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Utilizing Learning Analytics to Support Study Success

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Cover of 'Utilizing Learning Analytics to Support Study Success'

Table of Contents

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    Book Overview
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    Chapter 1 Educational Theories and Learning Analytics: From Data to Knowledge
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    Chapter 2 Utilising Learning Analytics for Study Success: Reflections on Current Empirical Findings
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    Chapter 3 Supporting Stakeholders with Learning Analytics to Increase Study Success
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    Chapter 4 Implementing Learning Analytics into Existing Higher Education Legacy Systems
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    Chapter 5 When Students Get Stuck: Adaptive Remote Labs as a Way to Support Students in Practical Engineering Education
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    Chapter 6 Learning Analytics Challenges to Overcome in Higher Education Institutions
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    Chapter 7 The LAPS Project: Using Machine Learning Techniques for Early Student Support
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    Chapter 8 Monitoring the Use of Learning Strategies in a Web-Based Pre-course in Mathematics
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    Chapter 9 Issues and Challenges for Implementing Writing Analytics at Higher Education
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    Chapter 10 Digital Applications as Smart Solutions for Learning and Teaching at Higher Education Institutions
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    Chapter 11 Learning Analytics to Support Teachers’ Assessment of Problem Solving: A Novel Application for Machine Learning and Graph Algorithms
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    Chapter 12 Utilizing Learning Analytics in Small Institutions: A Study of Performance of Adult Learners in Online Classes
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    Chapter 13 Empowering Teachers to Personalize Learning Support
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    Chapter 14 Predicting Success, Preventing Failure
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    Chapter 15 Using Learning Analytics to Examine Relationships Between Learners’ Usage Data with Their Profiles and Perceptions: A Case Study of a MOOC Designed for Working Professionals
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    Chapter 16 Learning Analytics Leading to Remote Invigilation for eTests: A Case Study
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    Chapter 17 Epilogue: Future Directions on Learning Analytics to Enhance Study Success
Attention for Chapter 14: Predicting Success, Preventing Failure
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Citations

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Readers on

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Chapter title
Predicting Success, Preventing Failure
Chapter number 14
Book title
Utilizing Learning Analytics to Support Study Success
Published by
Springer, Cham, January 2019
DOI 10.1007/978-3-319-64792-0_14
Book ISBNs
978-3-31-964791-3, 978-3-31-964792-0
Authors

Danny Glick, Anat Cohen, Eitan Festinger, Di Xu, Qiujie Li, Mark Warschauer, Glick, Danny, Cohen, Anat, Festinger, Eitan, Xu, Di, Li, Qiujie, Warschauer, Mark

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 13%
Student > Master 2 13%
Professor 2 13%
Other 1 6%
Lecturer 1 6%
Other 2 13%
Unknown 6 38%
Readers by discipline Count As %
Arts and Humanities 3 19%
Social Sciences 3 19%
Psychology 1 6%
Computer Science 1 6%
Unknown 8 50%