Recommender Systems for Technology Enhanced Learning

Research Trends and Applications

Editors: Manouselis, N., Drachsler, H., Verbert, K., Santos, O.C. (Eds.)

  • Presents cutting edge research from leading experts in the growing field of Recommender Systems for Technology Enhanced Learning (RecSys TEL)
  • International contributions are included to demonstrate the merging of various efforts and communities
  • Topics include: Linked Data and the Social Web as Facilitators for TEL Recommender Systems in Research and Practice, Personalised Learning-Plan Recommendations in Game-Based Learning and Recommendations from Heterogeneous Sources in a Technology Enhanced Learning Ecosystem
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eBook $99.00
price for USA (gross)
  • ISBN 978-1-4939-0530-0
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $129.00
price for USA
  • ISBN 978-1-4939-0529-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $129.00
price for USA
  • ISBN 978-1-4939-4656-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of individuals and organizations. Information retrieval is a pivotal activity in TEL and the deployment of recommender systems has attracted increased interest during the past years.

Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. The goal is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices.

Contributions address the following topics: i) user and item data that can be used to support learning recommendation systems and scenarios, ii) innovative methods and techniques for recommendation purposes in educational settings and iii) examples of educational platforms and tools where recommendations are incorporated.

Reviews

From the book reviews:

“Book represents a collection of state-of-the-art contributions devoted to RSs for TEL and explores contemporary research achievements in the area. … This very interesting, well-timed volume will provide great opportunities for PhD students and newcomers to this field to continue with high-quality research efforts. The book is also interesting for master’s students who would like to acquire adequate knowledge and emergent research achievements in this field. Secondary school teachers and experienced researchers could also find this book useful and interesting.” (M. Ivanović, Computing Reviews, October, 2014)

Table of contents (14 chapters)

  • Collaborative Filtering Recommendation of Educational Content in Social Environments Utilizing Sentiment Analysis Techniques

    Karampiperis, Pythagoras (et al.)

    Pages 3-23

  • Towards Automated Evaluation of Learning Resources Inside Repositories

    Cechinel, Cristian (et al.)

    Pages 25-46

  • A Survey on Linked Data and the Social Web as Facilitators for TEL Recommender Systems

    Dietze, Stefan (et al.)

    Pages 47-75

  • The Learning Registry: Applying Social Metadata for Learning Resource Recommendations

    Bienkowski, Marie (et al.)

    Pages 77-95

  • A Framework for Personalised Learning-Plan Recommendations in Game-Based Learning

    Hulpuş, Ioana (et al.)

    Pages 99-122

Buy this book

eBook $99.00
price for USA (gross)
  • ISBN 978-1-4939-0530-0
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $129.00
price for USA
  • ISBN 978-1-4939-0529-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $129.00
price for USA
  • ISBN 978-1-4939-4656-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Recommender Systems for Technology Enhanced Learning
Book Subtitle
Research Trends and Applications
Editors
  • Nikos Manouselis
  • Hendrik Drachsler
  • Katrien Verbert
  • Olga C. Santos
Copyright
2014
Publisher
Springer-Verlag New York
Copyright Holder
Springer Science+Business Media New York
eBook ISBN
978-1-4939-0530-0
DOI
10.1007/978-1-4939-0530-0
Hardcover ISBN
978-1-4939-0529-4
Softcover ISBN
978-1-4939-4656-3
Edition Number
1
Number of Pages
XIV, 306
Number of Illustrations and Tables
67 b/w illustrations
Topics