| 书目名称 | Computational Learning Theories |
| 副标题 | Models for Artificia |
| 编辑 | David C. Gibson,Dirk Ifenthaler |
| 视频video | |
| 概述 | Integrates learning and complexity theories.Outlines AI roles for individual, team and organizational learning.Provides advanced perspectives in learning theories related to advances in artificial int |
| 丛书名称 | Advances in Analytics for Learning and Teaching |
| 图书封面 |  |
| 描述 | .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.. |
| 出版日期 | Book 2024 |
| 关键词 | Artificial Intelligence; Learning Theory; Computational Learning; Social Epistemology; Knowledge Acquisi |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-65898-3 |
| isbn_softcover | 978-3-031-65900-3 |
| isbn_ebook | 978-3-031-65898-3Series ISSN 2662-2122 Series E-ISSN 2662-2130 |
| issn_series | 2662-2122 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
发表于 2025-3-21 16:44:23
