Enhancing Teaching and Learning through Educational Data Min

美国教育部教育数据挖掘概述文档

Enhancing Teaching and Learning Through Educational Data Mining and Learning Analytics: An Issue Brief

美国教育部教育数据挖掘概述文档

Enhancing Teaching and Learning

Through Educational Data Mining and Learning Analytics: An Issue Brief

U.S. Department of Education

Office of Educational Technology

Prepared by:

Marie Bienkowski

Mingyu Feng

Barbara Means

Center for Technology in Learning

SRI International

October 2012

美国教育部教育数据挖掘概述文档

This report was prepared for the U.S. Department of Education under Contract Number ED-04-CO-0040, Task 0010, with SRI International. The views expressed herein do not necessarily represent the positions or policies of the Department of Education. No official endorsement by the U.S. Department of Education is intended or should be inferred.

U.S. Department of Education

Arne Duncan

Secretary

Office of Educational Technology

Karen Cator

Director

October 2012

This report is in the public domain. Authorization to reproduce this report in whole or in part is granted. While permission to reprint this publication is not necessary, the suggested citation is: U.S. Department of Education, Office of Educational Technology, Enhancing Teaching and Learning Through Educational Data Mining and Learning Analytics: An Issue Brief, Washington, D.C., 2012.

This report is available on the Department’s Web site at . On request, this publication is available in alternate formats, such as Braille, large print, or

compact disc. For more information, please contact the Department’s Alternate Format Center at (202) 260-0852 or (202) 260-0818.

Technical Contact

Bernadette Adams

美国教育部教育数据挖掘概述文档

美国教育部教育数据挖掘概述文档

Contents

List of Exhibits .............................................................................................................................. iv Acknowledgments ......................................................................................................................... v Executive Summary ..................................................................................................................... vii

Introduction ................................................................................................................................... 1

Personalized Learning Scenarios ................................................................................................. 5

Data Mining and Analytics: The Research Base ........................................................................... 7

Educational Data Mining ........................................................................................................... 9

Learning Analytics ................................................................................................................... 13

Visual Data Analytics .............................................................................................................. 15

Data Use in Adaptive Learning Systems .................................................................................... 17

Educational Data Mining and Learning Analytics Applications ................................................... 25

User Knowledge Modeling ...................................................................................................... 28

User Behavior Modeling .......................................................................................................... 29

User Experience Modeling ...................................................................................................... 30

User Profiling .......................................................................................................................... 32

Domain Modeling .................................................................................................................... 33

Learning System Components and Instructional Principle Analysis ....................................... 34

Trend Analysis ........................................................................................................................ 35

Adaptation and Personalization .............................................................................................. 35

Implementation Challenges and Considerations ........................................................................ 37

Technical Challenges .............................................................................................................. 38

Limitations in Institutional Capacity ......................................................................................... 40

Privacy and Ethics Issues ....................................................................................................... 41

Recommendations ...................................................................................................................... 45

Educators ................................................................................................................................ 46

Researchers and Developers ................................................................................................. 49

Collaborations Across Sectors ................................................................................................ 50

Conclusion .................................................................................................................................. 51

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