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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Medical students' perceptions of AI-generated practice questions as learning tools.

Hudson Tate1, Brenton T Bicknell1, Paul Fiore1

  • 1Marnix E. Heersink School of Medicine, University of Alabama at Birmingham, AL, USA.

Journal of Investigative Medicine : the Official Publication of the American Federation for Clinical Research
|December 2, 2025
PubMed
Summary
This summary is machine-generated.

Generative artificial intelligence (AI) tools can enhance medical education. AI-generated practice questions were well-received by medical students, with upperclassmen performing better, suggesting AI

Keywords:
ChatGPTartificial intelligenceeducational technologyformative assessmentlearning toolsmedical education

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Area of Science:

  • Medical Education
  • Artificial Intelligence in Education
  • Health Professions Education

Background:

  • Generative artificial intelligence (AI) tools, including large language models (LLMs), show promise for enhancing student learning in medical education.
  • Formative assessment is crucial for medical student development, and AI offers novel approaches to creating practice materials.
  • The United States Medical Licensing Examination (USMLE) style practice questions are a standard tool for assessing medical knowledge.

Purpose of the Study:

  • To evaluate the perceived utility of AI-generated, USMLE-style practice questions as a formative learning tool for preclinical medical students.
  • To assess the performance outcomes of medical students using AI-generated multiple-choice questions (MCQs).
  • To explore differences in performance and perception based on student year and feedback.

Main Methods:

  • ChatGPT 4.0 was used to generate MCQs for 15 microbiology and endocrinology lectures.
  • A total of 386 preclinical medical students (198 first-year (MS1) and 188 second-year (MS2)) participated.
  • 490 AI-generated question sets were completed optionally, with student feedback collected on 94.9% of sets.

Main Results:

  • The majority of students found the AI-generated questions helpful (82.8%) or somewhat helpful (16.1%).
  • Second-year medical students (MS2) achieved significantly higher correct answer rates (84.4%) compared to first-year students (MS1) (78.6%).
  • No significant difference in average scores was found based on student feedback or rating of the questions.

Conclusions:

  • AI-generated MCQs are broadly accepted by medical students as valuable supplemental formative learning tools.
  • Performance on AI-generated questions varied between student cohorts and lecture topics, indicating potential areas for targeted learning.
  • Further research is warranted to explore the broader feasibility and impact of AI tools in medical education.