With fast development of technology, e-learning becomes one of the most popular education models. But this type of education is not sufficiently dynamic because the system only plays the role of a simple media for transferring knowledge. While psychological studies show that personal characteristics like emotion and personal type play an important role in learning. 

In order to increase efficiency of education, these factors should be considered in elearning. In this study, we identify user emotion from touching behavior on tablets or smartphones. Besides the ability to detect emotion, online education system should be able to improve negative emotions of users. This is not as easy as showing a few images or playing a music but it is a professional task which is different for different users. One of the important personal characteristics of human is personality type. In this study touching patterns of the user is used to specify the user’s emotion. Then the negative emotions is improved considering of their personal type. Statistical results show that we detect boredom, frustration and anxiety with 90%, 79% and 65% Precision and also improve the user efficiency significantly with our proposed method. Statistical sample includes 51 men and women from Razi University of Kermanshah between 2016-2017.

Publication

• Mohammadi, A.,Kazemifard, M., and Jahangir, K. (2017). “Emotion detection based on user interaction with touch screen in ELearning”, In Proceedings of 2nd International Conference on Knowledge Based Research in Computer Engineering Information Technology, September, 2017, Tehran, Iran, pp. 1-6. (pdf)

• Mohammadi, A. and Kazemifard, M., and Karami, J., (2019). “Improving Online Education Systems Based on the Emotions and Personal Type”, The International Journal of E-Learning and Educational Technologies in the Digital Media (IJEETDM), 5 (2), pp: 36-47. (pdf)