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Abstract
This thesis explores the application of personalized and adaptive learning methodologies in the teaching of anatomy, aiming to enhance student learning outcomes by catering to individual learning needs. By integrating cutting-edge technologies such as AI-driven platforms and data analytics, personalized learning environments allow students to engage with complex anatomical content at their own pace. This study investigates the impact of adaptive learning systems on student comprehension, retention, and engagement in anatomy education. Through a series of surveys, performance analyses, and case studies, this research provides valuable insights into the effectiveness of personalized learning pathways in improving anatomical knowledge and fostering deeper understanding.
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