Comparison of a generative large language model to pharmacy student performance on therapeutics examinations

ChatGPT scored lower than the average grade for pharmacy students and was less likely to answer application-based and case-based questions correctly. These findings provide valuable insight into how this technology will perform which can help to inform best practices for item development and helps highlight the limitations of this technology.

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Publication Details

Journal
Currents in Pharmacy Teaching and Learning
Published
2025-05-22
DOI
https://doi.org/10.1016/j.cptl.2025.102394
Citations
3
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
1.96
Controls
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article

Comparison of a generative large language model to pharmacy student performance on therapeutics examinations

Bernadette Cornelison, Brian L. Erstad, Christopher J. Edwards
3 citations
Currents in Pharmacy Teaching and Learning
Artificial Intelligence in Healthcare and Education
1.96
article

Comparison of a generative large language model to pharmacy student performance on therapeutics examinations

Bernadette Cornelison, Brian L. Erstad, Christopher J. Edwards
article en
3 citations

Abstract

ChatGPT scored lower than the average grade for pharmacy students and was less likely to answer application-based and case-based questions correctly. These findings provide valuable insight into how this technology will perform which can help to inform best practices for item development and helps highlight the limitations of this technology.

Currents in Pharmacy Teaching and LearningVol. 17(9)
University of Arizona (US)
Quality Education
Openalex Percentile: Top 12%
Artificial Intelligence in Healthcare and Education
1.96
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Comparison of a generative large language model to pharmacy student performance on therapeutics examinations — Bernadette Cornelison, Brian L. Erstad, et al. · Currents in Pharmacy Teaching and Learning (2025) | TGRS Research Map | TGRS