AIMC Topic: Educational Measurement

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Is AI the future of evaluation in medical education?? AI vs. human evaluation in objective structured clinical examination.

BMC medical education
BACKGROUND: Objective Structured Clinical Examinations (OSCEs) are widely used in medical education to assess students' clinical and professional skills. Recent advancements in artificial intelligence (AI) offer opportunities to complement human eval...

A Comparative Bicentric Study on Ultrasound Education for Students: App- and AI-Supported Learning Versus Traditional Hands-on Instruction (AI-Teach Study).

Academic radiology
BACKGROUND: The integration of artificial intelligence (AI) into medical education presents significant opportunities for enhancing teaching methods and student learning outcomes. Despite its potential benefits, the implementation of AI in curricula ...

Navigating the frontier of AI-assisted student assignments: challenges, skills, and solutions.

Advances in physiology education
The rise of artificial intelligence (AI) is transforming educational practices, particularly in assessment. While AI may support the students in idea generation and summarization of source materials, it also introduces challenges related to content v...

AI-generated questions for urological competency assessment: a prospective educational study.

BMC medical education
BACKGROUND: The integration of artificial intelligence (AI) in medical education assessment remains largely unexplored, particularly in specialty-specific evaluations during clinical rotations. Traditional question development methods are time-intens...

The role of artificial intelligence in medical education: an evaluation of Large Language Models (LLMs) on the Turkish Medical Specialty Training Entrance Exam.

BMC medical education
OBJECTIVE: To evaluate the performance of advanced large language models (LLMs)-OpenAI-ChatGPT 4, Google AI-Gemini 1.5 Pro, Cohere-Command R + and Meta AI-Llama 3 70B on questions from the Turkish Medical Specialty Training Entrance Exam (2021, 1st s...

Evaluating the performance of GPT-3.5, GPT-4, and GPT-4o in the Chinese National Medical Licensing Examination.

Scientific reports
This study aims to compare and evaluate the performance of GPT-3.5, GPT-4, and GPT-4o in the 2020 and 2021 Chinese National Medical Licensing Examination (NMLE), exploring their potential value in medical education and clinical applications. Six hund...

Randomized Controlled Study on the Impact of Problem-Based Learning Combined With Large Language Models on Critical Thinking Skills in Nursing Students.

Nurse educator
BACKGROUND: The integration of Large Language Models (LLMs) into nursing education presents a novel approach to enhancing critical thinking skills. This study evaluated the effectiveness of LLM-assisted Problem-Based Learning (PBL) compared to tradit...

Artificial intelligence performance in answering multiple-choice oral pathology questions: a comparative analysis.

BMC oral health
BACKGROUND: Artificial intelligence (AI) has rapidly advanced in healthcare and dental education, significantly impacting diagnostic processes, treatment planning, and academic training. The aim of this study is to evaluate the performance difference...

Assessing ChatGPT 4.0's Capabilities in the United Kingdom Medical Licensing Examination (UKMLA): A Robust Categorical Analysis.

Scientific reports
Advances in the various applications of artificial intelligence will have important implications for medical training and practice. The advances in ChatGPT-4 alongside the introduction of the medical licensing assessment (MLA) provide an opportunity ...

Large Language Models in Biochemistry Education: Comparative Evaluation of Performance.

JMIR medical education
BACKGROUND: Recent advancements in artificial intelligence (AI), particularly in large language models (LLMs), have started a new era of innovation across various fields, with medicine at the forefront of this technological revolution. Many studies i...