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Accepted for/Published in: JMIR Formative Research

Date Submitted: Nov 4, 2025
Date Accepted: Apr 1, 2026

The final, peer-reviewed published version of this preprint can be found here:

Opportunities and Challenges of Generative AI in Postgraduate Health Professions Education Assessments From Educator and Learner Perspectives: Qualitative Study

Phillips C, Harrison D

Opportunities and Challenges of Generative AI in Postgraduate Health Professions Education Assessments From Educator and Learner Perspectives: Qualitative Study

JMIR Form Res 2026;10:e87121

DOI: 10.2196/87121

PMID: 42090618

Opportunities and challenges of Generative AI in postgraduate Health Professions Education assessments: a qualitative study of educator and learner perspectives

  • Carys Phillips; 
  • David Harrison

ABSTRACT

Background:

The application of Artificial intelligence (AI) is increasingly valuable as a tool and assistance in many areas of clinical and academic medicine. ‘Generative AI’ (GenAI) creates new content used by Large language Models (LLMs) which can generate language that strongly resembles or even improves that of humans. Learners and educators in many areas of education are using GenAI for essays and assessments, raising issues regarding learning and assessment. GenAI is also raising new concerns in Healthcare Professions Education (HPE), an area of health professions training that sometimes has different aims and assessment methods from its clinical counterparts. HPE needs to assess levels of knowledge and understanding of pedagogy and the use of GenAI presents challenges to its current assessments, which are predominately written.

Objective:

The aim was to investigate educator and learner perspectives on the opportunities and challenges presented by generative AI in postgraduate HPE assessments. It particularly focused on perspectives of how GenAI may influence the future of assessment and essay-based assessment in HPE.

Methods:

Informed by a constructivist paradigm, a qualitative approach was adopted, undertaking 8 semi-structured interviews via MSTeams. Purposive sampling ensured a mixture of educators and learners on current HPE courses from a range of healthcare professions. Data were thematically analysed.

Results:

There was no difference between educator and learner perspectives. Four themes were identified: AI is here, students are at a disservice if we do not embrace it; AI as an opportunity to rethink HPE assessments; AI is a ‘grey area’ and AI is fallible.

Conclusions:

Findings presented AI as an external catalyst, highlighting current internal desire for assessment change within HPE. It offers opportunities for creative, authentic assessments reflecting real-life academic and clinical practice to develop competent future HPE educators and keep courses relevant. The findings contribute to the debate around future potential and development of AI in HPE assessments. Clinical Trial: NA


 Citation

Please cite as:

Phillips C, Harrison D

Opportunities and Challenges of Generative AI in Postgraduate Health Professions Education Assessments From Educator and Learner Perspectives: Qualitative Study

JMIR Form Res 2026;10:e87121

DOI: 10.2196/87121

PMID: 42090618

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