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Educational Data Mining

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Cover of 'Educational Data Mining'

Table of Contents

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    Book Overview
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    Chapter 1 Which Contribution Does EDM Provide to Computer-Based Learning Environments?
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    Chapter 2 A Survey on Pre-Processing Educational Data
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    Chapter 3 How Educational Data Mining Empowers State Policies to Reform Education: The Mexican Case Study
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    Chapter 4 Modeling Student Performance in Higher Education Using Data Mining
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    Chapter 5 Using Data Mining Techniques to Detect the Personality of Players in an Educational Game
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    Chapter 6 Students’ Performance Prediction Using Multi-Channel Decision Fusion
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    Chapter 7 Predicting Student Performance from Combined Data Sources
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    Chapter 8 Predicting Learner Answers Correctness Through Eye Movements with Random Forest
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    Chapter 9 Mining Domain Knowledge for Coherence Assessment of Students Proposal Drafts
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    Chapter 10 Adaptive Testing in Programming Courses Based on Educational Data Mining Techniques
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    Chapter 11 Educational Data Mining
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    Chapter 12 Finding Dependency of Test Items from Students’ Response Data
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    Chapter 13 Mining Texts, Learner Productions and Strategies with ReaderBench
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    Chapter 14 Maximizing the Value of Student Ratings Through Data Mining
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    Chapter 15 Data Mining and Social Network Analysis in the Educational Field: An Application for Non-Expert Users
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    Chapter 16 Collaborative Learning of Students in Online Discussion Forums: A Social Network Analysis Perspective
Attention for Chapter 16: Collaborative Learning of Students in Online Discussion Forums: A Social Network Analysis Perspective
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Chapter title
Collaborative Learning of Students in Online Discussion Forums: A Social Network Analysis Perspective
Chapter number 16
Book title
Educational Data Mining
Published by
Springer International Publishing, January 2014
DOI 10.1007/978-3-319-02738-8_16
Book ISBNs
978-3-31-902737-1, 978-3-31-902738-8
Authors

Reihaneh Rabbany, Samira Elatia, Mansoureh Takaffoli, Osmar R. Zaïane, Rabbany, Reihaneh, Elatia, Samira, Takaffoli, Mansoureh, Zaïane, Osmar R.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 4%
Netherlands 1 <1%
Portugal 1 <1%
Japan 1 <1%
Spain 1 <1%
Unknown 113 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 28%
Student > Master 20 16%
Student > Doctoral Student 14 11%
Researcher 8 7%
Professor > Associate Professor 6 5%
Other 21 17%
Unknown 19 16%
Readers by discipline Count As %
Computer Science 38 31%
Social Sciences 30 25%
Psychology 6 5%
Engineering 5 4%
Linguistics 3 2%
Other 16 13%
Unknown 24 20%