Metacognition through an Iterative Anatomy AI Chatbot: An Innovative Playing Field for Educating the Future Generation of Medical Students

Anatomia Pub Date : 2023-09-06 DOI:10.3390/anatomia2030025
Varna Taranikanti, Cameron J. Davidson
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引用次数: 1

Abstract

Medical educators face many challenges instructing future medical students, specifically in the integration of learning technologies. To overcome these challenges, educators must implement learner-centered and interactive teaching strategies. Anatomical sciences are the cornerstone of medical education and provide the bedrock to layer conceptual understanding of the human body. With the “medical knowledge boom”, most medical schools have reduced the curricular time for anatomy instruction, resulting in a paucity of knowledge and issues incorporating anatomical knowledge in clinical scenarios. Modern pedagogical techniques combining AI chatbots with concurrent metacognitive frameworks can foster a deeper understanding of anatomical knowledge and analysis of clinical cases. Student reflection on the learning process allows for monitoring their progress and tailoring of learning strategies to their specific capabilities and needs. A.I. technology can aid in scaffolding knowledge with practical applications via iterative and immediate feedback in case- or problem-based learning formats. The use of textual conversations actively engages students and simulates conversations with instructors. In this communication, we advocate for the incorporation of AI technologies fused with a metacognitive framework as a medium to foster increased critical thinking and skill development that enhances comprehension. These skills are important for medical students’ lifelong learning process.
通过迭代解剖人工智能聊天机器人的元认知:教育下一代医学生的创新竞争环境
医学教育工作者在指导未来的医学生时面临许多挑战,特别是在整合学习技术方面。为了克服这些挑战,教育者必须实施以学习者为中心的互动教学策略。解剖科学是医学教育的基石,为对人体的层层概念理解提供了基础。随着“医学知识热潮”的兴起,大多数医学院都减少了解剖学教学的课程时间,导致解剖学知识的匮乏和解剖学知识在临床场景中的应用问题。将人工智能聊天机器人与并发元认知框架相结合的现代教学技术可以促进对解剖学知识的更深入理解和临床病例的分析。学生对学习过程的反思可以监控他们的进步,并根据他们的具体能力和需求定制学习策略。人工智能技术可以通过案例或问题为基础的学习格式,通过迭代和即时反馈,在实际应用中帮助构建知识。文本对话的使用积极地吸引学生,并模拟与教师的对话。在本文中,我们提倡将人工智能技术与元认知框架相结合,作为培养批判性思维和技能发展的媒介,以增强理解能力。这些技能对医学生的终身学习过程非常重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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