Description

Emotions are of great significance in education as in all areas of human life. Educational models currently integrate a variety of technologies and computer applications that seek to improve learning environments. With this objective, information technologies have increasingly adapted to assume the role of educational assistants that support the teacher, the students, and the areas enrolled in educational quality. In video established eye tracking methods, there are both mechanical and electrical based approaches existing. With the emerging spread of gaze tracking technology in the recent years and its significance in daily life routine, the data content acquired from the eye behaviour tracing turn into important. This work proposes the design of an emotion identification system, based on the recognition of eye gazes in the faces of students during the teaching process in a specific subject. The main objectives of our system is to predict the student emotion based on eye- gaze while listening the online class by using machine learning algorithm such as Random Forest. The emotions such as bores, frustrated, drowsy, confused and engaged effectively. Then experimental results shows that accuracy, and error rate

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