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Background <p>Generative AI (GenAI) presents both opportunities and challenges for higher education. While it offers the potential to personalise learning and improve educator processes, concerns around academic integrity and output accuracy persist. Health professionals must navigate this landscape carefully to ensure technology augments, rather than compromises, the development of core clinical and professional competencies in higher education.</p> Objective <p>This study aimed to develop a framework for implementing GenAI into the curriculum. To achieve this, a synthesis of the existing evidence on the applications, benefits, and challenges of GenAI in health professions education was required.</p> Methods <p>To achieve the required knowledge for the development of the framework, a systematic scoping review was conducted following the Joanna Briggs Institute (JBI) methodology and reported using the PRISMA-ScR guidelines. A comprehensive search of MEDLINE, CINAHL, Scopus, Web of Science, and ERIC databases was performed to identify relevant studies. A narrative synthesis was used to map the literature across key themes to inform the framework’s development. Results:&#xa0;The review included 21 studies, which highlighted the use of GenAI by educators and students to aid in productivity and learning. Key challenges identified included the risk of generating inaccurate content, the potential for misuse, and the critical need for enhanced GenAI literacy among both students and staff. The findings were synthesised into three primary domains: educator use, student use, and assessment design and purpose.</p> Conclusion <p>The integration of GenAI in health education requires a structured, proactive approach. We propose an evidence-informed framework centred on three core pillars: Student GenAI Literacy, Educator Capability, and Assessment Design. This framework provides a roadmap for institutions to harness GenAI responsibly, ensuring it serves as a tool to support critical thinking and professional judgement.</p>

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Integrating Generative AI in Health Education: A Scoping Review and Implementation Framework

  • 期刊论文

  • 发表日期：

    2025年12月12日

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  • Kellie Toohey,
  • Zach Quince,
  • Felicity Walker,
  • Linda Furness,
  • Michelle Bissett,
  • Carlie Daley,
  • Kachina Allen,
  • Natalie Munro,
  • Andy Smidt,
  • Jodie Cochrane Wilkie,
  • Louise Horstmanshof,
  • Kathryn Baltrotsky,
  • Fiona Naumann

摘要

Background

Generative AI (GenAI) presents both opportunities and challenges for higher education. While it offers the potential to personalise learning and improve educator processes, concerns around academic integrity and output accuracy persist. Health professionals must navigate this landscape carefully to ensure technology augments, rather than compromises, the development of core clinical and professional competencies in higher education.

Objective

This study aimed to develop a framework for implementing GenAI into the curriculum. To achieve this, a synthesis of the existing evidence on the applications, benefits, and challenges of GenAI in health professions education was required.

Methods

To achieve the required knowledge for the development of the framework, a systematic scoping review was conducted following the Joanna Briggs Institute (JBI) methodology and reported using the PRISMA-ScR guidelines. A comprehensive search of MEDLINE, CINAHL, Scopus, Web of Science, and ERIC databases was performed to identify relevant studies. A narrative synthesis was used to map the literature across key themes to inform the framework’s development. Results: The review included 21 studies, which highlighted the use of GenAI by educators and students to aid in productivity and learning. Key challenges identified included the risk of generating inaccurate content, the potential for misuse, and the critical need for enhanced GenAI literacy among both students and staff. The findings were synthesised into three primary domains: educator use, student use, and assessment design and purpose.

Conclusion

The integration of GenAI in health education requires a structured, proactive approach. We propose an evidence-informed framework centred on three core pillars: Student GenAI Literacy, Educator Capability, and Assessment Design. This framework provides a roadmap for institutions to harness GenAI responsibly, ensuring it serves as a tool to support critical thinking and professional judgement.