Insights Gained from Using AI to Produce Cases for Problem-Based Learning
Ulster University’s School of Medicine embraces a problem-based learning (PBL) approach, yet crafting scenarios for this method poses challenges, requiring collaboration among medical and academic experts who are often difficult to convene. This obstacle can compromise scenario quality and ultimatel...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
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| Series: | Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-3900/114/1/5 |
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| Summary: | Ulster University’s School of Medicine embraces a problem-based learning (PBL) approach, yet crafting scenarios for this method poses challenges, requiring collaboration among medical and academic experts who are often difficult to convene. This obstacle can compromise scenario quality and ultimately impede students’ learning experiences. To address this issue, the school trialed the use of AI technology to develop a case scenario focusing on headaches caused by cerebral haemorrhage. The process involved a dialogue between a single “author” and ChatGPT, with their outputs combined into a complete clinical case adhering to the school’s standard template. Six experienced PBL tutors conducted quality checks on the scenario. The tutors did not immediately endorse its use, recommending further enhancements. Suggestions included updating terminology, names, spelling, and protocols to align with current best practices, providing additional explanations such as interventions and improvements post-initial stability, incorporating real scans instead of descriptions, reviewing symptoms and timelines for realism, and addressing comprehension issues by refraining from directly providing answers and including probing questions instead. From this trial, several valuable lessons were learned: AI can assist a single author in crafting medical scenarios, easing the challenges of organizing expert teams. However, the author’s role shifts to reviewing and enhancing depth, guided by a template, with clinician input crucial for authenticity. ChatGPT respects patient data privacy and confidentiality by abstaining from providing scanned images, and while AI can generate discussion questions for tutorials, it may require modification to enhance specificity and provoke critical thought. Furthermore, AI can generate multiple-choice questions and compile reading resources to support self-directed learning. Overall, adopting AI technology can improve efficiency in the case-writing process. |
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| ISSN: | 2504-3900 |