Qi wanxue (35 risultati)

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Condizione: New.

Paperback. Condizione: New. The book aims to design and construct early warning mechanisms based on the dynamic temporal tracking technology for online learning behaviors, driven by educational big data.By studying a massive amount of learning behavior instances generated in various interactive learning environments worldwide, the book explores the continuous sequences of correlated learning behaviors and characteristics. From various angles, the authors have devised a series of early warning measures that could effectively solve multiple issues in learning behaviors driven by educational big data. Additionally, the book predicts patterns and identifies risks by analyzing the temporal sequences of the entire learning process. While presenting a range of theoretical achievements and technical solutions to improve and design new online learning mode, it also provides relevant technical ideas and methodologies for research on similar problems.The book will attract scholars and students working on learning analytics and educational big data worldwide.…

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Paperback. Condizione: Brand New. 208 pages. 9.18x6.12x9.21 inches. In Stock.

Paperback. Condizione: New. The book aims to design and construct early warning mechanisms based on the dynamic temporal tracking technology for online learning behaviors, driven by educational big data.By studying a massive amount of learning behavior instances generated in various interactive learning environments worldwide, the book explores the continuous sequences of correlated learning behaviors and characteristics. From various angles, the authors have devised a series of early warning measures that could effectively solve multiple issues in learning behaviors driven by educational big data. Additionally, the book predicts patterns and identifies risks by analyzing the temporal sequences of the entire learning process. While presenting a range of theoretical achievements and technical solutions to improve and design new online learning mode, it also provides relevant technical ideas and methodologies for research on similar problems.The book will attract scholars and students working on learning analytics and educational big data worldwide.…

hardcover. Condizione: Fine.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New. 1st edition NO-PA16APR2015-KAP.

Condizione: New. 1st edition NO-PA16APR2015-KAP.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New. In English.

Hardback. Condizione: New. This book aims to fully demonstrate the burnout of learners in online learning processes. The authors propose a series of feasible and reliable solutions to sufficiently obtain and analyze massive instances of online learning behavior.In order to flexibly perceive and intervene in the "burnout state" and improve online learning processes and learning effectiveness, the authors design and construct various novel data analysis models and decision prediction methods using technological means and data-driven learning strategies. Their innovative methods, techniques, and decisions would benefit autonomous learning behavior tracking and stimulate the learning interest of online learning processes enabled by predictive learning analytics. By employing behavioral science research strategies, they build adaptive prediction and optimization measures for positive online learning patterns, improve learning behaviors, optimize learning states, and establish dynamic and sustainable knowledge tracing paths and behavior scheduling methods, enabling users to achieve self-organization and self-mobilization in their overall learning processes.The book will appeal to scholars and learners in Europe, North America, and Asia, especially those majoring in educational statistics and measurement, educational big data, learning analytics, educational psychology, artificial intelligence in education, computer science, and online collaborative learning.…