Machine learning based learner modeling for adaptive web-based learning

International Conference on Computational Science and Its Applications (ICCSA 2007) -- AUG 26-29, 2007 -- Kuala Lumpur, MALAYSIAWOS: 000250429300094Especially 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.Univ Perugia, Univ Calgary, Optima Numerics, Spark Planner Pte Ltd, Univ Calgary, SPARCS Lab, MASTER U