GenAI significantly shapes how nursing students construct knowledge and develop academic practice in the BT, and may support autonomy and critical thinking, provided its use remains reflective, ethically grounded and aligned with the discipline's educational objectives.
Abstract
Aim
To explore nursing students' generative artificial intelligence (GenAI) related practices during Bachelor Thesis (BT) preparation and to analyse their levels of technology integration, links with learning, and perceived barriers and facilitators.
Methods
This descriptive qualitative study adopted a constructivist approach. Participants were 66 final-year nursing students who reported using GenAI tools during the preparation and defense of the BT. Data were collected using a qualitative open-ended questionnaire and analysed using thematic analysis. Findings were interpreted using the SAMR model (Substitution, Augmentation, Modification and Redefinition).
Results
GenAI use spanned different levels of technology integration. At the Substitution and Augmentation levels, it primarily supported language correction, refinement of academic tone, and reference management. At the Modification and Redefinition levels, it supported critical reflection, knowledge reorganisation, integration of complex information, and co-creation of student-produced artefacts, with reports of a transformed learning experience. Nevertheless, students expressed concerns about the reliability of the information generated, the need for verification, and the ethical implications of using these tools.
Conclusions
GenAI significantly shapes how nursing students construct knowledge and develop academic practice in the BT. When integrated more fully, it may support autonomy and critical thinking, provided its use remains reflective, ethically grounded and aligned with the discipline's educational objectives. These findings have implications for curriculum design, academic supervision and pedagogical approaches that encourage responsible GenAI use in nursing education.
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
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
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
BACKGROUND
The rapid integration of generative artificial intelligence (GenAI) into nursing education presents both opportunities and challenges, yet empirical evidence on students' critical engagement with AI-generated content within assessment contexts remains limited.
AIM
To examine undergraduate nursing students' reflections when comparing their own evidence-based summaries with AI-generated outputs in response to the same clinical research questions.
METHODS
A qualitative descriptive design was employed using retrospective analysis of 497 assessment submissions from an undergraduate nursing cohort at an Australian university. Students formulated a research question, synthesised peer-reviewed evidence, submitted the same question to an AI tool, and critically reflected on the comparison. Data were analysed using qualitative content analysis and thematic analysis.
RESULTS
Four themes were identified: 1. Credibility, quality of evidence and academic rigour. Students identified fabricated references, outdated information, and absence of peer-reviewed sourcing as key limitations. Additionally, students reflected on algorithmic limitations and the challenge of verifying AI outputs without prior topic knowledge; 2. Critical thinking, depth of analysis, and human intelligence. AI was perceived as unable to replicate contextual reasoning or multi-source synthesis; 3. Efficiency, accessibility, and practical utility. AI's speed and clarity were valued for brainstorming and initial scoping; and 4. Student identity, learning, and professional development were shaped by the view that engaging in manual, hands-on research was integral to forming a safe, evidence-informed nursing identity.
CONCLUSION
This study suggests that structured AI-comparison tasks offer the opportunity to develop AI and digital health literacy in nursing students. Students are neither naively accepting of AI nor reflexively dismissive but are actively working to understand its place within the ethical frameworks of nursing education. These findings contribute to AI integration in nursing education and offer practical guidance for educators seeking to support graduates to be AI-critical and well-equipped to leverage the efficiencies of these tools.
AIM
To examine nursing academics' perceptions and experiences of artificial intelligence (AI) integration in nursing education.
DESIGN
Scoping review.
DATA SOURCES
MEDLINE, CINAHL, ERIC, Scopus, and Web of Science were searched in August 2025.
METHODS
A scoping review using Joanna Briggs Institute methodology. Peer-reviewed original research and reviews published in English (2019-2025) were included if they examined nursing educators' perspectives, attitudes, or experiences with AI in nursing education across undergraduate, postgraduate, and professional contexts. The Substitution, Augmentation, Modification, Redefinition (SAMR) framework was used to classify pedagogical integration levels.
RESULTS
Fifteen studies from eight countries, encompassing 2004 nursing academics, were included. A pattern described as an "adoption paradox" was identified: whilst most academics believe AI will revolutionise nursing education, implementation remains conservative. Two-thirds of applications operate at the augmentation level, with none achieving transformative redefinition. Nursing academics use AI selectively, predominantly for academic productivity and research writing but rarely for student assessment. Primary barriers included knowledge gaps, institutional policy vacuums, and pronounced global access inequities. Academics expressed concerns regarding critical thinking erosion and professional identity threats whilst acknowledging efficiency benefits.
CONCLUSIONS
Nursing academics appear to adopt AI selectively, prioritising preservation of core professional values while embracing applications perceived to enhance, rather than replace, educational practice. The absence of transformative integration suggests perceived incompatibilities between artificial intelligence and nursing's relational foundations, signalling a need for more active pedagogical engagement to bridge this widening gap.
IMPACT
This review addresses the critical gap in understanding how nursing academics integrate artificial intelligence while maintaining professional values. Despite high optimism, actual implementation remains basic, with multiple barriers limiting transformative adoption. Findings provide evidence for nursing education programs globally regarding faculty development, institutional policy frameworks, and curriculum design strategies integrating technological advancement whilst maintaining person-centred values.
NO PATIENT OR PUBLIC CONTRIBUTION
Not applicable, as no patients or public were involved.
Natasha Hawkins, Anthea Fagan, Yumiko Coffey et al.· Journal of Advanced Nursing· 0 citations