The Design of Ubiquitous Learning System with Computing Context-Aware Function

This research proposes a context-aware computing ubiquitous learning system architecture design. The system integrates data grid, the ability to perform context-awareness computing, and Improved Ganglia Agent design, structuring an architecture that is able to perform context awareness mobile network, creating a ubiquitous learning environment. The improved Ganglia Agent server could provide context information on system network traffic, the CPU load of the content server, and hard disk capacity, and utilize the information to balance the load of back-end content server, providing a flexible expandability mechanism for the back-end content server. The framework of the proposed ubiquitous learning system that has context-awareness computing ability is consisted of 3 major parts: Learning Management System (LMS), Learning Content Management System (LCMS) and the Improved Ganglia Agent (IGA). LMS is responsible for managing the learners’ basic personal information and studying records, LCMS is responsible for the management and storage of back-end learning contents, and IGA is responsible for the management network traffic, CPU load and hard disk capacity. With the three, the load of the back-end content server could be balanced, offering a flexible mechanism for the expansion of the server. Not only does the ubiquitous learning system architecture meet ADL’s (Advanced Distributed Learning) SCORM standard, with the one-to-many distribution system architecture that allows flexible expansion mechanism, the shortcomings of traditional one-to-one SCORM system architecture is effectively improved, allowing a flexible expansion mechanism for back-end content servers.