Open AccessE-Learner's Academic Emotions Based on Facial Expressions : A Survey
Author(s) -
Snehal Rathi,
Arnav Sakhariya,
Jeet Shah,
Mohit Sanghvi
Publication year - 2020
Publication title -
international journal of scientific research in science, engineering and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-1990
pISSN - 2394-4099
DOI - 10.32628/ijsrset207467
Subject(s) - facial expression , action (physics) , face (sociological concept) , domain (mathematical analysis) , psychology , emotion detection , computer science , mathematics education , cognitive psychology , human–computer interaction , artificial intelligence , emotion recognition , mathematics , mathematical analysis , physics , quantum mechanics , social science , sociology
This paper presents different technologies and framework used for academic emotion detection using facial recognition in E-Learning. E-Learning is growing day by day for various reasons like distance learning and user is able to do it at anytime and anywhere. But E-Learning lacks in real time feedback from the students to teachers and vice-versa. Academic Emotion plays an important role on detecting whether the students have understood the topic or not. In face to face learning, a skilled teacher achieves affective domain goals by interacting with the students and asking them questions. But in online learning student and teacher are apart so if system itself finds the emotion and take the action accordingly, is really very helpful to teacher and student both. There are various ways like sensors, facial expressions, log usage are used by many scientists to achieve this. We have researched and read many papers about various frameworks used and found that academic emotions play a vital role and also makes big difference in learning if it is properly analyzed and suitable action is taken. A model for the same purpose has been proposed here which will detect emotion and generate feedback accordingly.