Aug 2026· Nurse Education in Practice· Vol 96, pp.
104948
· 0 citations· 56 references
Medicine
TL;DR
The dual role of GenAI in HOTS development indicates that nursing education should integrate GenAI judiciously, and 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.
Abstract
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.
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
The findings suggest that concept mapping may be an effective learner-centered teaching strategy for strengthening critical thinking among undergraduate nursing students.
Barkha Devi, Champa Sharma, Shrijana Pradhan et al.· The Malaysian Journal of Nur...· 0 citations
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
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.
Shanshan Du, Sha Wang, Feng-ming Yan et al.· Frontiers in Medicine· 0 citations
Nursing academics appear to adopt AI selectively, prioritising preservation of core professional values while embracing applications perceived to enhance, rather than replace, educational practice, providing evidence for nursing education programs globally regarding faculty development, institutional policy frameworks, and curriculum design strategies integrating technological advancement whilst maintaining person-centred values.
Natasha Hawkins, Anthea Fagan, Yumiko Coffey et al.· Journal of Advanced Nursing· 0 citations
Introduction: The integration of Evidence-Based Practice (EBP) into nursing education faces challenges in linking theory to clinical application in complex family health contexts. Students struggle with efficiently accessing, appraising, and applying evidence influenced by sociocultural factors. Artificial intelligence (AI) offers transformative potential but requires pedagogical design to foster critical thinking and ethical use beyond technical skills.Method: An action research with mixed methods was conducted with 100 nursing students. The intervention had four phases: participatory family diagnosis, AI-assisted evidence retrieval and validation, community educational workshops design and execution, and multi-level evaluation.Results: A significant shift in AI use from basic to strategic, with a 40% reduction in literature search time. Qualitative data revealed enhanced critical awareness and ethical reasoning, while quantitative results indicated 90% of students improved critical appraisal skills and 70% felt more confident in evidence-based decisions. The project impacted 100 families, with 90% trusting evidence-based recommendations.Conclusions: Integrating AI in experiential pedagogies like Design Thinking and Service-Learning effectively develops nursing competencies, ensuring technology adoption supports context-sensitive family health learning outcomes.
Maria Graciela Villalba-Condori, Carla Cuya-Zevallos· Publicaciones· 0 citations