Facilitating a personalized learning environment through learning analytics on mobile devices

Abstract

Many learning analytics techniques to capture the learner's real-time responses are computationally intensive for running on mobile devices. In this paper, we propose a personalized learning platform named the PETAL facilitated by an efficient learning analytics application to detect learners' level of attentiveness and the proximity of their eyes to mobile devices and then alert learners to be more attentive or to keep acceptable distance from a device. Data privacy is guaranteed by password-protected accounts. Being the first attempt, a prototype of our PETAL application is carefully built and evaluated on Android tablets, with many promising directions for future extensions. © 2014 IEEE.