David C. Gibson – författare
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6 produkter
6 produkter
Häftad, Engelska
533 kr
Skickas inom 3-6 vardagar
Häftad, Engelska
406 kr
Skickas inom 3-6 vardagar
Inbunden, Engelska, 2023
646 kr
Skickas inom 10-15 vardagar
This book integrates foundational ideas from psychology, immersive digital learning environments supported by theories and methods of the learning sciences, particularly in pursuit of questions of cognition, behavior and emotion factors in digital learning experiences. New and emerging foundations of theory and analysis based on observation of digital traces are enhanced by data science, particularly machine learning, with extensions to deep learning, natural language processing and artificial intelligence brought into service to better understand higher-order thinking capacities such as self-regulation, collaborative problem-solving and social construction of knowledge. As a result, this edited volume presents a collection of indicators or measurements focusing on learning processes and related behavior, (meta-)cognition, emotion and motivation, as well as social processes. In addition, each section of the book includes an invited commentary from a related field, such as educational psychology, cognitive science, learning science, etc.
Häftad, Engelska, 2024
643 kr
Skickas inom 5-8 vardagar
This book integrates foundational ideas from psychology, immersive digital learning environments supported by theories and methods of the learning sciences, particularly in pursuit of questions of cognition, behavior and emotion factors in digital learning experiences.
Inbunden, Engelska, 2024
1 656 kr
Skickas inom 5-8 vardagar
This book shows how artificial intelligence grounded in learning theories can promote individual learning, team productivity and multidisciplinary knowledge-building.
Häftad, Engelska, 2025
1 664 kr
Skickas inom 10-15 vardagar
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 collaborationpromoting individual learningbalancing personalization with privacydealing with biases and promoting fairnessexplaining decisions and recommendations to build trust and accountabilitycontinuously balancing and adapting to individual, team and organizational goalsgenerating and generalizing knowledge across fields and domainsThe book will be of interest to educational professionals, researchers, and developers of educational technology that utilize artificial intelligence.