Detecting Artificial Intelligence–Generated Versus Human-Written Medical Student Essays: Semirandomized Controlled Study

The findings suggest that both medical and humanities experts were able to identify ChatGPT-generated texts in medical contexts, with their decisions largely based on linguistic attributes. The accuracy of identification appears to be independent of experts' familiarity with the text content. As the decision-making process primarily relies on linguistic attributes-such as stylistic features and text coherence-further quasi-experimental studies using texts from other academic disciplines should be conducted to determine whether instructions based on these features can enhance lecturers' ability to distinguish between student-authored and AI-generated work.

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Publication Details

Journal
JMIR Medical Education
Published
2025-01-16
DOI
https://doi.org/10.2196/62779
Citations
13
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
8.51
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article

Detecting Artificial Intelligence–Generated Versus Human-Written Medical Student Essays: Semirandomized Controlled Study

Maria Berger, Thomas Luecke, Elena Enax‐Krumova, Marianne Tokic et al.
13 citations
JMIR Medical Education
Artificial Intelligence in Healthcare and Education
8.51
article

Detecting Artificial Intelligence–Generated Versus Human-Written Medical Student Essays: Semirandomized Controlled Study

Maria Berger, Thomas Luecke, Elena Enax‐Krumova, Marianne Tokic, Berin Doru, Judith Schönhoff, Christoph Maier, Johanna Sophie Busse, Steffen Hessler
article en
13 citations

Abstract

The findings suggest that both medical and humanities experts were able to identify ChatGPT-generated texts in medical contexts, with their decisions largely based on linguistic attributes. The accuracy of identification appears to be independent of experts' familiarity with the text content. As the decision-making process primarily relies on linguistic attributes-such as stylistic features and text coherence-further quasi-experimental studies using texts from other academic disciplines should be conducted to determine whether instructions based on these features can enhance lecturers' ability to distinguish between student-authored and AI-generated work.

JMIR Medical EducationVol. 11
University Hospitals of the Ruhr-University of Bochum (DE), Institute for Prevention and Occupational Medicine (DE), St. Josef-Hospital (DE), BG University Hospital Bergmannsheil Bochum (DE), Ruhr University Bochum (DE)
Quality Education
Openalex Percentile: Top 3%
Artificial Intelligence in Healthcare and Education
8.51
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Detecting Artificial Intelligence–Generated Versus Human-Written Medical Student Essays: Semirandomized Controlled Study — Maria Berger, Thomas Luecke, et al. · JMIR Medical Education (2025) | TGRS Research Map | TGRS