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How does artificial intelligence improve ophthalmology education outcomes?-The mediating role of learning motivation
Xia Wang1, Siyan Jin1, Ping Hu1
1Ophthalmologic Center of the Second Hospital, Jilin University, Changchun, China.
Background:
Artificial intelligence (AI) is increasingly being applied in medical education, yet evidence on how it translates into achievement it is most effective remains limited in ophthalmology.
Methods:
This cross-sectional study examined undergraduate ophthalmology students at a university in Jilin Province, China. A total of 416 students were randomly selected at two time points-November 2024 and March 2025-corresponding to the autumn 2024 and spring 2025 course cohorts, respectively. Survey measures captured AI usage, learning motivation, self-efficacy, final examination scores, and AI literacy. A moderated parallel mediation model was tested using structural equation modeling.
Results:
AI usage was positively associated with academic performance (β = 0.247, p < 0.001). Indirect effects via learning motivation and self-efficacy were significant, with standardized effects of 0.081 and 0.079, with confidence intervals of 0.059 to 0.103 and 0.017-0.141, respectively. AI literacy strengthened the path from AI usage to learning motivation, interaction (β = 0.183, p < 0.001).
Conclusion:
AI usage is associated with higher ophthalmology academic performance partly through increased learning motivation and self-efficacy, and AI literacy strengthened the AI usage in the learning motivation path. Given the cross-sectional design, longitudinal validation is warranted.
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