Eye Movement Analysis and Usability Assessment on Affective Computing Combined with Intelligent Tutoring System

Abstract

Education is the key to achieving sustainable development goals in the future, and quality education is the basis for improving the quality of human life and achieving sustainable development. In addition to quality education, emotions are an important factor to knowledge acquisition and skill training. Affective computing makes computers more humane and intelligent, and good emotional performance can create successful learning. In this study, affective computing is combined with an intelligent tutoring system to achieve relevant and effective learning results through affective intelligent learning. The system aims to change negative emotions into positive ones of learning to improve students’ interest in learning. With a total of 30 participants, this study adopts quantitative research design to explore the learning situations. We adopt the System Usability Scale (SUS) to evaluate overall availability of the system and use the Scan Path to explore if the subject stays longer in learning the course. This study found that both availability and satisfaction of affective tutoring system are high. The emotional feedback mechanism of the system can help users in transforming negative emotions into positive ones. In addition, the system is able to increase the learning duration the user spends on learning the course as well.