Title |
Computational Learning Theories : Models for Artificial Intelligence Promoting Learning Processes / by David C. Gibson, Dirk Ifenthaler |
|---|---|
Involved |
David Gibson (Verfasser) |
Published |
Cham: Springer Nature Switzerland, Imprint: Springer |
Edition |
1st ed. 2024 |
Extent |
Online-Ressource, XIII, 154 p. 20 illus. : online resource. |
Contains |
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 |
ISBN |
978-3-031-65898-3 |
Language |
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Country |
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Topic |
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Subject |
Research Methods in Education. |
DDC notation |
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Series |
Advances in Analytics for Learning and Teaching |
Persistent identifier |
urn:nbn:de:101:1-2408151636370.138841240912 (URN) |
Record ID |
1339110989 |
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