A Context-Aware Approach for Modeling Bijective Adaptations between Context and Activity in a Mobile and Collaborative learning

Jihene Malek, Mona Laroussi, Alain Derycke, Henda Ben Ghezala

Abstract


Context-awareness is becoming a key aspect of mobile learning systems. In fact, an efficient mobile learning system has to be sensitive to the context that characterizes the interactions between humans, applications and the surrounding environment. Researches in context-aware mobile learning have concentrated on how to adapt application to context. In this paper, we present an innovative approach for modeling bijective adaptations between learning activities and context because they influence each others in learning processes. First, we identify contextual elements and their features relevant for mobile and collaborative learning. Then, we propose a multi-layer middleware that supports tasks for managing and adapting context. The originality of this middleware comes especially from its top-most layer which is an adaptor that defines two classes of functionalities: the adaptation of learning activities to context and the adaptation and updating of context to learning activities. Finally, we present a simulator that implements this adaptor and our bijective adaptation approach. This simulator based on context-aware and mobile learning scenario, makes possible the interactions of mobile learning applications with context (environment) in such a way that they can detect the contextual elements values changes in order to, on the one side, adapt their learning activities to provide services more appropriate to new values of the environment. On the other side, adapt and update contextual elements to the needs of their learning activities and preferences of the mobile user to create more adequate learning environment which helps him/her concentrate better on his/her learning activities.

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International Journal of Interactive Mobile Technologies. ISSN: 1865-7923
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