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商品詳細
Computational Learning Theories: Models for Artificial Intelligence Promoting Learning Processes.
・ISBN 978-3-031-65900-3 paper EUR 149.99
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| 著者・編者 | Gibson, David C. / Ifenthaler, Dirk, |
|---|---|
| シリーズ | (Advances in Analytics for Learning and Teaching) |
| 出版社 | (Springer International Publishing AG, SZ) |
| 出版年月 | 2025 |
| ページ数 | 154 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A04-84663＞ |
解説
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.