Clinical Report: Utilizing AI-Generated Visual Aids for Ophthalmic Anatomy Education

Overview

This study assessed the impact of AI-assisted comparative exercises versus traditional anatomical labeling on knowledge acquisition and learner satisfaction among medical and non-medical students. No significant differences in knowledge outcomes were found.

Background

The decline in ophthalmology teaching hours has prompted the need for effective educational tools. Generative AI offers innovative methods for teaching anatomy, yet its effectiveness varies based on learner background.

Data Highlights

Key Findings

• No statistically significant difference in post-test knowledge scores between AI and conventional methods (p > 0.05).
• Non-medical students showed higher satisfaction with AI-assisted exercises (p < 0.001).
• Self-assessed performance was better in non-medical students using AI (p = 0.003).
• Composite NASA-TLX scores did not differ between AI and conventional conditions.
• Medical students did not experience the same satisfaction benefits from AI as non-medical students.

Clinical Implications

Further research is needed to optimize AI applications for different learner backgrounds.

Conclusion

AI-assisted comparative exercises may improve learner satisfaction among non-medical students without enhancing immediate knowledge outcomes.

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