Computational Intelligence for Technology Enhanced Learning

  • Fatos Xhafa
  • Santi Caballé
  • Ajith Abraham
  • Thanasis Daradoumis
  • Angel Alejandro Juan Perez

Part of the Studies in Computational Intelligence book series (SCI, volume 273)

Table of contents

  1. Front Matter
  2. Urszula Markowska-Kaczmar, Halina Kwasnicka, Mariusz Paradowski
    Pages 1-23
  3. Soumya Banerjee, Monica Chis, G. S. Dangayach
    Pages 59-77
  4. Nor Bahiah Hj Ahmad, Siti Mariyam Shamsuddin, Ajith Abraham
    Pages 99-124
  5. Marta Rey-López, Rebeca P. Díaz-Redondo, Ana Fernández-Vilas, José J. Pazos-Arias
    Pages 125-142
  6. Kurosh Madani, Amine Chohra, Arash Bahrammirzaee, Dalel Kanzari
    Pages 169-194
  7. Pavla Dráždilová, Gamila Obadi, Kateřina Slaninová, Shawki Al-Dubaee, Jan Martinovič, Václav Snášel
    Pages 195-224
  8. Valeria Marina Monetti, Loredana Randazzo, Antonello Santini, Gerardo Toraldo
    Pages 225-248
  9. Back Matter

About this book


E-Learning has become one of the most wide spread ways of distance teaching and learning. Technologies such as Web, Grid, and Mobile and Wireless networks are pushing teaching and learning communities to find new and intelligent ways of using these technologies to enhance teaching and learning activities. Indeed, these new technologies can play an important role in increasing the support to teachers and learners, to shorten the time to learning and teaching; yet, it is necessary to use intelligent techniques to take advantage of these new technologies to achieve the desired support to teachers and learners and enhance learners’ performance in distributed learning environments.

The chapters of this volume bring advances in using intelligent techniques for technology enhanced learning as well as development of e-Learning applications based on such techniques and supported by technology. Such intelligent techniques include clustering and classification for personalization of learning, intelligent context-aware techniques, adaptive learning, data mining techniques and ontologies in e-Learning systems, among others.

Academics, scientists, software developers, teachers and tutors and students interested in e-Learning will find this book useful for their academic, research and practice activity.


Learning management system Web artificial intelligence behavior computational intelligence data analysis data mining e-learning fuzzy intelligence learning mathematics mobile Learning ontology performance

Editors and affiliations

  • Fatos Xhafa
    • 1
  • Santi Caballé
    • 2
  • Ajith Abraham
    • 3
  • Thanasis Daradoumis
    • 2
  • Angel Alejandro Juan Perez
    • 4
  1. 1.Department of Languages and Informatics SystemsPolytechnic University of CataloniaBarcelonaSpain
  2. 2.Department of Computer Sciences Multimedia and TelecommunicationsOpen University of CataloniaBarcelonaSpain
  3. 3.Machine Intelligence Research Labs (MIR Labs)Scientific Network for Innovation and Research ExcellenceAuburnUSA
  4. 4.Department of Information SciencesOpen University of CataloniaBarcelonaSpain

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2010
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-11223-2
  • Online ISBN 978-3-642-11224-9
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site
Industry Sectors
IT & Software
Oil, Gas & Geosciences