Emotion prediction student module based on CVS-Emotional Agent for ATS platform

An affective tutoring system (ATS) is a software process with decision capabilities focused on student´s training and adapted to student´s skills and needs. Generally, ATS systems have the following components: a pedagogical module, a domain module, a dialog module and a student module. The student module tries to predict features about student´s behavior like reactions, emotions, etc. In this research we aimed to design an emotion prediction student module based on a new approach of an emotional agent. This agent is named Control-Value Simplified Emotional Agent (CVSEA) and is based on the Theory of Control-Value in Psychology.