Researching affective computing techniques for intelligent tutoring systems

Intelligent Tutoring is applied as a supportive tool in decision making, problem solving, knowledge receiving. Adding computer vision for affect recognition leads to the adaptation of tutor behavior not only to the cognitive level of a student but also to his emotional state that could improve quality of learning. In this paper the current research in the area of facial expression and gesture recognition in the context of intelligent tutoring is examined with the aim to facilitate educational society in building of affective intelligent tutoring systems.