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Title:      LEARNER MODELING TO FACILITATE PERSONALIZED E-LEARNING EXPERIENCE
Author(s):      İlhami Görgün , Ali Türker , Yıldıray Ozan , Jürgen Heller
ISBN:      972-8924-05-4
Editors:      Kinshuk, Demetrios Sampson and Pedro Isaías
Year:      2005
Edition:      Single
Keywords:      Adaptivity, prior knowledge, ontological abstraction, knowledge representation.
Type:      Full Paper
First Page:      231
Last Page:      237
Language:      English
Cover:      cover          
Full Contents:      click to dowload Download
Paper Abstract:      This article describes a learner modeling strategy that is employed by an adaptive learning system in order to provide each learner with a personalized e-Learning experience. Parameters related to the learners’ prior knowledge, goal and learning style constitute the basis of the personalization and the adaptivity of the mentioned learning system. The present paper focuses on the mechanisms concerning the learner’s prior knowledge and the goal parameters. The learner modeling that takes into account the prior knowledge of the learners is achieved by developing an ontological abstraction. Based on this ontological abstraction, a knowledge base is constructed in order to introduce the knowledge representations of the domain model and the curricular model, the knowledge and the learning structures. These knowledge representations specify how the prior knowledge of a learner will be represented, and also how it will be assessed and continuously updated.
   

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