Educational Data Science: Essentials, Approaches, and Tendencies: Proactive Education Based on Empirical Big Data Evidence

Peña-Ayala, Alejandro

Educational Data Science: Essentials, Approaches, and Tendencies: Proactive Education Based on Empirical Big Data Evidence
  • 出版商: Springer
  • 出版日期: 2024-05-01
  • 售價: $6,380
  • 貴賓價: 9.5 折 $6,061
  • 語言: 英文
  • 頁數: 291
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 981990028X
  • ISBN-13: 9789819900282
  • 相關分類: 大數據 Big-data、Data Science

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

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!


商品描述(中文翻譯)

本書描述了理論元素、實務方法和專業工具，系統性地組織、特徵化和分析從教育事務和環境中收集的大數據。此外，本書展示了幾個推論標準，以利用和產生描述性、解釋性和預測性結論，來研究和理解課堂及線上環境中的教育現象。

這就是為什麼多位研究者和學者貢獻了寶貴的章節，以建立在教育數據科學（Educational Data Science, EDS）這一新興領域中，具有良好理論和方法論基礎的內容，該領域檢視學術大數據庫，並引入系統性回顧，揭示有價值的見解，並促進其應用以擴展實踐。

EDS作為一個跨學科的領域，依賴於統計學、概率論、機器學習、數據挖掘和分析，此外還包括有關學習科學的生物學、心理學和神經學知識。考慮到這一點，本書專門針對負責教育管理的相關人員、教育工作者、教育學者、學術界人士、計算機技術專家、研究人員和研究生，幫助他們獲得如何部署EDS以建立主動、即時和反應式應用程序的概念性、正式和實務性知識，從而個性化教育、提升教學和改善學習！

作者簡介

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.

作者簡介(中文翻譯)

教授 Alejandro Peña-Ayala 是墨西哥國立工業學院電機與機械工程學院的人工智慧與教育及認知領域教授。Peña-Ayala 博士已發表超過 50 篇科學著作，並擁有三項機器學習專利（其中兩項正在授權中），此外，他還擔任過六本 Springer 書系列的客座編輯以及一本 Elsevier 期刊的客座編輯。他是墨西哥國家研究系統、墨西哥科學院、工程學院及墨西哥資訊學院的研究員。Peña-Ayala 教授於 2016 年擔任麻省理工學院的科學訪客，於 2010 至 2012 年在大阪大學進行博士後研究，並以優異的成績獲得計算機科學、人工智慧及資訊學的博士、碩士及學士學位。

類似商品