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Frontiers of Cyberlearning

Overview of attention for book
Cover of 'Frontiers of Cyberlearning'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Learning Any Time, Anywhere: Big Educational Data from Smart Devices
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    Chapter 2 Framing Learning Analytics and Educational Data Mining for Teaching: Critical Inferencing, Domain Knowledge, and Pedagogy
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    Chapter 3 Learning Traces, Competence Assessment, and Causal Inference for English Composition
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    Chapter 4 QUESGEN: A Framework for Automatic Question Generation Using Semantic Web and Lexical Databases
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    Chapter 5 A Big Data Reference Architecture for Teaching Social Media Mining
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    Chapter 6 Big Data in Education: Supporting Learners in Their Role as Reflective Practitioners
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    Chapter 7 Towards Big Data in Education: The Case at the Open University of the Netherlands
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    Chapter 8 Learning Analytics in Practice: Providing E-Learning Researchers and Practitioners with Activity Data
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    Chapter 9 Using Apache Spark for Modeling Student Behavior at Scale
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    Chapter 10 Towards a Cloud-Based Big Data Infrastructure for Higher Education Institutions
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    Chapter 11 Cloud Services in Collaborative Learning: Applications and Implications
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    Chapter 12 Cloud Computing Environment in Big Data for Education
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    Chapter 13 Head in the Clouds: Some of the Possible Issues with Cloud Computing in Education
Attention for Chapter 5: A Big Data Reference Architecture for Teaching Social Media Mining
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5 Mendeley
Summary
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Chapter title
A Big Data Reference Architecture for Teaching Social Media Mining
Chapter number 5
Book title
Frontiers of Cyberlearning
Published by
Springer, Singapore, January 2018
DOI 10.1007/978-981-13-0650-1_5
Book ISBNs
978-9-81-130649-5, 978-9-81-130650-1
Authors

Jochen Wulf

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 2 40%
Professor > Associate Professor 1 20%
Lecturer 1 20%
Unknown 1 20%
Readers by discipline Count As %
Business, Management and Accounting 1 20%
Agricultural and Biological Sciences 1 20%
Computer Science 1 20%
Unknown 2 40%

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