Abstract
It has been proven that adopting the “one size fits one” approach has better learning outcomes than the “one size fits all” one. A customized learning experience is attainable with the use of learner models, the main source of variability, in adaptive educational hypermedia systems or any intelligent learning environment. While such a model includes a large number of characteristics which can be difficult to incorporate and use, several standards that were developed to overcome these complexities. 
 In this paper, the proposed work intents to improve learner’s model representation to meet the requirements and needs of adaptation. We took IMS-LIP, IMS-ACCLIP and IMS-RDCEO standards into consideration and incorporated their characteristics to our proposed learner model so that it conforms to international standards. Moreover, the suggested learner model takes advantage of the semantic web technologies that offer a better data organization, indexing and management and ensures the reusability, the interoperability and the extensibility of this model. Furthermore, due to the use of ontologies, the metadata about a learner can be used by a wide range of personalization techniques to provide more accurate customization.
Highlights
E-learning has moved from traditional content delivery approaches to a personalized, adaptive and learner-centered knowledge transfer
That can be used as an integral ITS module and can be accessed from a web-based application. [18] describe learners’ model ontology for creating personalized e-Learning systems based on learner’s abilities, learning styles, prior knowledge and preferences. [19] introduce a semantic learner model based on the FOAF ontology to support automation of the process of grouping students and preserve at the same time each learner’s personal needs and interests
Considering reuse: We investigated the learner modeling standards mentioned in section 5 as well as upper, domain-specific, reference ontologies and ontologies that have been validated through use in other applications
Summary
E-learning has moved from traditional content delivery approaches to a personalized, adaptive and learner-centered knowledge transfer. This adaptation is essentially based on a meticulous design of the learner model, which is the core component of any adaptive learning system. Recent developments in the semantic web have captivated researcher on using these technologies for developing adaptive e-learning systems (i.e. learner modeling, domain knowledge representing, etc.). From this perspective, the semantic web allows the provision of knowledge and learning content in various forms that might be distributed over a heterogeneous network but with semantic links to each other. It allows web content to be read, processed and interpreted by humans and machines accurately [3] It provides a framework based on formal logic for structured, distributed and extensible knowledge. That can be used as an integral ITS module and can be accessed from a web-based application. [18] describe learners’ model ontology for creating personalized e-Learning systems based on learner’s abilities, learning styles, prior knowledge and preferences. [19] introduce a semantic learner model based on the FOAF ontology to support automation of the process of grouping students and preserve at the same time each learner’s personal needs and interests
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