*1.2. Research Purpose*

With the advancement of technology, diversified learning modes can create richer teaching materials and learning methods. Based on the aforementioned research background and motivation, this study aimed to combine affective computing with intelligent tutoring system to understand the user's learning emotions, convert the user's negative emotions into positive ones and improve his/her interest of learning. Moreover, we used an eye tracker to perform eye movement analysis and understand if the user is able to increase the course learning duration by using the affective tutoring system. Based on the research background and motivation as well as the above discussions, the purpose of this study was set as follows: 1. Exploring the usability assessment of the affective tutoring system. 2. Understanding the fixation duration when using the affective tutoring system through eye movement analysis. 3. Understanding if the user is able to increase the course learning duration by using the affective tutoring system through eye movement analysis. Eye movement analysis was conducted to explore if the affective tutoring system can improve learners' attention and increase the course learning duration. The study themes are as follows:


### **2. Literature Review**

### *2.1. Affective Computing*

Affective computing methods have been applied to many fields such as training and learning environments [11]. In learning environments, the most important emotions to be dealt with are those associated with the teaching process (such as boredom, frustration, confusion, and engagement). Picard (1997) proposed four levels of affective computing: Recognize Emotion, Understand Emotion, Express Emotion and Emotion Intelligence. Affective Computing aims to detect signals caused by emotions and affections, such as language, physiological changes and body movements through various sensors. The computers will analyze these signals and make appropriate responses to current emotions. Emotion recognition can be detected by heartbeat, skin potential difference and facial emotion expression [12].
