Recognition of Student Emotions in an Online Education System

Online education system was developed due to the Covid-19 pandemic. The core idea of this paper is to map the connection between teaching practices to student learning in an online environment. Face to face evaluation techniques are fairly quick and easy for formative assessments to check student understanding in existent environment. Prevailing studies illustrate that a person's facial expressions and emotions are closely related. In order to make the teaching-learning process more effective, teachers usually collect day to day feedback from the students. This feedback can be used to improve teaching skills and make the process more interactive. In a virtual learning mode, there is a need to identify and understand the emotions of people. Constructive information can be extracted from online platforms using facial recognition algorithms. An online course connected with students is used for examination; the results have shown that this technique performs strongly.