Computational Learning Theories
Models for Artificial Intelligence Promoting Learning Processes
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Beschreibung
This book shows how artificial intelligence grounded in learning theories can promote individual learning, team productivity and multidisciplinary knowledge-building. It advances the learning sciences by integrating learning theory with computational biology and complexity, offering an updated mechanism of learning, which integrates previous theories, provides a basis for scaling from individuals to societies, and unifies models of psychology, sociology and cultural studies.
The book provides a road map for the development of AI that addresses the central problems of learning theory in the age of artificial intelligence including:
- optimizing human-machine collaboration
- promoting individual learning
- balancing personalization with privacy
- dealing with biases and promoting fairness
- explaining decisions and recommendations to build trust and accountability
- continuously balancing and adapting to individual, team and organizational goals
- generating and generalizing knowledge across fields and domains
The book will be of interest to educational professionals, researchers, and developers of educational technology that utilize artificial intelligence.
This book shows how artificial intelligence grounded in learning theories can promote individual learning, team productivity and multidisciplinary knowledge-building. It advances the learning sciences by integrating learning theory with computational biology and complexity, offering an updated mechanism of learning, which integrates previous theories, provides a basis for scaling from individuals to societies, and unifies models of psychology, sociology and cultural studies.
The book provides a road map for the development of AI that addresses the central problems of learning theory in the age of artificial intelligence including:
- optimizing human-machine collaboration
- promoting individual learning
- balancing personalization with privacy
- dealing with biases and promoting fairness
- explaining decisions and recommendations to build trust and accountability
- continuously balancing and adapting to individual, team and organizational goals
- generating and generalizing knowledge across fields and domains
The book will be of interest to educational professionals, researchers, and developers of educational technology that utilize artificial intelligence.
Integrates learning and complexity theories Outlines AI roles for individual, team and organizational learning Provides advanced perspectives in learning theories related to advances in artificial intelligence
Autor*in
David C. Gibson
Themen in »Computational Learning Theories«
Artificial Intelligence Learning Theory Computational Learning Social Epistemology Knowledge Acquisition