Context-Aware Mobile Learning Model for Traveler

Currently, the emerging of ubiquitous computing has provided a significant opportunity for using a mobile technology as a learning medium. This situation has led many researchers to investigate the potential of adaptive learning through mobile learning. However, there are limited researchers present a model of adaptive mobile learning for learners who are always traveling. This paper proposed a context-aware mobile learning model for learners who are traveling frequently by considering several challenges in moving situation. This model aims to provide alternative learning by providing educational resources as well as the location presenting the nearest educational resources tailored to conditions and situations context of learners. Learning style (video, audio, text, animation), learning preference (case-study, conceptual, simulation) and preferred time are selected as static context parameter and used as an adaptive filter to presenting learning materials through mobile. On the other hand, location and environment level (connectivity, noise, illumination) are chosen as the dynamic context to provide the position of the nearest learning resources such as libraries and classmates for collaboration. As the result of this model produced a wireframe design of context-aware mobile learning for the traveler, by providing and recommending the learning materials, learning approach, as well as the nearest source of knowledge according to the conditions and situations of learners. In conclusion, this model can provide alternative guidelines for developers who interested implementing context-aware mobile learning, especially for the frequent traveling learners to keep learning and following the learning process wherever located.