Semantic modelling for learning styles and learning material in an e-learning environment
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).
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the URI link.
Citation : Alhasan, K., Chen, L. and Chen, F. (2017) Semantic modelling for learning styles and learning material in an e-learning environment. In: proc. IADIS International Conference e-Learning 2017 (part of MCCSIS 2017), Lisbon, July 2017. IADIS. pp.71-79.
ISBN : 9789898533630
Research Group : CIIRG
Research Institute : Cyber Technology Institute (CTI)
Peer Reviewed : Yes
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