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Title: Machine learning based learner modeling for adaptive web-based learning
Authors: Aslan, Burak Galip
İnceoğlu, Mustafa Murat
Keywords: Adaptive web-based learning
Learner modeling
Machine learning
Learning systems
Interactive computer systems
Issue Date: 2007
Publisher: Springer Verlag
Source: Aslan, B. G., and İnceoğlu, M. M. (2007). Machine learning based learner modeling for adaptive web-based learning. Lecture Notes in Computer Science, 4705 LNCS(PART 1), 1133-1145. doi:10.1007/978-3-540-74472-6_94
Abstract: Especially in the first decade of this century, learner adapted interaction and learner modeling are becoming more important in the area of web-based learning systems. The complicated nature of the problem is a serious challenge with vast amount of data available about the learners. Machine learning approaches have been used effectively in both user modeling, and learner modeling implementations. Recent studies on the challenges and solutions about learner modeling are explained in this paper with the proposal of a learner modeling framework to be used in a web-based learning system. The proposed system adopts a hybrid approach combining three machine learning techniques in three stages.
Description: International Conference on Computational Science and its Applications, ICCSA 2007; Kuala Lumpur; Malaysia; 26 August 2007 through 29 August 2007
URI: http:/
ISBN: 9783540744689
ISSN: 0302-9743
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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