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Big Data and Learning Analytics in Higher Education

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Cover of 'Big Data and Learning Analytics in Higher Education'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Overview of Big Data and Analytics in Higher Education
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    Chapter 2 Thoughts on Recent Trends and Future Research Perspectives in Big Data and Analytics in Higher Education
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    Chapter 3 Big Data in Higher Education: The Big Picture
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    Chapter 4 Preparing the Next Generation of Education Researchers for Big Data in Higher Education
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    Chapter 5 Managing the Embedded Digital Ecosystems (EDE) Using Big Data Paradigm
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    Chapter 6 The Contemporary Research University and the Contest for Deliberative Space
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    Chapter 7 Ethical Considerations in Adopting a University- and System-Wide Approach to Data and Learning Analytics
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    Chapter 8 Big Data, Higher Education and Learning Analytics: Beyond Justice, Towards an Ethics of Care
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    Chapter 9 Curricular and Learning Analytics: A Big Data Perspective
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    Chapter 10 Implementing a Learning Analytics Intervention and Evaluation Framework: What Works?
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    Chapter 11 GraphFES: A Web Service and Application for Moodle Message Board Social Graph Extraction
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    Chapter 12 Toward an Open Learning Analytics Ecosystem
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    Chapter 13 Predicting Four-Year Student Success from Two-Year Student Data
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    Chapter 14 Assessing Science Inquiry Skills in an Immersive, Conversation-Based Scenario
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    Chapter 15 Learning Analytics of Clinical Anatomy e-Cases
Attention for Chapter 10: Implementing a Learning Analytics Intervention and Evaluation Framework: What Works?
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Chapter title
Implementing a Learning Analytics Intervention and Evaluation Framework: What Works?
Chapter number 10
Book title
Big Data and Learning Analytics in Higher Education
Published by
Springer International Publishing, August 2016
DOI 10.1007/978-3-319-06520-5_10
Book ISBNs
978-3-31-906519-9, 978-3-31-906520-5
Authors

Bart Rienties, Simon Cross, Zdenek Zdrahal

Editors

Ben Kei Daniel

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 81 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 19%
Student > Master 13 16%
Researcher 9 11%
Lecturer > Senior Lecturer 6 7%
Other 4 5%
Other 16 20%
Unknown 18 22%
Readers by discipline Count As %
Computer Science 22 27%
Social Sciences 11 14%
Engineering 6 7%
Business, Management and Accounting 3 4%
Arts and Humanities 3 4%
Other 13 16%
Unknown 23 28%