;</p> <ul> <li>Select PhD in Medicine, Health & Human Disease as your planned programme of study</li> <li>Give the full project title and name the supervisors listed in this advert</li> </ul>

A degree in biological sciences, dentistry, medicine, midwifery, nursing, psychology or a good honours degree in a subject relevant to the research topic. A Masters degree in a relevant subject may also be required in some areas of the Faculty. For entry requirements for all other research degrees we offer, please contact us.

Applicants whose first language is not English must provide evidence that their English language is sufficient to meet the specific demands of their study. The minimum requirements for this programme in IELTS tests are: • British Council IELTS - score of 7.0 overall, with no element less than 6.5

<p>For further information please contact the Faculty Admissions Team:<br /> e:<a href="mailto:fmhpgradmissions@leeds.ac.uk">fmhpgradmissions@leeds.ac.uk</a></p>