Using artificial intelligence to provide a ‘flipped assessment’ approach to medical education learning opportunities

While increased confidence is positive, rigorous evaluation of AI-generated question quality is needed to confirm accuracy. Teaching students to use generative AI to create and critique practice questions represents a means of encouraging appropriate AI use.

Authors

Institutions

Publication Details

Journal
Medical Teacher
Published
2024-12-01
DOI
https://doi.org/10.1080/0142159x.2024.2434101
Citations
10
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
1.20
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Using artificial intelligence to provide a ‘flipped assessment’ approach to medical education learning opportunities

James Gray, Claire Darling-Pomranz, Samuel Birks
10 citations
Medical Teacher
Artificial Intelligence in Healthcare and Education
1.20
article

Using artificial intelligence to provide a ‘flipped assessment’ approach to medical education learning opportunities

James Gray, Claire Darling-Pomranz, Samuel Birks
article en
10 citations

Abstract

While increased confidence is positive, rigorous evaluation of AI-generated question quality is needed to confirm accuracy. Teaching students to use generative AI to create and critique practice questions represents a means of encouraging appropriate AI use.

Medical TeacherVol. 47(8)
University of Sheffield (GB)
Quality Education
Openalex Percentile: Top 19%
Artificial Intelligence in Healthcare and Education
1.20
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.