A Context Awareness Architecture for Mobile Learning Based on Fuzzy Petri Nets

The portability and immediate communication properties of mobile devices influence the learning processes in accessing resources and transferring data. The strength of mobile learning is the personalization and mobility; therefore it must support the availability of sensing contextual information about the learner and provide the learning content with mobile metadata. Based on fuzzy Petri nets, a context awareness architecture for mobile learning supporting English learning at anytime and anywhere is proposed in this paper. And then, learning object knowledge representation and reasoning under multi-constraints (contextual information) are discussed. Finally, an algorithm of approximate fuzzy reasoning based on matrix operation is suggested. The example indicates that fuzzy reasoning process is simple and quick, and the efficiency of the reasoning is also improved due to the parallel operation ability of Petri Nets.