ArticleEmerging topics in life sciences2025
Clinical assessment meets laboratory science: adapting OSCE methodology for authentic biosciences evaluation in the age of generative AI.
Article in Emerging topics in life sciences, 2025. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The proliferation of generative artificial intelligence (AI) tools has fundamentally challenged traditional written assessments across higher education, with particular implications for laboratory-based disciplines where written work may substitute for demonstration of practical competence, necessitating approaches that prioritise direct performance. This study presents the adaptation of objective structured clinical examination (OSCE) methodology from medical education to laboratory biosciences, demonstrating a practical framework for authentic assessment in the AI era. We describe and evaluate the transformation of a microscopy assessment in FHEQ Level 4 Biomedical Sciences from a traditional laboratory report to a 20-minute OSCE-style practical evaluation. The redesigned assessment maintained grade distributions while eliminating AI vulnerability through real-time performance demonstration and conversational examination. The implementation achieved close alignment between learning outcomes and assessment methods while providing inherent resistance to generative AI exploitation through direct performance requirements. Equity implications are complex and context-dependent, with potential barriers for students with communication differences alongside potential benefits for others, such as those with written communication difficulties, emphasising the importance of balanced assessment portfolios and appropriate reasonable adjustments. The cross-disciplinary adaptation demonstrates that OSCE methodology offers a scalable solution to AI-era assessment challenges, with performance-focused design maintaining academic integrity more effectively than restrictive policies while enhancing authenticity and equity outcomes.
Indexed as
Identifiers
What OpenQuestion holds
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.