Emotion Recognition of Students Based on Facial Expressions in Online Education Based on the Perspective of Computer Simulation

Abstract

Online education has developed rapidly due to its irreplaceable convenience. Under the severe circumstances caused by COVID-19 recently, many schools around the world have delayed opening and adopted online education as one of the main teaching methods. However, the efficiency of online classes has long been questioned. Compared with traditional face-to-face classes, there is a lack of direct, timely, and effective communication and feedback between teachers and students in the online courses. Previous studies have shown that there is a close and stable relationship between a person’s facial expressions and emotions generally. From the perspective of computer simulation, a framework combining a face expression recognition (FER) algorithm with online courses platforms is proposed in this work. The cameras in the devices are used to collect students’ face images, and the facial expressions are analyzed and classified into 8 kinds of emotions by the FER algorithm. An online course containing 27 students conducted on Tencent Meeting is used to test the proposed method, and the result proved that this method performs robustly in different environments. This framework can also be applied to other similar scenarios such as online meetings.

Awareness and Readiness of Malaysian University Students for Emotion Recognition System

“…Delivery of classes using online platform has been popular since the Covid19. In [31], facial expression based ERS is used to measure the students' reaction towards the end of an online meeting to overcome the lack of communication between the students and instructor.…”

Facial Emotion Recognition with Sparse Coding Descriptor

“…Automatic Face Analysis (AFA) system was developed by (Tian, et (Yang et al, 2017) proposed a learning emotion recognition model consisting of feature extraction, subset feature and emotion classifier. In the work of Wang et al (2020), the framework of FER algorithm was combined with online courses platforms using computer simulation to recognise student's emotion in an online education. Shuaibu et al (2018) fused PCA and LBP with sparse coding to achieved FER using the linear kernel multi-class support vector machine (LSVM) classifier.…”

“…he classification of human facial expressions which include surprise, happiness, anger, contempt, disgust, fear is a process known as facial expression recognition (FER) (Shuaibu, et al 2018). Facial expression is used by humans irrespective of their nationality, sex or race to express their states of emotion and what they intent (Wang, et al 2020). Despite the FER process, recognition of the face remains a difficult task due to variations of the face that are caused by aging, varying illumination, pose etc.…”

Faculty Members’ Attitudes and Practices: How They Responded to Forced Adoption of Distance Education?

“…However, some studies address problems in the use of distance education for various reasons. For instance, W. Wang et al (2020) and Hodges et al (2020) confirmed the existence of a physical gap between the teacher and the learners due to the application of distance education, which had a role in limiting the building of relationships between these two basic elements in the educational process (Cakula et al, 2016). Some studies noted that distance education would not yield completely positive results without a very high degree of self-discipline (Al-Abdullatif et al, 2020;Augner et al, 2012;Lee et al, 2016).…”