This book describes theoretical elements, practical approaches, and specialized tools that systematically organize, characterize, and analyze big data gathered from educational affairs and settings. Moreover, the book shows several inference criteria to leverage and produce descriptive, explanatory, and predictive closures to study and understand education phenomena at in classroom and online environments.
This is why diverse researchers and scholars contribute with valuable chapters to ground with well-–sounded theoretical and methodological constructs in the novel field of Educational Data Science (EDS), which examines academic big data repositories, as well as to introduces systematic reviews, reveals valuable insights, and promotes its application to extend its practice.
EDS as a transdisciplinary field relies on statistics, probability, machine learning, data mining, and analytics, in addition to biological, psychological, and neurological knowledge aboutlearning science. With this in mind, the book is devoted to those that are in charge of educational management, educators, pedagogues, academics, computer technologists, researchers, and postgraduate students, who pursue to acquire a conceptual, formal, and practical landscape of how to deploy EDS to build proactive, real- time, and reactive applications that personalize education, enhance teaching, and improve learning!
Chapter “Sync Ratio and Cluster Heat Map for Visualizing Student Engagement” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
"Sinopsis" puede pertenecer a otra edición de este libro.
Prof. Alejandro Peña-Ayala, is professor of Artificial Intelligence on Education & cognition in the School of Electric & Mechanical Engineering of the National Polytechnic Institute of México. Dr. Peña-Ayala has published more than 50 scientific works and is author of three machine learning patents (two of them in progress to be authorized), including the role of guest-editor for six Springer Book Series and guest-editor for an Elsevier journal. He is fellow of the National Researchers System of Mexico, the Mexican Academy of Sciences, Academy of Engineering, and the Mexican Academy of Informatics. Professor Peña-Ayala was scientific visitor of the MIT in 2016, made his postdoc at the Osaka University 2010-2012, and earned with honors his PhD, M. Sc., & B. Sc. in computer sciences, artificial intelligence, and informatics respectively.
This book describes theoretical elements, practical approaches, and specialized tools that systematically organize, characterize, and analyze big data gathered from educational affairs and settings. Moreover, the book shows several inference criteria to leverage and produce descriptive, explanatory, and predictive closures to study and understand education phenomena at in classroom and online environments.
This is why diverse researchers and scholars contribute with valuable chapters to ground with well--sounded theoretical and methodological constructs in the novel field of Educational Data Science (EDS), which examines academic big data repositories, as well as to introduces systematic reviews, reveals valuable insights, and promotes its application to extend its practice.
EDS as a transdisciplinary field relies on statistics, probability, machine learning, data mining, and analytics, in addition to biological, psychological, and neurological knowledge aboutlearning science. With this in mind, the book is devoted to those that are in charge of educational management, educators, pedagogues, academics, computer technologists, researchers, and postgraduate students, who pursue to acquire a conceptual, formal, and practical landscape of how to deploy EDS to build proactive, real- time, and reactive applications that personalize education, enhance teaching, and improve learning!
Chapter "Sync Ratio and Cluster Heat Map for Visualizing Student Engagement" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware Englisch. Nº de ref. del artículo: 9789819900282
Cantidad disponible: 2 disponibles
Librería: moluna, Greven, Alemania
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book describes theoretical elements, practical approaches, and specialized tools that systematically organize, characterize, and analyze big data gathered from educational affairs and settings. Moreover, the book shows several inference criteria to . Nº de ref. del artículo: 1609737521
Cantidad disponible: Más de 20 disponibles
Librería: preigu, Osnabrück, Alemania
Taschenbuch. Condición: Neu. Educational Data Science: Essentials, Approaches, and Tendencies | Proactive Education based on Empirical Big Data Evidence | Alejandro Peña-Ayala | Taschenbuch | xiii | Englisch | 2024 | Springer Singapore | EAN 9789819900282 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Nº de ref. del artículo: 129103810
Cantidad disponible: 5 disponibles
Librería: Books Puddle, New York, NY, Estados Unidos de America
Condición: New. 2023rd edition NO-PA16APR2015-KAP. Nº de ref. del artículo: 26402252361
Cantidad disponible: 4 disponibles
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book describes theoretical elements, practical approaches, and specialized tools that systematically organize, characterize, and analyze big data gathered from educational affairs and settings. Moreover, the book shows several inference criteria to leverage and produce descriptive, explanatory, and predictive closures to study and understand education phenomena at in classroom and online environments.This is why diverse researchers and scholars contribute with valuable chapters to ground with well-¿sounded theoretical and methodological constructs in the novel field of Educational Data Science (EDS), which examines academic big data repositories, as well as to introduces systematic reviews, reveals valuable insights, and promotes its application to extend its practice.EDS as a transdisciplinary field relies on statistics, probability, machine learning, data mining, and analytics, in addition to biological, psychological, and neurological knowledge aboutlearning science. With this in mind, the book is devoted to those that are in charge of educational management, educators, pedagogues, academics, computer technologists, researchers, and postgraduate students, who pursue to acquire a conceptual, formal, and practical landscape of how to deploy EDS to build proactive, real- time, and reactive applications that personalize education, enhance teaching, and improve learning!Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 312 pp. Englisch. Nº de ref. del artículo: 9789819900282
Cantidad disponible: 1 disponibles
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering. Nº de ref. del artículo: 9789819900282
Cantidad disponible: 1 disponibles
Librería: Majestic Books, Hounslow, Reino Unido
Condición: New. Print on Demand. Nº de ref. del artículo: 395206038
Cantidad disponible: 4 disponibles
Librería: Biblios, Frankfurt am main, HESSE, Alemania
Condición: New. PRINT ON DEMAND. Nº de ref. del artículo: 18402252355
Cantidad disponible: 4 disponibles