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In this paper we present a knowledge-driven model for mobile learning based on the semantic Web. The knowledge model uses a global ontology space and a unified reasoning mechanism to integrate and aggregate knowledge describing both system-centric and user-centric context information. The reasoning engine perceives, understands, and translates context changes into new adaptation constraints in the operating environment to achieve personalized learning. In particular, the system strives to adapt the learning sequence and the learning content based on the learnerpsilas activity, profile, used technology, and surrounding environment. An initial system prototype is described and the obtained experimental results are very promising.