Title:	SEMANTIC MODELLING FOR LEARNING STYLES AND LEARNING MATERIAL IN AN E-LEARNING ENVIRONMENT
Author(s):	Khawla Alhasan, Liming Chen and Feng Chen
ISBN:	978-989-8533-63-0
Editors:	Miguel Baptista Nunes and Maggie McPherson
Year:	2017
Edition:	Single
Keywords:	E-learning; Semantic Web; Personalisation; Adaptive System; Learning Style; FSLSM
Type:	Full Paper
First Page:	71
Last Page:	79
Language:	English
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Paper Abstract:	Various learners with various requirements have led to the raise of a crucial concern in the area of e-learning. A new technology for propagating learning to learners worldwide, has led to an evolution in the e-learning industry that takes into account all the requirements of the learning process. In spite of the wide growing, the e-learning technology is still lacking the ability to achieve the best personalised learning path for each learner resulting in performance dissatisfaction. Recent research indicates that each learner has a unique way of learning that leads to different preferences in the selection of the learning resources. Thus, the learning material must be tailored for the individual learners in order to meet their own personal needs. In this paper, we present a novel approach for designing a model for an adaptive e-learning course and learning styles based on ontology and semantic web technologies. In this approach, we build an adaptive student profile through analysing the pattern of the learner’s behaviour while using the e-learning course in accordance to the Felder- Silverman learning style model (FSLSM).
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