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 1-880094-76-2Full text not available from this repository.
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.
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