Key Techniques And Application For3G Based Mobile Learning Platform

With the development of Mobile and Wireless Network technology, Mobile learning (M-learning) becomes a hot research topic after E-Learning. This dissertation focuses on some problems of traditional learning such as low efficiency, boring learning methods and waste of resources underlying hardware and software and so on. To solve these problems, an improved mobile learning program to take full advantage of rich learning resources in3G network environment is proposed to realize efficient learning anytime and anywhere. Cloud technique is applied to mobile learning to realize the hardware and software reasonable resource allocation by means of virtualization. Then, ontology is applied to build user interest model and realize personal learning. Finally, granular computing is used to integrate lots of learning resources in order to achieve maximum efficiency of mobile learning. The main contributions are as follows.1) Traditional learning shortcomings are analyzed and mobile learning with new forms and new features are discussed. An improved M-learning model is proposed by using3G mobile networks and cloud techniques. To solve hardware and software resource sharing and utilization in3G network environment, cloud service is applied. Server virtualization technology of open source cloud platform is studied to realize the sharing of learning resources. On the basis of analysis of hierarchical structure of clouds, the integration program combined open-source platform for mobile learning (Eucalyptus) and open source learning platform (Moodle) is studied.2) The ontology theory is studied to realize individual learning. The ontology class hierarchy and semantic inference theories are used to design experts in the ontology database expert. The expert reasoning is achieved according to Jena Api semantic ontology and simple retrieval visualization is implemented by JSP. The design of the expert user interest ontology model and experimental case study are implemented at last. 3) Granular based learning resource integration techniques are studied, the granular computing and quotient space are used to learning information indexing to realize the indexing algorithm which provides the support for learning resource integration and efficient application4) The architecture of ontology mobile learning on the cloud platform is proposed in this paper. By setting the open source cloud platform Eucalyptus and configuring open source learning platform Moodle on the cloud, the initial3G network and cloud based mobile learning platform architecture is built.