Online education has developed rapidly due to its irreplaceable convenience. Under the severe circumstances caused by COVID-\n19 recently, many schools around the world have delayed opening and adopted online education as one of the main teaching\nmethods. However, the efficiency of online classes has long been questioned. Compared with traditional face-to-face classes, there\nis a lack of direct, timely, and effective communication and feedback between teachers and students in the online courses. Previous\nstudies have shown that there is a close and stable relationship between a personâ??s facial expressions and emotions generally. From\nthe perspective of computer simulation, a framework combining a face expression recognition (FER) algorithm with online\ncourses platforms is proposed in this work. The cameras in the devices are used to collect studentsâ?? face images, and the facial\nexpressions are analyzed and classified into 8 kinds of emotions by the FER algorithm. An online course containing 27 students\nconducted on Tencent Meeting is used to test the proposed method, and the result proved that this method performs robustly in\ndifferent environments. This framework can also be applied to other similar scenarios such as online meetings.
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