ReviewBritish dental journal2026
AI-informed healthcare pedagogy: a review of the literature and application to pedagogical practice informed by case studies from dental education.
Review in British dental journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
1 author.
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Abstract
Artificial intelligence (AI) applications in healthcare continue to grow at a rapid pace. Healthcare education is struggling to effectively integrate the manifold applications and opportunities presented by AI to education. Concerns and fears around negative impacts on student learning and potential for misuse alongside a paucity of guidance has led to a sluggish response across much of healthcare education. This paper offers a short review of the applications of AI in healthcare including clinical dentistry and makes suggestions for bridging the gap between education and practice so that educators can better prepare students for their professional careers. This paper argues that open, reflective classroom discussions around ethical concerns and climate impacts of AI are as important as the positive clinical applications to endow students with the knowledge to make decisions that align with social justice and social accountability. Two widely used assessments in dental and wider healthcare education - reflective assessments and evidence-based practice projects - are explored as case studies to develop an updated, AI-informed approach to teaching. Drawing on pedagogical literature, the author offers suggestions for educators to support thoughtful and ethical integration of AI within a student's learning repertoire so that AI becomes supplementary to, and not a substitute for, learning.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.