This book explores the application of machine learning (ML) in outcome-based education (OBE) and its transformative potential to enhance learning effectiveness. It examines how ML can be seamlessly integrated into various dimensions of OBE to optimize assessment techniques, personalize curriculum design, and modernize teaching methodologies. Emphasizing practical implementation, the book highlights how ML enables personalized learning experiences, supports early intervention strategies, and promotes data-driven decision-making for continuous improvement. Serving as a valuable resource for educators, researchers, and policymakers, it provides actionable insights into leveraging the power of ML to drive innovation and improve educational outcomes.
This book explores the application of machine learning (ML) in outcome-based education (OBE) and its transformative potential to enhance learning effectiveness. It examines how ML can be seamlessly integrated into various dimensions of OBE to optimize assessment techniques, personalize curriculum design, and modernize teaching methodologies. Emphasizing practical implementation, the book highlights how ML enables personalized learning experiences, supports early intervention strategies, and promotes data-driven decision-making for continuous improvement. Serving as a valuable resource for educators, researchers, and policymakers, it provides actionable insights into leveraging the power of ML to drive innovation and improve educational outcomes.
D. Vetrithangam
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