Mood-Based on-Line Learning System

Many millennial learners are associated with massive open on-line courses for learning. This online learning to be more interactive and to substitute the teacher observation, it requires the augmentation of those humanly traits, to keep the learner active. This paper proposes such a sub-system to the online learning environments which performs necessary activities to bring the learner into pace of the course. From the reactions of learner while learning from the continuous capturing of face images, this system can analyze the emotions and initiate the necessary actions to continue the learning. The Emotional Back Propagation Neural Networks with successful PCA were used for training and Genetic Algorithm is used for optimizing the results. The system can automatically identify the facial expressions and initiates the counter actions to keep the learning successful.