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Data Mining and Learning Analytics: Applications in Educational Research
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所在地：Cincinnati, Ohio, 美國
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估計於 10月30日 (星期四)至 11月4日 (星期二)之間送達 運送地點 94104
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- Educational Level
- Adult & Further Education, High School, Vocational School
- Subject
- Computer Science
- Level
- Intermediate
- ISBN
- 9781118998236
關於產品
Product Identifiers
Publisher
Wiley & Sons, Incorporated, John
ISBN-10
1118998235
ISBN-13
9781118998236
eBay Product ID (ePID)
219853213
Product Key Features
Number of Pages
320 Pages
Publication Name
Data Mining and Learning Analytics : Applications in Educational Research
Language
English
Publication Year
2016
Subject
Research, Databases / Data Mining, Statistics
Type
Textbook
Subject Area
Computers, Education
Series
Wiley Series on Methods and Applications in Data Mining Ser.
Format
Hardcover
Dimensions
Item Height
0.9 in
Item Weight
20 Oz
Item Length
9.1 in
Item Width
6.2 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
2016-016549
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
370.727
Synopsis
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., 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., 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.
LC Classification Number
LB1028.43.D385 2017