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Pedagogical strategies for enhancing critical thinking in nursing students using large language models: a
Lucy Oh1, Gael Mearns2, Rebecca Mowat3
1School of Nursing, Faculty of Health and Environmental Sciences, Auckland University of Technology, Auckland, New Zealand lucy.oh@aut.ac.nz.
BMJ Open
|July 9, 2026
Summary
This review explores how large language models (LLMs) impact nursing students' critical thinking. It identifies effective teaching strategies to ensure clinical competency with AI integration.
Area of Science:
- Nursing Education
- Artificial Intelligence
- Pedagogical Strategies
Background:
- Large language models (LLMs) are increasingly used in nursing education, but their effect on critical thinking is unclear.
- Existing research often focuses on student satisfaction rather than specific instructional methods for critical thinking development.
- This review addresses the need for evidence-based guidance on fostering critical thinking in an AI-integrated nursing workforce.
Purpose of the Study:
- To identify effective pedagogical strategies for enhancing critical thinking in undergraduate nursing students using LLMs.
- To provide evidence-based recommendations for integrating AI into nursing education to maintain clinical competency.
- To explore the specific instructional mechanisms through which LLMs influence critical thinking development.
Main Methods:
- A convergent segregated mixed-methods systematic review following Joanna Briggs Institute (JBI) methodology.
- Systematic search across major databases (CINAHL, ERIC, MEDLINE, PsycINFO, Scopus) and grey literature (Jan 2023-June 2026).
- Appraisal using JBI Critical Appraisal Checklists, outcome classification via Kirkpatrick framework, and synthesis using narrative and thematic approaches, integrated via Joint Display Analysis.
Main Results:
- (Study currently in progress; results pending dissemination)
- (Anticipated findings will detail effective LLM-based pedagogical strategies for critical thinking)
- (The review will synthesize evidence on instructional design for AI integration in nursing education)
Conclusions:
- Effective pedagogical strategies are crucial for leveraging LLMs to foster critical thinking in nursing students.
- Evidence-based guidance is needed to ensure clinical competency as AI becomes more integrated into healthcare.
- This review will inform educators on best practices for AI-assisted nursing education to uphold safe clinical practice.
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