Evidence map›Paper›PMID 39973890›Full record

ReviewBritish journal of biomedical science2024

Education and Training Assessment and Artificial Intelligence. A Pragmatic Guide for Educators.

Philip M Newton, Sue Jones

Abstract readReview
In one paragraph

Review in British journal of biomedical science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
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

2 authors.

Philip M NewtonSwansea University Medical School, Swansea University, Swansea, United Kingdom.
Sue JonesInstitute of Biomedical Science, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emergence of ChatGPT and similar new Generative AI tools has created concern about the validity of many current assessment methods in higher education, since learners might use these tools to complete those assessments. Here we review the current evidence on this issue and show that for assessments like essays and multiple-choice exams, these concerns are legitimate: ChatGPT can complete them to a very high standard, quickly and cheaply. We consider how to assess learning in alternative ways, and the importance of retaining assessments of foundational core knowledge. This evidence is considered from the perspective of current professional regulations covering the professional registration of Biomedical Scientists and their Health and Care Professions Council (HCPC) approved education providers, although it should be broadly relevant across higher education.

Indexed as

Artificial IntelligenceEducational MeasurementHumansLearningacademic integrityassessment practicescheatinggenerative artificial intelligence (GenAI)professional regulation

Identifiers

PMID39973890
PMCPMC11837776

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.