A Model of Personalized Context Aware E-learning Based on Psychological Experience

Abstract

The use of context-aware approach in e-learning system has brought a new passion for users as an alternative to learning. It can provide personalized and adaptive learning patterns that can tailor to the needs, the circumstances and the behavior of users. Along with the continued development pervasive and ubiquitous computing, there are several studies related to this model. However, the existing models developed still focus on a wide variety of contexts, such as explicit contexts and context related to the physical environment of learning. Additionally, the developments of the current models by involving psychological condition of the learner taken into account are still limited. In fact, this condition can influence the learning engagement of learners. This research proposed a model of context aware e-learning that personalizing e-learning according to psychological state of the learners. The psychological experience is based on the theory of flow consisting of anxiety, boredom, and optimal condition measured naturally when users are interacting with e-learning. Furthermore, it becomes one of the strengths of this research. Psychological experiences are measured after the learner interacting with the e-learning. The data are obtained from learner behavior saved in the server log.