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Computational Learning Theories : Models for Artificial Intelligence Promoting Learning Processes - David C. Gibson

Computational Learning Theories

Models for Artificial Intelligence Promoting Learning Processes

By: David C. Gibson, Dirk Ifenthaler

eText | 16 July 2024

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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.

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