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Recommender Systems for Technology Enhanced Learning

Overview of attention for book
Cover of 'Recommender Systems for Technology Enhanced Learning'

Table of Contents

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    Book Overview
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    Chapter 1 Collaborative Filtering Recommendation of Educational Content in Social Environments Utilizing Sentiment Analysis Techniques
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    Chapter 2 Towards Automated Evaluation of Learning Resources Inside Repositories
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    Chapter 3 A Survey on Linked Data and the Social Web as Facilitators for TEL Recommender Systems
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    Chapter 4 The Learning Registry: Applying Social Metadata for Learning Resource Recommendations
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    Chapter 5 A Framework for Personalised Learning-Plan Recommendations in Game-Based Learning
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    Chapter 6 An Approach for an Affective Educational Recommendation Model
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    Chapter 7 The Case for Preference-Inconsistent Recommendations
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    Chapter 8 Further Thoughts on Context-Aware Paper Recommendations for Education
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    Chapter 9 Towards a Social Trust-Aware Recommender for Teachers
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    Chapter 10 ALEF: From Application to Platform for Adaptive Collaborative Learning
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    Chapter 11 Two Recommending Strategies to Enhance Online Presence in Personal Learning Environments
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    Chapter 12 Recommendations from Heterogeneous Sources in a Technology Enhanced Learning Ecosystem
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    Chapter 13 COCOON CORE: CO-author REcommendations Based on Betweenness Centrality and Interest Similarity
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    Chapter 14 Scientific Recommendations to Enhance Scholarly Awareness and Foster Collaboration
Overall attention for this book and its chapters
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Mentioned by

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1 X user

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55 Mendeley
Summary X
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Title
Recommender Systems for Technology Enhanced Learning
Published by
Springer New York, January 2014
DOI 10.1007/978-1-4939-0530-0
ISBNs
978-1-4939-0529-4, 978-1-4939-0530-0
Editors

Nikos Manouselis, Hendrik Drachsler, Katrien Verbert, Olga C. Santos

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 4%
Unknown 53 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 27%
Student > Master 11 20%
Researcher 6 11%
Student > Doctoral Student 3 5%
Student > Bachelor 3 5%
Other 11 20%
Unknown 6 11%
Readers by discipline Count As %
Computer Science 23 42%
Social Sciences 14 25%
Engineering 3 5%
Business, Management and Accounting 2 4%
Agricultural and Biological Sciences 1 2%
Other 5 9%
Unknown 7 13%

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