New Perspectives on Affect and Learning Technologies

Abstract

This chapter describes a fully automated affect-sensitive Intelligent Tutoring System (ITS) called the Affective AutoTutor. AutoTutor is an ITS that helps students learn topics in Newtonian physics, computer literacy, and critical thinking via natural language dialogues that simulate the dialogue patterns observed in human–human tutoring. AutoTutor uses state-of-the-art natural language understanding mechanisms to model learners’ cognitive states and plan its dialogue moves in a manner that is sensitive to these states. While the original AutoTutor is sensitive to learners’ cognitive states, the affect-sensitive tutor is responsive to their affective states as well. This Affective tutor automatically detects learners’ boredom, confusion, and frustration by monitoring conversational cues, gross body language, and facial features. The sensed affective states guide the tutor’s responses in a manner that helps learners regulate their negative emotions. The tutor also synthesizes affect via the verbal content of its responses and the facial expressions and speech of an embodied pedagogical agent. An experiment comparing the affect-sensitive and nonaffective tutors indicated that the affective tutor improved learning for low-domain knowledge learners, particularly at deeper levels of comprehension.