An Adaptive E-Learning Environment Centred On Learner's Emotional Behaviour

Recent trends in Information and Communication Technology, Web based learning environment attract the learner for anywhere and anytime learning such as e-learning environment. Many research says that the learner's active listening duration is 15 to 20 minutes and research on e-learning mainly focusing to offer an adaptive e-learning content with respect to the learner's profile and knowledge. This paper, we are mainly focused, how to engage the student in e-learning for longer duration. To keep the learner, in active listening mood, we have to recognize the learner mood and offer the adaptive learning content with respect to their mood, knowledge in the domain, profile and Learner history feedback. We focused to reveal the learner's emotional behavior, we have taken Facial feature emotion extraction, body gesture, movement and EEG - Bio signal approach for emotion prediction. The result was analyzed and it shows that bio-signal accurately predicting the learner's emotion. Finally, we have used the EEG approach for predicting the learner's emotional behavior while learning.