AIMC Topic: Education, Medical, Undergraduate
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Which curriculum components do medical students find most helpful for evaluating AI outputs?
BMC medical education
Feb 6, 2025
INTRODUCTION: The risk and opportunity of Large Language Models (LLMs) in medical education both rest in their imitation of human communication. Future doctors working with generative artificial intelligence (AI) need to judge the value of any output...
Empowering medical students with AI writing co-pilots: design and validation of AI self-assessment toolkit.
BMC medical education
Jan 31, 2025
BACKGROUND AND OBJECTIVES: Assessing and improving academic writing skills is a crucial component of higher education. To support students in this endeavor, a comprehensive self-assessment toolkit was developed to provide personalized feedback and gu...
Design strategies for artificial intelligence based future learning centers in medical universities.
BMC medical education
Jan 31, 2025
BACKGROUND: This study explores the acceptance of artificial intelligence(AI) tools in medical students and its influencing factors, thus providing theoretical basis and practical guidance for the construction of future learning centers in medical un...
Assessing the disconnect between student interest and education in artificial intelligence in medicine in Saudi Arabia.
BMC medical education
Jan 30, 2025
BACKGROUND: Although artificial intelligence (AI) has gained increasing attention for its potential future impact on clinical practice, medical education has struggled to stay ahead of the developing technology. The question of whether medical educat...
Claude, ChatGPT, Copilot, and Gemini performance versus students in different topics of neuroscience.
Advances in physiology education
Jan 17, 2025
Despite extensive studies on large language models and their capability to respond to questions from various licensed exams, there has been limited focus on employing chatbots for specific subjects within the medical curriculum, specifically medical ...
Medical students' attitudes toward AI in education: perception, effectiveness, and its credibility.
BMC medical education
Jan 17, 2025
BACKGROUND: The rapid advancement of artificial intelligence (AI) has revolutionized both medical education and healthcare by delivering innovative tools that enhance learning and improve overall outcomes. The study aimed to assess students' percepti...
Effect of feedback-integrated reflection, on deep learning of undergraduate medical students in a clinical setting.
BMC medical education
Jan 14, 2025
BACKGROUND: Reflection fosters self-regulated learning by enabling learners to critically evaluate their performance, identify gaps, and make plans to improve. Feedback, in turn, provides external insights that complement reflection, helping learners...
Awareness and Attitude Toward Artificial Intelligence Among Medical Students and Pathology Trainees: Survey Study.
JMIR medical education
Jan 10, 2025
BACKGROUND: Artificial intelligence (AI) is set to shape the future of medical practice. The perspective and understanding of medical students are critical for guiding the development of educational curricula and training.
Enhancing Medical Student Engagement Through Cinematic Clinical Narratives: Multimodal Generative AI-Based Mixed Methods Study.
JMIR medical education
Jan 6, 2025
BACKGROUND: Medical students often struggle to engage with and retain complex pharmacology topics during their preclinical education. Traditional teaching methods can lead to passive learning and poor long-term retention of critical concepts.
Food for thought: a qualitative assessment of medical trainee and faculty perceptions of nutrition education.
BMC medical education
Dec 30, 2024
BACKGROUND: The American Society of Clinical Nutrition recommends 37 to 44 h of undergraduate medical nutrition education. The Total Health Curriculum at Geisinger Commonwealth School of Medicine (GCSOM) contains 14 h of objective-based nutritional i...
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