The Impact of ChatGPT on Problem-Based Learning in Medical Education: A Comparative Study on an Anaphylaxis Tutorial

Projects supported by Funding Scheme for student projects/activities by Tam Wing Fan Innovation Fund and Philomathia Foundation Innovation Fund

Supervisor: Prof. Philip K.T. LI (LKS Faculty of medicine); Dr. Shilpa B. PURDAL (LKS Faculty of medicine); Prof. Kendrick C. SHIH (LKS Faculty of medicine)

Project information

Project descriptions

Generative AI, such as ChatGPT provides many promises, yet its role in medical education remains unclear and controversial. To evaluate the impact of adopting ChatGPT in medical education, we developed a pilot randomised controlled trial to evaluate the impact of ChatGPT on medical students ability to achieve learning outcomes in a problem-based learning (PBL) tutorial on anaphylaxis. We then evaluated the ability of GPT-3.5 and GPT-4.0 to achieve the learning outcomes in the PBL case. Results showed that students who used ChatGPT achieve the learning outcomes better, and GPT-3.5 and GPT-4.0 models of ChatGPT could achieve the PBL learning outcomes with minimal prompting. Nevertheless, the adoption of ChatGPT could also hinder the development of clinical reasoning skills.

Project innovation

To our knowledge, this is the first study in Hong Kong evaluating the impact of ChatGPT on problem-based learning in medicine. This study has implications for adopting generative AI in education with local relevance.


Team information

Project leader: NG Sheung Chit, MBBS

Team member(s): YIU Wing San, MBBS(MRes); CHAN H.M. Derrick, MBBS; AU-YEUNG Yee Man, MBBS/PhD; SONG Zak, MBBS; NG Hoi Chak, MBBS(MPH)

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Winner of the Inno Show Award @ The 6th Inno Show

This project team was selected for the Inno Show award at the 6th Inno Show. 

This team has received HK$20,000 sponsorship to participate in international design competition(s) and consumables expenses to support further development of the project.

The best project award - COMP3329 Computer Game Design and Programming @ The 1st Engineering InnoShow

This project team was selected for the best project award – COMP3329 Computer Game Design and Programming at the 1st Engineering InnoShow.

PERfECT Wearables: for Minimally-Invasive and Continuous Blood-Glucose Monitoring was selected for the Inno Show Award
Photos in the Engineering Inno Show