BACKGROUND: To analyze medical students' perceptions, trust, and attitudes toward artificial intelligence (AI) in medical education, and explore their willingness to integrate AI in learning and teaching practices.
BACKGROUND: With the integration of Artificial Intelligence (AI) into educational systems, its potential to revolutionize learning, particularly in content personalization and assessment support, is significant. Personalized learning, supported by AI...
BACKGROUND: Standardized patients (SPs) prepare medical students for difficult conversations with patients. Despite their value, SP-based simulation training is constrained by available resources and competing clinical demands. Researchers are turnin...
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...
INTRODUCTION: Feedback is at the core of competency-based medical education. Learner perceptions of the evaluation process influence how feedback is utilized. Systems emphasize a fixed mindset, prioritizing evaluation over growth. Embracing growth mi...
BACKGROUND: As artificial intelligence (AI) becomes increasingly integral to healthcare, preparing medical and health sciences students to engage with AI technologies is critical.
Freely accessible generative artificial intelligence (GenAI) poses challenges to physiology education regarding learning and academic integrity. Although many studies have explored the capabilities of GenAI to complete assessments, few have implement...
INTRODUCTION: Artificial intelligence (AI) platforms have achieved a noteworthy role in various fields of medical sciences, ranging from medical education to clinical diagnostics and treatment. ChatGPT, Gemini, and Meta AI are some large language mod...
BACKGROUND: To investigate the perspectives and expectations of faculty radiologists, residents, and medical students regarding the integration of artificial intelligence (AI) in radiology education, a survey was conducted to collect their opinions a...
BACKGROUND: Pre-clerkship medical students benefit from practice questions that provide rationales for answer choices. Creating these rationales is a time-intensive endeavor. Therefore, not all practice multiple choice questions (MCQ) have correspond...
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