AIMC Topic: Educational Measurement

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The pitfalls of multiple-choice questions in generative AI and medical education.

Scientific reports
The performance of Large Language Models (LLMs) on multiple-choice question (MCQ) benchmarks is frequently cited as proof of their medical capabilities. We hypothesized that LLM performance on medical MCQs may in part be illusory and driven by factor...

Evaluating ChatGPT-4o as an Educational Support Tool for the Emergency Management of Dental Trauma: Randomized Controlled Study Among Students.

JMIR medical education
BACKGROUND: Digital tools are increasingly used to support clinical decision-making in dental education. However, the accuracy and efficiency of different support tools, including generative artificial intelligence, in the context of dental trauma ma...

Teaching Clinical Reasoning in Health Care Professions Learners Using AI-Generated Script Concordance Tests: Mixed Methods Formative Evaluation.

JMIR formative research
BACKGROUND: The integration of artificial intelligence (AI) in medical education is evolving, offering new tools to enhance teaching and assessment. Among these, script concordance tests (SCTs) are well-suited to evaluate clinical reasoning in contex...

Comparative performance of large language models in answering periodontology questions from the Turkish Dental Specialty Examination: a cross-sectional study on accuracy and coverage.

BMC oral health
BACKGROUND: In recent years, several studies have explored the use of large language models (LLMs) such as ChatGPT-4, Claude, Gemini Advanced, and DeepSeek-R1 in dental education. Nevertheless, no study has yet reported a comparative evaluation of mu...

Using machine learning to predict student outcomes for early intervention and formative assessment.

Scientific reports
The increasing importance of early prediction of student performance has led to research into machine learning models that can be used to assess student outcomes more accurately.This study focused on developing a predictive model based on machine lea...

Artificial intelligence-based chatbots improve the efficiency of course orientation among medical students: a cross-sectional study.

BMC medical education
BACKGROUND: Large language models (LLMs) like ChatGPT offer new ways to improve academic and administrative workflows in medical education, particularly for students studying in a language that is not their native tongue. We set out to examine whethe...

Performance of the Large Language Models on the Chinese National Nurse Licensure Examination: Cross-Sectional Evaluation Study.

JMIR medical informatics
BACKGROUND: Large language models (LLMs) are increasingly explored in nursing education, but their capabilities in specialized, high-stakes, culturally specific examinations, such as the Chinese National Nurse Licensure Examination (CNNLE), remain un...

Performance of AI Chatbots on Head and Neck Pathology Board-Style Exam Questions and Guidelines for Responsible Use.

Head and neck pathology
The promising integration of artificial intelligence (AI), particularly large language models (LLMs) or AI chatbots, into medical education and practice necessitates rigorous evaluation of their capabilities. While chatbot performance has been assess...

Large language models as educational collaborators: developing non-conventional teaching aids in pharmacology & therapeutics.

BMC medical education
BACKGROUND: With the growing integration of artificial intelligence in medical education, this study compares the quality and educational robustness of content generated by two large language models (LLMs), DeepSeek-V3 and ChatGPT 4.0, on the emergin...