Exploring Emotion in an E-learning System Using Eye Tracking

Abstract

Since appropriate emotions are a sign of mental health, learners who have good mental health learn more successfully. In e-learning systems, emotions are critical for learners to create positive contexts for optimal learning. To data, however, few e-learning systems have derived emotions from eye tracking data. With eye tracking equipment, we recorded the eye movements of learners and calculated their eye metric indexes, which we focused on to explore their relationship to two learner emotions: interest and boredom. We designed and implemented a prototype and experimentally evaluated it.