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Learning Adaptation in Artificial Intelligence-Enabled Nursing Education: A Network Analysis of Artificial Intelligence Literacy, Self-Regulated Learning and Academic Resilience

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 com…

By the Truvace desk1 min read1 sourcePeer-reviewedTRV-2026-1950· cite & verify
Learning Adaptation in Artificial Intelligence-Enabled Nursing Education: A Network Analysis of Artificial Intelligence Literacy, Self-Regulated Learning and Academic Resilience
USAID, USACE team up to renovate nursing school in Georgia (5138983389) by U.S. Army Corps of Engineers Europe District from Wiesbaden, Germany. Public domain

In brief

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.

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.

Main points

  1. 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.
  2. Design A cross-sectional survey.
  3. Methods Using convenience sampling, 1784 undergraduate nursing students were recruited from five universities in Hunan Province, China, between March and May 2026.

The gain

Learning Adaptation in Artificial Intelligence-Enabled Nursing Education: A Network Analysis of Artificial Intelligence Literacy, Self-Regulated Learning and Academic Resilience: 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.

The rundown

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.

Sources

  1. Peer-reviewedJournal of Advanced Nursing2026-10-15

The debate