To view the full text of this article...

Subscribe for faster access!

Subscribe for only $19/month (or $150/year) and receive immediate access to 20,000+ documents/media files.

Purchase individual articles and papers

Purchase fulltext access to individual articles and papers for $9.95 USD each. You can purchase as a guest or save your information for faster access later.

Investigation on Student Modeling in Adaptive E-learning Systems

New Search

Print Abstract

E-mail Abstract

Full Text

View Slides

Save to My Collections

Export Citation

Cemal Nat, M. (2009). Investigation on Student Modeling in Adaptive E-learning Systems. In T. Bastiaens et al. (Eds.), Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2009 (pp. 2420-2427). Chesapeake, VA: AACE.
Retrieved from http://www.editlib.org/p/32824.

• Share:
• 
• 
• 
• 
• 
• 
• 

Conference Information

World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (ELEARN) 2009
Vancouver, Canada
October 26, 2009
ISBN 1-880094-76-2
  Theo Bastiaens, Jon Dron & Cindy Xin
AACE

More Information on ELEARN
Table of Contents

Author

Muesser Cemal Nat, University of Greenwich, United Kingdom

Abstract

Adaptive e-learning systems hold promise for the future development as innovative technologies continuously appear in the field. Along with the facilities that they provide, they have led to enhanced education. Students can receive customized learning with improved alternatives for learning anytime and anywhere. This field has a direct relation with the emergence of new technologies, advances in learning, machine learning and artificial intelligence therefore future of this field is wide open (Shute, 2007). This paper aims to investigate developed and emerging technologies for student modelling in personalized e-learning systems and discuss a proposed style that is being developed to address issues in the field of adaptive e-learning. Various techniques have been generated for collecting data about students’ characteristics and integrated into e-learning systems.

Also Read

• Designing with and for Technological Pedagogical Content Knowledge: The Evolution of GeoThentic
• Using e-Learning Technologies in Developing Remeditainment Products for the Treatment of Children with Central Auditory Processing Disorder (CAPD)
• Post degree online course in Haematopathology and e-Learning: description of an innovative curriculum in e-Learning
• Podcasts in Higher Education: What Students Want, What They Really Need, and How This Might be Supported
• Using RSS in Collaborative Course Development
• Teaching for Success: Technology and Learning Styles in Preservice Teacher Education
• Reducing E-Learning Development Costs Using a Streamlined XML-based Approach
• Using Authentic Situations and Avatars to Build Knowledge in an E-Learning Environment
• Inspiring Learning and Teaching: Using e-tools to Facilitate Change
• Scenario making support in PBL

Tags