A computational model of emotion and personality in e-learning environments

One of the currently most important discussions in artificial intelligence is modeling personality and emotion in artificial intelligence, chiefly in Human-Computer-Interaction (HCI). The purpose of this research is designing a general model that identifies a user’s affective status based on user’s personality and emotion. The proposed model is composed of two main modules: personality and emotion modules. The personality module detects personality type of a user based on two approaches: determining personality through users’ actions in a system and using sequential behavioral pattern mining to determine personality. In the emotion module, we propose a computational model to calculate a user’s desirability based on personality in e-learning environments. The desirability of an event is one of the most important factors in determining a user’s emotions. The proposed model has been evaluated in simulated and real e-learning environments. The results show that the model formulates the relationship between personality and emotions with adequate accuracy.