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Computational learning theories = mo...
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Gibson, David C.
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Computational learning theories = models for artificial intelligence promoting learning processes /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Computational learning theories/ by David C. Gibson, Dirk Ifenthaler.
其他題名:
models for artificial intelligence promoting learning processes /
作者:
Gibson, David C.
其他作者:
Ifenthaler, Dirk.
出版者:
Cham :Springer Nature Switzerland : : 2024.,
面頁冊數:
xiii, 154 p. :ill., digital ;24 cm.
內容註:
1. Why 'Computational' Learning Theories? -- 2. AI and Learning Processes -- 3. A Complex Hierarchical Framework of Learning -- 4. Piaget and the Ontogeny of Intelligence -- 5. Keller and the ARCS Model of Motivation -- 6. Complexity Theory and Learning -- 7. AI Roles for Enhancing Individual Learning -- 8. Informal Social Learning -- 9. How People Learn -- 10. AI Assisting Individuals as Team Members -- 11. AI Roles for the Team or Organization -- 12. A Network Theory of Culture -- 13. AI Roles in Cultural Learning -- 14. Open Questions.
Contained By:
Springer Nature eBook
標題:
Artificial intelligence - Educational applications. -
電子資源:
https://doi.org/10.1007/978-3-031-65898-3
ISBN:
9783031658983
Computational learning theories = models for artificial intelligence promoting learning processes /
Gibson, David C.
Computational learning theories
models for artificial intelligence promoting learning processes /[electronic resource] :by David C. Gibson, Dirk Ifenthaler. - Cham :Springer Nature Switzerland :2024. - xiii, 154 p. :ill., digital ;24 cm. - Advances in analytics for learning and teaching,2662-2130. - Advances in analytics for learning and teaching..
1. Why 'Computational' Learning Theories? -- 2. AI and Learning Processes -- 3. A Complex Hierarchical Framework of Learning -- 4. Piaget and the Ontogeny of Intelligence -- 5. Keller and the ARCS Model of Motivation -- 6. Complexity Theory and Learning -- 7. AI Roles for Enhancing Individual Learning -- 8. Informal Social Learning -- 9. How People Learn -- 10. AI Assisting Individuals as Team Members -- 11. AI Roles for the Team or Organization -- 12. A Network Theory of Culture -- 13. AI Roles in Cultural Learning -- 14. Open Questions.
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.
ISBN: 9783031658983
Standard No.: 10.1007/978-3-031-65898-3doiSubjects--Topical Terms:
567577
Artificial intelligence
--Educational applications.
LC Class. No.: LB1028.43
Dewey Class. No.: 371.33463
Computational learning theories = models for artificial intelligence promoting learning processes /
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1. Why 'Computational' Learning Theories? -- 2. AI and Learning Processes -- 3. A Complex Hierarchical Framework of Learning -- 4. Piaget and the Ontogeny of Intelligence -- 5. Keller and the ARCS Model of Motivation -- 6. Complexity Theory and Learning -- 7. AI Roles for Enhancing Individual Learning -- 8. Informal Social Learning -- 9. How People Learn -- 10. AI Assisting Individuals as Team Members -- 11. AI Roles for the Team or Organization -- 12. A Network Theory of Culture -- 13. AI Roles in Cultural Learning -- 14. Open Questions.
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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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