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Application of generative artificial intelligence by nurse academics in higher education: A scoping review
Journal article   Open access   Peer reviewed

Application of generative artificial intelligence by nurse academics in higher education: A scoping review

Jennifer Hamilton, Martina Costello, Lesley Barr, Simon Cooper and Martin Jones
Nurse Education in Practice, Vol.90, 104669
2026
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CC BY V4.0 Open Access

Abstract

Artificial intelligence Generative AI Nursing students Higher education Academic integrity Scoping review
Aim To systematically map existing research on nurse academics incorporation of generative artificial intelligence when developing teaching and learning resources in higher education and to identify knowledge gaps and future research. Background Generative artificial intelligence technology is rapidly evolving in healthcare and it’s use in nursing higher education is developing. However, concerns regarding its adoption in higher education relate to academic integrity and ethical considerations, including privacy, confidentiality, bias and critical thinking development. Generative artificial intelligence tools present new pedagogy possibilities in nursing higher education; however, the scope and impact of its adoption is unclear. Methods The Joanna Briggs Institute (JBI) methodology for scoping reviews were used to guide this scoping review. Electronic databases were searched from inception until February 2025. Results The search yielded seven quantitative and two qualitative studies. The findings highlight that nurse academics use generative artificial intelligence to assist with student learning and time management. Findings revealed that generative artificial intelligence use may improve student satisfaction and critical thinking skills. Nurse academics were identified as critical role models in academic integrity and the ethical adoption of generative artificial intelligence. Knowledge gaps and opportunities for future research are highlighted. Conclusions The findings highlight the opportunities of generative artificial intelligence use in nursing higher education. Role modelling ethical use of generative artificial intelligence by nurse academics can instil academic integrity principles. However, gaps in evidence on the impact on student education outcomes and industry readiness highlight the need for further research using randomised control trials and longitudinal studies.

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Collaboration types
Domestic collaboration
Citation topics
6 Social Sciences
6.185 Communication
6.185.2797 AI Ethics
Web Of Science research areas
Nursing
ESI research areas
Social Sciences, general
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