A Framework for Affective Intelligent Tutoring Systems

In social context, emotions play a prominent role in verbal and non-verbal communication. With their multi-modal perception, the aptitude of an interlocutor in identifying them, through a diversity of behaviors such as face movements, gestures, speech, is a fundamental aspect as judgment and decision making are influenced by mood, feelings, which facilitates human adaptation and social integration. In a cognitive activity such as learning, communication (between learners and tutors) is one of the fundamental issues, and its quality may influence the learning. Therefore, learning process implies cognitive aspects as well as socio-emotional aspects: in real world, teaching also implies to observe the student´s affective behavior in order to detect affective responses which can express interest, excitation, confusion, etc. and suggest a review of the actual interaction flow. This paper presents an intelligent tutoring systems (ITS) architecture equipped with emotional management capabilities which make it possible the capture of student emotions during learning and affective response to learners´ actions. The result system called AITS (affective tutoring system) could efficiently adapt content planning, learning/tutoring strategies and even tutoring dialogues based on affective and cognitive data