Obtaining Teachers' Expertise to Refine an Affective Model in an Intelligent Tutor for Learning Robotics

Abstract

Emotions are a ubiquitous component of motivation and learning; therefore it is desirable for intelligent tutors the incorporation of affective models. We developed an affective behavior model for intelligent tutoring systems with base on intuition, literature and teachers’ expertise. The model selects a tutorial action based on the knowledge and affective state of the student. We conducted a study to ask teachers how they deal with affective aspects when they are teaching; and we used the results to refine our model. In the study the teachers saw a video of students interacting with the learning environment, they rated the affective and knowledge state of the students and selected the tutor actions according with the student state. The tutorial action is given via an animated pedagogical agent. Nine teachers from different scholar levels participated in the study. In this paper, we present the teachers study to refine the affective behavior model.