ArticleFrontiers in public health2026
Artificial intelligence literacy among nursing students and its association with learning engagement.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Current research does not examine how distinct AI literacy profiles are differentially associated with learning engagement, thereby impeding the development of stratified and precise training plans for nursing students. Objective: To identify latent profiles of artificial intelligence literacy among undergraduate nursing students, characterize their distributional features, and examine the relationship between distinct AI literacy profiles and learning engagement. Methods: The study included 479 Chinese undergraduate nursing students who finished the Utrecht Work Engagement Scale-Student Version and the Artificial Intelligence Literacy Scale. Latent profile analysis was conducted using item-level AI literacy scores as manifest indicators. Results: Three distinct profiles of AI literacy were identified: low literacy-ethically cautious, medium literacy-balanced development, and high literacy-fully mature. Non-parametric test results demonstrated significant differences in learning engagement and its dimensions across the three AI literacy profiles. After controlling for relevant confounding factors in multilevel linear regression analyses, AI literacy profile remained significantly associated with learning engagement, accounting for an additional 31.2% of the variance. Students in the medium and high AI literacy groups demonstrated significantly higher levels of learning engagement compared to those in the low literacy group. Conclusion: Undergraduate nursing students' AI literacy is heterogeneous and markedly related to learning engagement. These findings provide valuable insights for improving student engagement in AI-supported learning environments.
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