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...
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...
BACKGROUND: As medical education evolves, current teaching practices often remain misaligned with how today's digitally native students prefer to learn. While the use of digital tools is widespread, there is limited clarity on students' learning beha...
OBJECTIVE: To evaluate the feasibility and educational value of employing large language models (LLMs) to generate clinical case scenario with multiple-choice questions (MCQs) for undergraduate medical education.
BACKGROUND: Effective communication is fundamental to high-quality health care delivery, influencing patient satisfaction, adherence to treatment plans, and clinical outcomes. However, communication skills training for medical undergraduates often fa...
BACKGROUND: Improving the quality of education in clinical settings requires an understanding of learners' experiences and learning processes. However, this is a significant burden on learners and educators. If learners' learning records could be aut...
BACKGROUND: Artificial intelligence (AI) has revolutionized medical education by delivering tools that enhance and optimize learning. However, there is limited research on the medical students' perceptions regarding the effectiveness of AI as a learn...
BACKGROUND: At the beginning of their clinical clerkships (CCs), medical students face multiple challenges related to acquiring clinical and communication skills, building professional relationships, and managing psychological stress. While mentoring...
BACKGROUND: Medical biochemistry, a fundamental course in medical education, has a complex and expanding knowledge base. Traditional teaching methods often fail to meet students' needs for in-depth understanding and personalized learning. Students ca...
BACKGROUND: Optimizing the skill of answering Short answer questions (SAQ) in medical undergraduates with personalized feedback is challenging. With the increasing number of students and staff shortages this task is becoming practically difficult. He...
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