This book explores the measurement of learning effectiveness and the optimization of knowledge retention by modeling the learning process and building the mathematical foundation of multi-space learning theory.
This book explores the measurement of learning effectiveness and the optimization of knowledge retention by modeling the learning process and building the mathematical foundation of multi-space learning theory.
Tai Wang is a professor affiliated with the Faculty of Artificial Intelligence in Education at the Central China Normal University, China. His research interests include educational technologies, internet psychology, and natural language processing. One major topic of his research is learning environment constructions. Mengsiying Li is a PhD candidate at the National Engineering Research Center for E-Learning, Central China Normal University, China, whose research focuses on learning spaces, strategies, and behavior.
Inhaltsangabe
1. Introduction on Multi-Space Learning 2. Partition Spaces to Optimize Learning Effectiveness 3. Matroid Theory 4. Current Foundations of Learning Sciences 5. Applications in Vocabulary Learning 6. Applications in Math Learning 7. Summary
1. Introduction on Multi-Space Learning 2. Partition Spaces to Optimize Learning Effectiveness 3. Matroid Theory 4. Current Foundations of Learning Sciences 5. Applications in Vocabulary Learning 6. Applications in Math Learning 7. Summary
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