Eye tracking system for enhanced learning experiences

Abstract

Nowadays, we are living in a world where information is readily available and being able to provide the learner with the best suited situations and environment for his/her learning experiences is of utmost importance. In most learning environments, information is basically available in the form of written text. According to the eye-tracking technology, eye movements, scanning patterns and pupil diameter are indicators of thought and mental processing involved during visual information extraction. Hence, learners can be supported and guided throughout their learning journey by the real-time information of the precise position of gaze and of pupil diameter. A proper interpretation and consequently an efficient monitoring or supervision of learners’ eye movements by different methods of eye tracking may lead to an enhanced learning process and experience. This research gives an insight of the various existing techniques that contribute to the improvement of the learning mechanism through proposing a real time monitoring system using image processing and eye detection techniques. To portray such a robust mechanism, a multipronged eye tracking approach has been envisioned. The system is deployed with a first identification of the user’s eyes followed by the detection of the iris and pupil movements of the latter. Subsequently, the information about the eyes and pupil movements were analysed and graphs were generated that helps in determining the interest and behaviour of the user. To evaluate the accuracy of the system, some user tests and various scenarios in different application domains have been performed by computing the tracking error rate and as a result it has been noticed that these tests yield to an acceptable efficiency rate and a True Acceptance Rate (TAR) of around 75 %. Moreover, the proposed system is a low cost system and can be compatible with any computer or laptop equipped with an ordinary web camera.