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"Learning theory" as a book category covers the conceptual and mathematical foundations of how learning occurs—whether in humans, animals, or machines—and the principles used to model, analyze, and improve learning processes. Titles in this category range from theoretical treatments of cognitive and educational psychology (covering behaviorist, constructivist, and connectionist accounts; memory, transfer, and instructional design) to formal accounts in machine learning and statistical/computational learning theory (PAC learning, generalization bounds, algorithms, and proofs). Works may be textbooks, surveys, or research monographs and typically combine theory, empirical evidence, and practical implications for teaching, curriculum design, AI system design, or neuroscience. Readers are usually advanced students, researchers, and practitioners who want rigorous explanations of why learning works, how to measure and guarantee performance, and how to design systems or interventions that facilitate effective learning.

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