利用人工智能的循证医学学习策略。

IF 3.2 Q1 EDUCATION, SCIENTIFIC DISCIPLINES
Juan Pablo Arango-Ibanez, Jose Alejandro Posso-Nuñez, Juan Pablo Díaz-Solórzano, Gustavo Cruz-Suárez
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引用次数: 0

摘要

无标签:大型语言模型(LLM),如 ChatGPT,正在改变医学教育的面貌。它们提供了广泛的应用,如辅导(个性化学习)、病人模拟、生成考题和简化信息访问。医学知识的飞速发展和个性化学习的需求凸显了探索将人工智能(AI)融入医学教育的创新策略的现实意义和及时性。在本文中,我们建议将基于证据的学习策略(如主动回忆和记忆线索)与人工智能相结合,以优化学习。这些策略包括生成测试、记忆法和视觉提示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evidence-Based Learning Strategies in Medicine Using AI.

Unlabelled: Large language models (LLMs), like ChatGPT, are transforming the landscape of medical education. They offer a vast range of applications, such as tutoring (personalized learning), patient simulation, generation of examination questions, and streamlined access to information. The rapid advancement of medical knowledge and the need for personalized learning underscore the relevance and timeliness of exploring innovative strategies for integrating artificial intelligence (AI) into medical education. In this paper, we propose coupling evidence-based learning strategies, such as active recall and memory cues, with AI to optimize learning. These strategies include the generation of tests, mnemonics, and visual cues.

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来源期刊
JMIR Medical Education
JMIR Medical Education Social Sciences-Education
CiteScore
6.90
自引率
5.60%
发文量
54
审稿时长
8 weeks
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