Nursing students’ experiences with generative AI are shaped by both the opportunities and challenges associated with its use in learning, highlighting the need for nursing educators to strengthen students’ AI literacy, critical thinking, and ethical awareness.
Abstract
Objective To systematically evaluate the real experiences of nursing students participating in generative artificial intelligence-assisted learning. Methods Electronic searches were conducted in the China National Knowledge Infrastructure (CNKI), VIP Database, Scopus, Wanfang Data, and the China Biomedical Literature Database (CBM), Web of Science, PubMed, Cochrane, Embase, and CINAHL databases for qualitative studies on the experiences of nursing students with generative AI-assisted learning from the establishment of the databases to March 2026. Qualitative studies on nursing students’ experiences with generative AI-assisted learning were screened, appraised, and synthesized using thematic synthesis. Results Eighteen studies were included in the synthesis. A total of 49 themes were identified and organized into 13 categories, leading to four integrated findings: (1) dual experience of empowerment and challenges, (2) internal conflict between technology and nursing humanism, (3) user experience differentiation amid Practical Constraints, (4) general demand for supporting systems and educational reform. Conclusion This study found that nursing students’ experiences with generative AI are shaped by both the opportunities and challenges associated with its use in learning. These findings highlight the need for nursing educators to strengthen students’ AI literacy, critical thinking, and ethical awareness, for curriculum designers to integrate AI-related competencies into nursing curricula while maintaining a strong emphasis on humanistic care, and for policymakers to establish clear governance frameworks and educational guidelines to support the responsible use of AI in nursing education. Systematic review registration https://www.crd.york.ac.uk/PROSPERO/view/CRD420261367837, identifier CRD420261367837.
Qualitative evidence suggests that registered nurses perceive GAI as a potentially supportive tool for improving efficiency, assisting clinical and research decision-making, and promoting professional development.
Yan Deng, Yidan Zhu, Jiaqi Li et al.· Frontiers in Public Health· 0 citations
Aims: This study aimed to synthesize the scientific literature on the integration of artificial intelligence (AI) into nursing education to significantly enhance learning outcomes. The application of AI in clinical teaching can enhance nursing students' preparation for a technologically advanced healthcare environment.
Methods: This study used a narrative literature review. Key electronic databases, including CINAHL, MEDLINE, Scopus, and Google Scholar, were searched according to the PRISMA guidelines. The review included articles published between 2020 and 2024, written in English, and employing qualitative and quantitative research designs. The search items included AI, ChatGPT, challenges, opportunities, nursing education, technology, students, teaching, and learning. Data were synthesized by summarizing the main results of the included studies.
Results: Ten studies met the inclusion criteria and were included in the review. The findings showed that AI can enhance clinical teaching, improve nursing students' self-efficacy, and support teaching and learning. However, challenges related to academic integrity, assessment quality, unequal access to AI, and inadequate skill development were also identified.
Conclusion: The findings of this study revealed that the use of AI in nursing education is instrumental in improving the acquisition of clinical skills and teaching and learning. Nursing education institutions should create awareness of the safe use of AI. Furthermore, policies should be implemented to ensure that AI use is controlled and adequately monitored. All stakeholders, including patients, students, nurses, and nurse educators, should be developed and provided with adequate resources for effective AI implementation.
S. Khunou, Carine Prinsloo· Indonesian Contemporary Nurs...· 0 citations
Aim: This meta-analysis examined the effectiveness of artificial intelligence (AI)-based educational interventions on learning outcomes in nursing students.Material and Method: A systematic search of PubMed, Scopus, CINAHL, and Web of Science identified studies published between January 2021 and May 2025. Following PRISMA guidelines, 11 studies with 1,539 students were included, comprising randomized controlled trials and quasi-experimental designs. Outcomes assessed were knowledge, clinical reasoning, satisfaction, clinical performance, attitude, and self-efficacy. Risk of bias was evaluated with the RoB 2 tool, and random-effects models were used for meta-analysis.Results: AI-based interventions significantly improved knowledge acquisition (MD = 4.47, 95% CI [2.60, 6.34], p
Orkun Erkayıran· Bandırma Onyedi Eylül Üniver...· 0 citations
AIM
This study aimed to map evidence regarding the role of generative artificial intelligence (GenAI) in developing higher-order thinking skills (HOTS) among nursing students.
BACKGROUND
GenAI is revolutionizing medical education by enabling innovative pedagogical approaches and showing promise in cultivating HOTS. However, its implementation and evidence on its role in fostering HOTS in nursing students remain unclear.
DESIGN
A scoping review.
METHODS
The review was conducted in accordance with the PRISMA-ScR checklist and Arksey and O'Malley methodological framework. Searches were performed in October 2025 and updated in February 2026 across eight databases: PubMed, Ovid EMBASE, CINAHL, Web of Science, PsycINFO, Cochrane Library, Education Source and ERIC. Two reviewers independently screened the studies in a blinded manner. Seventeen articles were included. Data were analyzed using interpretive description to summarize study characteristics, followed by thematic analysis to identify relevant themes.
RESULTS
Studies showed the dual role of GenAI in cultivating HOTS in nursing education. Three key themes were identified, including: (1) the paradoxical reconstruction of cognitive dynamics; (2) tensions and frictions at the human-AI interface; and (3) reshaping learning and professional identity in the AI era.
CONCLUSIONS
The dual role of GenAI in HOTS development indicates that nursing education should integrate GenAI judiciously. While GenAI offers potential benefits for HOTS development, it also introduces risks related to cognitive dependence and reduced critical engagement. Furthermore, efforts should focus on improving the quality of human-AI collaboration, with particular attention to humanistic care, thereby helping students positively reshape their professional perceptions.
Yan Ning, Shanshan Sun, Yi Lu et al.· Nurse Education in Practice· 0 citations
Thematic analysis revealed that various factors underpinning their attitudinal, normative, and control beliefs are critical determinants of nurses' and students' overall experiences with GenAI and their intentions to use GenAI technologies.
Ming Wei Jeffrey Woo, Adrian Heng Tsai Tan· Nursing and Health Sciences· 0 citations