S.C. Satapathy et al. (Eds.): Proceedings of the InConINDIA 2012, AISC 132, pp. 613–622. springerlink.com © Springer-Verlag Berlin Heidelberg 201 Design and Implementation of Affective E-Learning Strategy Based on Facial Emotion Recognition Arindam Ray 1 and Amlan Chakrabarti 2 1 Awadh Centre of Education Guru Gobind Singh Indraprastha University, New Delhi, India arindamray_2007@yahoo.co.in 2 A K Choudhury School of Information Technology University of Calcutta Kolkata, West Bengal, India acakcs@caluniv.ac.in Abstract. E Learning is emerging as a heavily learner-centric, emphasizing pervasive and personalized learning technology. Affective learning outcomes in a nutshell, involve attitudes, motivation, and values. In the same tune we can also define the affective E-learning, as a strategy, which implies recognition of learner’s emotion and selection of pedagogy in a best possible way. For the best delivery, learner’s affective state needs to be identified where the key solution is emotion recognition. Our work focuses on emotion detection using biophysical signals which further explores the evolution of emotion during learning process, to generate a feedback that can be used to improve learning experiences. Our research is deeply focused into the aspects of operative content delivery mechanism by using physiological facial signals for the detection of learner’s emotion but without detecting the face. In this paper we propose a key technique to detect learner’s facial expression, based on neural network classification and selection of appropriate learning style, which shows reasonable results in comparison with the other existing systems. The result manifests that the recognizer system is effective. 1 Introduction A fundamental tenet of this design is that one method does not fit to all learners. Different pedagogy has to be chosen for different learner. In E-Learning portal the method of teaching-learning is unidirectional which implies simultaneous communication can’t happen. But in the face to face interactive session, it happens. Teacher’s experience plays an important role and hence an E-Learning portal needs such platform for emotion sharing between the leaner and the teacher. Learner’s emotion first reflects on the face and hence facial emotion recognition [1] is preferred to get the affective state of learner. The proposed model can recognize learners’ emotion to identify the affective state. In this paper we propose a technique to detect learner’s facial expression using SVM (Support Vector Machine) and also selection of the course based on neural network. As per the psychological theory that human emotions –could be classified into six typical emotions [2] viz. ‘‘happiness’’, 2