Incorporating an Affective Model to an Intelligent Tutor for Mobile Robotics

Emotions have been identified as important players in motivation, and motivation is very important for learning. When a tutor recognizes the affective state of the student and responds accordingly, the tutor may be able to motivate students and improve the learning process. We propose a general affective behavior model which integrates information from the student's pedagogical state, affective state, and the tutorial situation, to decide the best tutorial action, considering the tutor preferences from a pedagogical and affective point of view. Our proposal is based on emotions models, personality theories and teachers' expertise. The affective model is implemented as a dynamic decision network, with utility measures on both learning and motivation, and is being incorporated to an intelligent tutor within a virtual laboratory for learning mobile robotics. This paper presents preliminary results in the construction of the affective behavior model.