A new monograph focussing on models for artificial intelligence promoting learning processes was published.<\/p>\n\n\n\n
Gibson, D. C., & Ifenthaler, D. (2024). Computational learning theories. Models for artificial intelligence promoting learning processes. Springer. https:\/\/doi.org\/10.1007\/978-3-031-65898-3<\/strong><\/p>\n\n\n\n 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. It offers an updated mechanism of learning that integrates previous theories, provides a basis for scaling from individuals to societies, and unifies models of psychology, sociology, and cultural studies.<\/p>\n\n\n\n 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:<\/p>\n\n\n\n The book will be of interest to educational professionals, researchers, and developers of educational technology that utilize artificial intelligence.<\/p>\n\n\n\n\n