Learning by seamless migration - A kind of mobile working paradigm

Abstract

In this paper, we propose a kind of mobile learning paradigm - learning by seamless migration, which has the capability that task for learning dynamically follows the learner from place to place and machine to machine without learner awareness or intervention. Our key idea is this capability can be achieved by architecture of component platform and agent-based migrating mechanism. In order to study this learning paradigm, a description of pervasive computing task for learning and migrating granularity of task of learning has been suggested, firstly. Then, the architecture for seamless migration has been proposed, a kind of mechanism of seamless migration has been adopted, including solving several sub-problems. Finally, the validity evaluation of this kind of mobile working paradigm is shown by an experimental demo. Suggested learning paradigm by seamless migration is convenient to learn during mobility and is useful for the busy or mobile learner. © Springer-Verlag 2004.