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Educational Data Science: Essentials, Approaches, and Tendencies : Proactive Education based on Empirical Big Data Evidence / edited by Alejandro Peña-Ayala
(Big Data Management. ISSN:25220187)

データ種別	電子ブック
版	1st ed. 2023.
出版者	(Singapore : Springer Nature Singapore : Imprint: Springer)
出版年	2023
大きさ	XIII, 291 p. 1 illus : online resource
著者標目	Peña-Ayala, Alejandro editor SpringerLink (Online service)

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URL	巻　次	配架場所	請求記号	登録番号	コメント	刷　年	状　態	利用注記	ISBN	予約	請求メモ
URL		射水-電子	007	EB0001326	Computer Scinece R0 2005-6,2022-3				9789819900268

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一般注記	1. Engaging in Student-Centered Educational Data Science through Learning Engineering -- 2. A review of clustering models in educational data science towards fairness-aware learning -- 3. Educational Data Science: Is an “Umbrella Term” or an Emergent Domain? -- 4. Educational Data Science Approach for End-to-End Quality Assurance Process for Building Credit-Worthy Online Courses -- 5. Understanding the Effect of Cohesion in Academic Writing Clarity Using Education Data Science -- 6. Sequential pattern mining in educational data: the application context, potential, strengths, and limitations -- 7. Sync Ratio and Cluster Heat Map for Visualizing Student Engagement 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 about learning 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! HTTP:URL=https://doi.org/10.1007/978-981-99-0026-8
件　名	LCSH:Artificial intelligence -- Data processing 全ての件名で検索 LCSH:Data mining LCSH:Big data FREE:Data Science FREE:Data Mining and Knowledge Discovery FREE:Big Data
分　類	LCC:Q336 DC23:005.7
書誌ID	EB00000714
ISBN	9789819900268