Evidence map›Paper›PMID 41688097›Full record

ArticleThe clinical teacher2026

AI in the Classroom: Observing Preclinical Students' Use of ChatGPT During Case-Based Learning at a UK Medical School.

A W R Taylor, F Y Patel, E K Smyth, S Gay, T Bird

Abstract read
In one paragraph

Article in The clinical teacher, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

A W R TaylorUniversity of Leicester, Leicester, UK.ORCID https://orcid.org/0000-0002-2397-0638
F Y PatelUniversity of Leicester, Leicester, UK.
E K SmythUniversity of Leicester, Leicester, UK.
S GayUniversity of Leicester, Leicester, UK.ORCID https://orcid.org/0000-0002-1743-9824
T BirdUniversity of Leicester, Leicester, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis article explores how preclinical students in a UK medical school utilise ChatGPT during their case-based learning (CBL) curriculum. MATERIALS AND

methodsFocused ethnography was used to study 42 medical students and three clinical sciences students as they undertook seven CBL sessions over 4 weeks. In situ observations, screenshots of ChatGPT conversations and focus group data were collected and analysed using reflexive thematic analysis.

resultsChatGPT was used to automate concept retrieval, problem-solving and applying theory to clinical context. This occurred because students were motivated by the efficient completion of workbook questions, which could be achieved by entering them into ChatGPT. Collaborative groups were less likely to automate cognitive effort because they placed greater value on being engaged during learning and perceived socially constructing answers as more efficient than ChatGPT use. Although ChatGPT sometimes gave partial or false-but-plausible answers, students were rarely observed cross-checking it.

conclusionsAI chatbot use during conventional curricular activities can result in students automating cognitive effort. This is more likely during tasks scaffolded by guiding materials and when students are motivated by external pressures rather than a desire for engaging learning. Educators should specify how and when AI chatbots should be used, promote autonomy and collaboration in student cultures and teach students about the value of cognitive effort to learning.

Indexed as

Education, Medical, UndergraduateProblem-Based LearningStudents, MedicalFocus GroupsGenerative Artificial IntelligenceHumansSchools, MedicalUnited Kingdomactive learningAI chatbotsartificial intelligence in educationcase‐based learningundergraduate medical education

Identifiers

PMID41688097
PMCPMC12904756

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.