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

BACKGROUND

Retinitis 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.

METHODS

A 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.

RESULTS

Both groups significantly improved in post-test scores ( < 0.001), but the ChatGPT group required less review time (24.29 ± 12.62 vs. 42.54 ± 20.43 min,  < 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.

CONCLUSION

ChatGPT 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.