Modeling and design of an architecture for Adaptive Intelligent Educational Distributed CBR system.

By Soundouss Abroun, Mohamed Ghailani, Abdelhadi Fennan

Abstract


Nowadays E-learning systems have known notable progress in term of learning adaptation. Several systems were proposed in this context and different methods were adopted for the generation of customized learning paths. CBR is a problem-solving paradigm that is distracting increasing attention in the field of systems' personalization in various domains including E-learning, for the set of advantages that it provides as a decision-making tool in complex and unstructured environments, in addition to its capacity of reasoning in non-well described domains. In this regard, we present in this paper different CBR systems treating static and dynamic cases in the e-learning domain, and we propose, an architecture of an Adaptive Intelligent Educational Distributed CBR system that adopts a Dynamic CBR cycle for personalized pedagogical training generation, using Multi-Agent System to reduce system’s complexity, and it defined various ontologies providing a detailed description of knowledge and serving it reuse and sharing. We also present the implementation of the proposed architecture by introducing the system’s Technical Architecture and a scenario illustrating the system’s functioning for learning process generation.


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