Data Mining and Learning Analytics: Applications in Educational Research (Wiley Series on Methods and Applications in Data Mining)

  • 出版商: Wiley
  • 出版日期: 2016-09-26
  • 售價: $4,710
  • 貴賓價: 9.5$4,475
  • 語言: 英文
  • 頁數: 320
  • 裝訂: Hardcover
  • ISBN: 1118998235
  • ISBN-13: 9781118998236
  • 相關分類: Data-mining
  • 海外代購書籍(需單獨結帳)

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商品描述

Addresses the impacts of data mining on education and reviews applications in educational research teaching, and learning 

This book discusses the insights, challenges, issues, expectations, and practical implementation of data mining (DM) within educational mandates. Initial series of chapters offer a general overview of DM, Learning Analytics (LA), and data collection models in the context of educational research, while also defining and discussing data mining’s four guiding principles— prediction, clustering, rule association, and outlier detection. The next series of chapters showcase the pedagogical applications of Educational Data Mining (EDM) and feature case studies drawn from Business, Humanities, Health Sciences, Linguistics, and Physical Sciences education that serve to highlight the successes and some of the limitations of data mining research applications in educational settings. The remaining chapters focus exclusively on EDM’s emerging role in helping to advance educational research—from identifying at-risk students and closing socioeconomic gaps in achievement to aiding in teacher evaluation and facilitating peer conferencing. This book features contributions from international experts in a variety of fields.

  •  Includes case studies where data mining techniques have been effectively applied to advance teaching and learning
  • Addresses applications of data mining in educational research, including: social networking and education; policy and legislation in the classroom; and identification of at-risk students
  • Explores Massive Open Online Courses (MOOCs) to study the effectiveness of online networks in promoting learning and understanding the communication patterns among users and students
  • Features supplementary resources including a primer on foundational aspects of educational mining and learning analytics

Data Mining and Learning Analytics: Applications in Educational Research is written for both scientists in EDM and educators interested in using and integrating DM and LA to improve education and advance educational research.

商品描述(中文翻譯)

本書探討資料探勘對教育的影響,並回顧其在教育研究、教學和學習中的應用。

本書討論了資料探勘(DM)在教育任務中的見解、挑戰、問題、期望和實際實施。最初的一系列章節提供了資料探勘、學習分析(LA)和資料收集模型在教育研究背景下的一般概述,同時定義並討論資料探勘的四個指導原則——預測、聚類、規則關聯和異常檢測。接下來的章節展示了教育資料探勘(EDM)的教學應用,並以商業、人文、健康科學、語言學和物理科學教育中的案例研究為例,突顯資料探勘研究在教育環境中的成功與一些限制。其餘章節則專注於EDM在推進教育研究中的新興角色——從識別高風險學生和縮小成就的社會經濟差距,到協助教師評估和促進同儕會議。本書匯集了來自各個領域的國際專家的貢獻。

- 包含資料探勘技術有效應用於推進教學和學習的案例研究
- 討論資料探勘在教育研究中的應用,包括:社交網路與教育;課堂中的政策與立法;以及高風險學生的識別
- 探索大規模開放線上課程(MOOCs),研究線上網路在促進學習中的有效性,以及用戶和學生之間的溝通模式
- 提供補充資源,包括教育探勘和學習分析基礎方面的入門指南

《資料探勘與學習分析:教育研究中的應用》是為EDM領域的科學家和有興趣使用及整合DM和LA以改善教育和推進教育研究的教育工作者所撰寫的。