Samuel Alexander

An Affect-sensitive Intelligent Tutor: Adapting to Student Emotions Based on Human Empathy Samuel Alexander

One of the established strengths of human tutors is their ability to recognise and adapt to the emotions of students. This is a skill that has traditionally been lacking from Intelligent Tutoring Systems (ITSs); despite their ability to intelligently model and adapt to aspects of the student?s cognitive state, ITSs are generally completely unable to detect or adapt to aspects of the student?s affective state. In response to this shortcoming, this book explores the exciting development of an emotion-sensitive ITS. With the empathy of effective human tutors as our blueprint, we investigate how an artificial tutor should adapt to the affective state of students. To inform the tutor?s adaptation to student affect, a novel method for student modelling and emotion-sensitive tutoring strategies has been developed using a fuzzy, case-based reasoning approach. As a validation of the feasibility of an emotion-sensitive tutoring system, we implement and test our method in an Affective Tutoring System (ATS) for counting and addition, Easy with Eve, featuring an empathetic animated pedagogical agent, Eve.