Application of context-aware and personalized recommendation to implement an adaptive ubiquitous learning system

Advances in wireless networking, mobile broadband Internet access technology as well as the rapid development of ubiquitous computing means e-learning is no longer limited to certain settings. A ubiquitous learning (u-learning) system must however not only provide the learner with learning resources at any time and any place. However, it must also actively provide the learner with the appropriate learning assistance for their context to help him or her complete their e-learning activity. In the traditional e-learning environment, the lack of immediate learning assistance, the limitations of the screen interface or inconvenient operation means the learner is unable to receive learning resources in a timely manner and incorporate them based on the actual context into the learner's learning activities. The result is impaired learning efficiency. Though developments in technology have overcome the constraints on learning space, an inability to appropriately exploit the technology may make it an obstacle to learning instead. When integrating the relevant information technology to develop a u-learning environment, it is therefore necessary to consider the personalization requirements of the learner to ensure that the technology achieves its intended result. This study therefore sought to apply context aware technology and recommendation algorithms to develop a u-learning system to help lifelong learning learners realize personalized learning goals in a context aware manner and improve the learner's learning effectiveness. (C) 2011 Elsevier Ltd. All rights reserved.