Exploring Emotion in an E-learning System Using Eye Tracking

Abstract

E-learning is the computer and network-enabled transfer of skills and knowledge. In e-learning systems, emotions are critical for learners to create positive contexts for optimal learning. In particular, increasing learner motivation by stimulating their interest is crucial. 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 learners' emotions groups: interest and boredom groups. We designed and implemented a prototype and experimentally evaluated it.