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.