Learning Resource Adaptation and Delivery Framework for Mobile Learning

Abstract

With the rapid development of wireless networks and mobile devices, mobile learning has got more and more attention. However, most of current learning resources (LR) were designed with desktop computers and high-speed network connections. Moreover, for different user preferences in mobile learning environment, not all of the data are relevant and critical to the learning process. It is a challenge to deliver such learning resources to various devices with limited capability over low-speed wireless network while ensuring higher synthetically quality of learning resource. To solve above problem, in this paper we proposed a Learning Resource Adaptation and Delivery Framework to adapt learning resources to various learning environments. It consists of two layers: multimedia adaptation layer and learning object adaptation layer. In the multimedia adaptation layer, MPEG-21 Digital Item Adaptation (DIA) mechanism is incorporated to handle the adaptation of low-level multimedia contents contained in learning resources. In the learning object layer, the appropriate selection of learning objects is based on an extended Learning Object Model for mobile learning. With the introduction of an integrated quality mechanism filling the quality metrics gap between high-level learning objects and low-level multimedia objects, an adaptation decision algorithm is presented to ensure higher final adaptation quality of learning resources