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Investigation on student modeling in adaptive e-learning systems

Investigation on student modeling in adaptive e-learning systems

Cemel Nat, Muesser, Bacon, Liz and Dastbaz, Mohammad (2009) Investigation on student modeling in adaptive e-learning systems. In: Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2009. 2009 (1). Association for Advancement of Computing in Education (ACCE), Chesapeake, VA, USA, pp. 2420-2427. ISBN 1-880094-76-2

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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 the future of this field is wide open (Shute, 2007). This paper aims to investigate developed and emerging technologies for student modeling in personalized e-learning systems and discusses 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.

Item Type: Conference Proceedings
Title of Proceedings: Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2009
Additional Information: [1] World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (ELEARN) 2009 Vancouver, Canada, October 26, 2009
Uncontrolled Keywords: e-learning systems, adaptive e-learning
Subjects: L Education > LC Special aspects of education
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Department of Computing and Information Systems
Related URLs:
Last Modified: 14 Oct 2016 09:17
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/6905

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