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In this case study Deepti Nayak, Eirinaios Tsiartas and Simple Ouma explore how students and tutors can embrace the use of AI tools in the Institute of Clinical Trials and Methodology.

Case study by Fiona Wilkie.

What did you set out to do?

[Through this project,] I aspired to incorporate latest practices in AI-powered teaching and learning into my pedagogical approach at ICTM. By staying abreast of the latest advancements in AI education, I aimed to enhance the effectiveness and engagement of my teaching methods. This endeavour aligns with my commitment to continuous improvement and my passion for fostering a dynamic and engaging learning environment for students.

How did you work with students to achieve this?

Together, we conducted a comprehensive literature review, examining the current landscape of AI-driven teaching methodologies in post graduate courses in healthcare with a focus on online courses and their impact on education. By systematically evaluating the existing body of research, we identified the most promising practices that hold the potential to transform our teaching approach at ICTM. We built on these insights and integrated and evaluated new practice into our modules. The project gave ICTM students the opportunity to benefit from the latest advancements in AI-enhanced education.

What were the learnings around the benefits of AI?

Deepti: We found out from this project that:

1. Most studies we looked up via our literature search focused on the ability of AI to give exams. This was quite an interesting find for us.
2. The next biggest group we found, focused on conducting perception studies about the need for AI in healthcare education.
3. We found that there was no specific review to guide academics in higher education about AI in education with a focus on healthcare. We believe our project will help guide and provide a useful overview about the current roles and potential of AI in healthcare education.

Eirinaios: [We found that] AI can tailor educational content to individual learning styles and paces, and can provide realistic, hands-on training experiences through simulations.
It can offer real-time feedback and guidance to improve student learning, as well as analyse educational data to optimize curriculum and teaching strategies, and can assist in the creation process of assessments tools.

Did the project reveal any concerns about AI?

Deepti: Not a concern as such, but it was quite interesting to see such a focus on detecting the ability of LLMs to give exams. This could be due to the worries about academic integrity.

Eirinaios:

• There's a risk of students becoming too dependent on AI, potentially neglecting the development of critical thinking and hands-on skills.
• Implementing AI technologies can be expensive, potentially creating disparities in access to advanced educational tools between institutions.
• The integration of AI in education raises ethical questions about the role of technology in learning and the potential for AI to replace human educators.

In what ways will your findings feed into your teaching or future aims?Ìý

Deepti: I plan to use best practices I discover from this literature review and hope to use some well studied methods of using AI in my own teaching.

Eirinaios: As a Teaching Dialogue student partner, I played a key role in developing the aims and objectives for a systematic review. I collaborated with a fellow student and our staff partner to create the strategy and protocol for the project. This involved defining the research questions, establishing inclusion and exclusion criteria, and designing a comprehensive search strategy. Additionally, I contributed to the overall development of the project, ensuring a rigorous and methodical approach to our systematic review. This experience enhanced my skills in research planning, teamwork, and project management, which I believe are invaluable in any professional setting.

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