Evidence map›Paper›PMID 42137401›Full record

ArticleJournal of medical education and curricular development

The Hidden Preceptor: How AI Is Already Teaching Our Learners.

Samita M Heslin

Abstract read
In one paragraph

Article in Journal of medical education and curricular development. 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

1 author.

Samita M HeslinDepartment of Emergency Medicine & Biomedical Informatics, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, USA.ORCID https://orcid.org/0000-0001-8054-3387

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While Artificial Intelligence (AI) is being used increasingly by medical learners for studying and clinical decision-making, the educational impact of AI remains an opportunity for further discussion. This commentary introduces the concept of AI as a "hidden preceptor" that influences medical learners' approach to clinical reasoning, uncertainty, and professional identity. It draws on the concepts of hidden curriculum and clinical reasoning theory. The commentary argues that typically, AI demonstrates characteristics of speed, certainty, and pattern recognition, which can be counterproductive to the educationally desired outcomes of deliberate thinking, mechanical understanding, and reflective practice. Strategies are proposed to assist educators in making AI's pedagogy an explicit part of the educational process, and to enable learners to effectively engage with AI to promote, rather than hinder, their clinical growth and development.

Indexed as

artificial intelligenceclinical reasoninghidden curriculummedical educationprofessional identity formation

Identifiers

PMID42137401
PMCPMC13167320

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.