AIMC Topic: Educational Measurement

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AI-Driven Objective Structured Clinical Examination Generation in Digital Health Education: Comparative Analysis of Three GPT-4o Configurations.

JMIR medical education
BACKGROUND: Objective Structured Clinical Examinations (OSCEs) are used as an evaluation method in medical education, but require significant pedagogical expertise and investment, especially in emerging fields like digital health. Large language mode...

Leading large language models on a periodontology knowledge test.

Swiss dental journal
Large language models (LLMs) are increasingly used in clinical and educational settings. However, there is a paucity of data on LLMs' performance in specialized dental domains. This study assessed the performance of four LLMs, including two general-p...

GPT-4o and OpenAI o1 Performance on the 2024 Spanish Competitive Medical Specialty Access Examination: Cross-Sectional Quantitative Evaluation Study.

JMIR medical education
BACKGROUND: In recent years, generative artificial intelligence and large language models (LLMs) have rapidly advanced, offering significant potential to transform medical education. Several studies have evaluated the performance of chatbots on multi...

Generating multiple-choice questions using reverse engineering techniques.

Medical education online
The study is aimed at exploring the potential of using ChatGPT-4 to develop multiple-choice questions that adhere to item development principles through the application of reverse engineering techniques in nursing education. To determine whether Chat...

Comparing AI-Assisted Problem-Solving Ability With Internet Search Engine and e-Books in Medical Students With Variable Prior Subject Knowledge: Cross-Sectional Study.

JMIR medical education
BACKGROUND: Artificial intelligence (AI), particularly large language models (LLMs) such as ChatGPT (OpenAI), is rapidly influencing medical education. Its effectiveness for students with varying levels of prior knowledge remains underexplored.

AI-generated biochemistry test item parameters in MST test conditions.

BMC medical education
BACKGROUND: This study investigated whether ChatGPT 4o could accurately estimate the difficulty of medical assessment items by comparing its predictions with empirically-derived parameters from multistage testing simulations.

Comparing ChatGPT and DeepSeek for Assessment of Multiple-Choice Questions in Orthopedic Medical Education: Cross-Sectional Study.

JMIR formative research
BACKGROUND: Multiple-choice questions (MCQs) are essential in medical education for assessing knowledge and clinical reasoning. Traditional MCQ development involves expert reviews and revisions, which can be time-consuming and subject to bias. Large ...

Performance of DeepSeek-R1, ChatGPT (GPT-o3-mini), and Gemini 2.0 Flash on German Medical Multiple-Choice Questions: Comparative Evaluation.

JMIR formative research
BACKGROUND: Despite the transformative potential of artificial intelligence (AI)-based chatbots in medicine, their implementation is hindered by data privacy and security concerns. DeepSeek offers a conceivable solution through its capability for loc...

Multiple Large Language Models' Performance on the Chinese Medical Licensing Examination: Quantitative Comparative Study.

JMIR human factors
BACKGROUND: ChatGPT excels in natural language tasks, but its performance in the Chinese National Medical Licensing Examination (NMLE) and Chinese medical education remains underexplored. Meanwhile, Chinese corpus-based large language models (LLMs) s...

Token-splitting improves GPT-4.1 performance on plastic surgery exams: implications for AI-Assisted medical education.

Medical education online
Large language models (LLMs), such as ChatGPT, have demonstrated impressive performance on general medical examinations; however, their effectiveness significantly declines in specialized board examinations due to limited domain-specific training dat...