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Learning Adaptation in Artificial Intelligence-Enabled Nursing Education: A Network Analysis of Artificial
Xueqing Gong1, Zemei Xiao2, Dan Chen1
1School of Nursing, Hunan Normal University, Changsha, Hunan, China.
Aims:
To examine the interconnections among artificial intelligence literacy, self-regulated learning strategies, and academic resilience in undergraduate nursing students, and to conduct an exploratory comparison of network characteristics between students with and without clinical practice experience.
Design:
A cross-sectional survey.
Methods:
Using convenience sampling, 1784 undergraduate nursing students were recruited from five universities in Hunan Province, China, between March and May 2026. Participants completed a demographic questionnaire and three validated scales. Network analysis estimated node strength, bridge strength, and predictability. Bootstrap procedures assessed network accuracy and stability, and the Network Comparison Test was used to conduct an exploratory comparison between students with and without clinical practice experience.
Results:
The 10-node network contained 35 non-zero edges and had a mean predictability of 62.6%. Artificial intelligence evaluation showed the highest node strength, followed jointly by monitoring learning strategies and cognitive maturity. Evaluating and revising learning strategies showed the highest bridge strength, followed by cognitive maturity. In the exploratory subgroup analysis, the overall network structure differed between students with and without clinical practice experience, whereas global strength did not.
Conclusions:
Artificial intelligence evaluation, monitoring learning strategies and cognitive maturity showed relatively high node strength, whereas evaluating and revising learning strategies and cognitive maturity showed relatively high cross-domain bridge strength.
Implications For The Profession:
Findings may inform nursing curricula integrating artificial intelligence literacy, learning regulation, and academic adaptation.
Impact:
This study addressed fragmented understanding of these capacities. It identified dimensions with relatively high node strength and bridge strength, providing exploratory evidence for future nursing education research.
Reporting Method:
This study was reported in accordance with the STROBE statement.
No Patient Or Public Contribution:
This study did not involve patients, service users, caregivers, or members of the public.
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