'Apply caution' Medical educator perspectives on undergraduate students using AI in reflection: a qualitative study.
TL;DR
How undergraduate primary care educators should be cautious of the heightened challenges to academic integrity posed by AI is highlighted, as well as key areas for medical educators to support learners' early engagement with AI.
Abstract
INTRODUCTION Reflection, a cornerstone of professional development and a core component of medical education, is increasingly challenged by the emergence of generative artificial intelligence (AI). AI's capability to mimic human behaviour through real-time feedback, content generation, and conversational interfaces presents pressing ethical and pedagogical concerns regarding its use in reflection.
Aim
This qualitative study sought to explore the perspectives of educators on undergraduate medical students using AI in reflection.
Methods
Data were generated through two online focus groups with general practitioners in the role of expert participants, each lasting around one hour and including three participants. All six participants were academic undergraduate primary care educators who teach reflection skills to students.
Results
Five themes were conceptualised by reflexive thematic analysis: questioning assessment of reflection; professionalism in jeopardy; acceptability of using AI in learning; digital divide and educational equity; and institutional and educator readiness for AI. Educators faced complex tensions between embracing technological progress and protecting the relational and ethical foundations of medical education.
Discussion
Although there was cautious optimism about AI's role as a facilitative tool, participants uniformly emphasised that its educational value depends on critical, transparent, and ethically grounded implementation. This study highlights how undergraduate primary care educators should be cautious of the heightened challenges to academic integrity posed by AI. Uncertainty around fostering authentic student engagement in reflection suggests the need for further exploration in partnership with students. These findings highlight key areas for medical educators to support learners' early engagement with AI.
