ArticleBMC medical education2025
Exploring the integration of AI and national quality courses in China: a study on teaching practices in nursing smart education.
Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence in Nursing Practice Education: A Systematic Review and Meta-Analysis.Journal of nursing management · 2026Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
introductionThe 2024 Global MOOC and Online Education Conference, held in the UK with the theme "Reconstructing Future Higher Education in the Intelligent Age," first proposed that global higher education has entered the "Year of Smart Education." With the global promotion of education digitalization, the trend of "AI+higher education" is becoming increasingly prominent. As a key component of China's education reform, the deep integration of national high-quality curricula and artificial intelligence is crucial for developing digital learning models. This study utilizes generative AI to develop personalized curriculum enhancement models (such as AI teaching/learning partners), using the Chinese national high-quality course"Nursing Ethics" as an example, to investigate smart education models through teaching reform. Its objectives include integrating AI into Nursing Ethics, constructing an intelligent curriculum system, evaluating application effectiveness, and summarizing reform achievements.
methodFour complete classes were randomly assigned to either the control group or the experimental group. The experimental group adopted an AI-assisted blended learning mode, while the control group retained traditional teaching methods. A comparative study was conducted to evaluate differences in student satisfaction and academic performance between the two groups.
resultThe experimental group demonstrated significantly higher satisfaction and academic performance compared to the control group (p<0.05). DISCUSSION: Students in the "AI + National High-Quality Course" blended learning model showed significantly better outcomes in final examination scores and course satisfaction surveys. These preliminary findings suggest that integrating AI technology with high-quality curriculum resources may constitute a feasible and student-preferred strategy for enhancing nursing ethics education effectiveness.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.