Enhancing ophthalmology students’ awareness of retinitis pigmentosa: assessing the efficacy of ChatGPT in AI-assisted teaching of rare diseases—a quasi-experimental study

BackgroundRetinitis pigmentosa (RP) is a rare retinal dystrophy often underrepresented in ophthalmology education. Despite advancements in diagnostics and treatments like gene therapy, RP knowledge gaps persist. This study assesses the efficacy of AI-assisted teaching using ChatGPT compared to tradi...

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Bibliographic Details
Main Authors: Jiamu Zeng, Kexin Sun, Peng Qin, Shulin Liu
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-03-01
Series:Frontiers in Medicine
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Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2025.1534294/full
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Summary:BackgroundRetinitis pigmentosa (RP) is a rare retinal dystrophy often underrepresented in ophthalmology education. Despite advancements in diagnostics and treatments like gene therapy, RP knowledge gaps persist. This study assesses the efficacy of AI-assisted teaching using ChatGPT compared to traditional methods in educating students about RP.MethodsA quasi-experimental study was conducted with 142 medical students randomly assigned to control (traditional review materials) and ChatGPT groups. Both groups attended a lecture on RP and completed pre- and post-tests. Statistical analyses compared learning outcomes, review times, and response accuracy.ResultsBoth groups significantly improved in post-test scores (p < 0.001), but the ChatGPT group required less review time (24.29 ± 12.62 vs. 42.54 ± 20.43 min, p < 0.0001). The ChatGPT group also performed better on complex questions regarding advanced RP treatments, demonstrating AI’s potential to deliver accurate and current information efficiently.ConclusionChatGPT enhances learning efficiency and comprehension of rare diseases like RP. A hybrid educational model combining AI with traditional methods can address knowledge gaps, offering a promising approach for modern medical education.
ISSN:2296-858X