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TRV-2026-0325Certified recordPeer-reviewed

Mapping artificial intelligence integration in objective structured clinical examinations: A scoping review

INTRODUCTION: Objective Structured Clinical Examinations (OSCEs) are widely used to assess clinical competence, but face challenges related to examiner workload, scoring variability, delayed feedback, and resource demands. Although AI may address these constraints and support precision medical education, the evidence remains fragmented. This scoping review maps AI applications in OSCEs. METHODS: We followed PRISMA-ScR. We searched MEDLINE, Scopus, Embase, Web of Science, ERIC, LILACS, and IEEE Xplore from incept…

Health · The Trace — both readings · certified 2026-07-20 · v1 · article view · machine-readable

Current reading — gain

In health professions OSCEs, AI applications improved grading efficiency, feedback speed, and consistency for structured observable tasks, with personalization as the dominant P4 precision education alignment observed by June 2025.

Current reading — problem

As of the June 2025 search cutoff, evidence did not support claims that AI delivers precision medical education through OSCEs, with weaker performance in relational, situated, and culturally mediated competencies.

What this doesn’t fix

Evidence base was small and fragmented with only 22 included studies from 421 screened, and P4 precision education alignment was partial and conditional, with weaker performance in relational competencies.

Evidence

Reader signal

How should this claim be treated?

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Truvace Impact Record TRV-2026-0325, v1: “Mapping artificial intelligence integration in objective structured clinical examinations: A scoping review.” Truvace, 2026-07-20. /record/TRV-2026-0325 (accessed at citation time). sha256 dabe11ce765a5586…

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