Adaptive Content Delivery System for Ubiquitous Learning

Abstract Most of learning contents, designed for desktop computers and high-speed network connections today, are not suitable for handheld devices with limited resources and computing capabilities. Also, some delivered materials, irrelevant to learners ’ preferences or contextual environment, may slow down learning efficiency, and increase learners ’ communication costs and channel burdens. In order to provide adaptive contents based on device capabilities and learner’s context awareness, this paper proposes a functional architecture for ubiquitous learning. The architecture consists of four engines: learner engine, detector engine, adaptation engine, and transcoding engine. After contextual data and learners ’ preferences are separately identified by detector engine and learner engine, adapted contents created by transcoding engine can be dispensed to learners by adaptation engine. Finally, the adaptive content delivery system is experimentally evaluated on standard document learning contents