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Advances in conversational artificial intelligence agents in medical education: Prospects and challenges

artificial-intelligence
natural-language-and-speech

Abstract

With the rapid advancement of artificial intelligence technology, conversational artificial intelligence agents (CAA) have found increasing applications across various domains, particularly demonstrating significant potential and value in medical education. CAA not only provides real-time learning support for medical education but also offers personalized teaching experiences tailored to the individual needs of students, thereby enhancing learning outcomes. Furthermore, CAA exhibits high efficiency in resource utilization, which can alleviate the workload of educators and improve the quality of education. However, several challenges remain in terms of chatbot functionalities, advantages, and limitations, including issues related to accuracy, user experience, and evaluation of educational outcomes. This paper aims to thoroughly explore the developmental trajectory and current applications of CAA in medical education, analyze their performance in practical teaching scenarios, and discuss future directions based on the latest research findings. The study seeks to provide valuable insights and recommendations for innovation in medical education.
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