The aim of this paper is to propose a customized recommendation model of educational resources for virtual courses that incorporates the benefits of ubiquitous computing and intelligent agents. This model is intended to provide relevant and personalized information to students about their virtual courses planning, online assessment, search and retrieval of learning objects. The methodology used for the construction of the system is MAS-CommonKADS which offers useful models for the phases of conceptualization, analysis and design expressed through artifacts provided by the Agent Unified Modeling Language (AUML). The prototype developed exhibits intelligent proactive and deliberative agents that allow the search and recommendation of information adapted to the student's profile. To validate the system a testing phase on a learning scenario was performed which demonstrate the effectiveness of using this kind of technology within ubiquitous virtual learning environments.
Abstract. In the last decade, some useful contributions have occurred to elearning system development such as adaptation, ubiquity, personalization, as well as context-awareness services. The aim of this paper is to present the advantages brought by the integration of ubiquitous computing along with distributed artificial intelligence techniques in order to build an adaptive and personalized context-aware learning system by using mobile devices. Based on this model we propose a multi-agent context-aware u-learning system that offers several functionalities such as context-aware learning planning, personalized course evaluation, selection of learning objects according to student profile, search of learning objects in repository federations, search of thematic learning assistants, and access of current context-aware collaborative learning activities involved. In addition, several context-awareness services are incorporated within the adaptive e-learning system that can be used from mobile devices. In order to validate the model a prototype was built and tested through a case study. Results obtained demonstrate the effectiveness of using this kind of approaches in virtual learning environments which constitutes an attempt to improve learning processes.
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