Metacognition through an Iterative Anatomy AI Chatbot: An Innovative Playing Field for Educating the Future Generation of Medical Students - Varna Taranikanti; Cameron J. Davidson (Anatomia, 2023)
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.