Machine learning based learner modeling for adaptive web-based learning
Küçük Resim Yok
Tarih
2007
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer-Verlag Berlin
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
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.
Açıklama
International Conference on Computational Science and Its Applications (ICCSA 2007) -- AUG 26-29, 2007 -- Kuala Lumpur, MALAYSIA
Anahtar Kelimeler
adaptive web-based learning, learner modeling, machine learning
Kaynak
Computational Science and Its Applications - Iccsa 2007, Pt 1, Proceedings
WoS Q Değeri
N/A
Scopus Q Değeri
Q3
Cilt
4705