During classes, students’ mastery of knowledge points is reflected in their facial expressions. Teachers usually judge their degrees of understanding through the expressions and then adjust the teaching schedule. However, at least 30 students are in a class, and it is impossible for the teachers to take care of each student at all times in a classroom. As a result, teachers can not fully understand each student’s mastery of knowledge points, thus affecting the quality of teaching. To solve this problem, this study introduces a classroom teaching feedback system based on facial expression recognition, which can analyze the facial expression of each student in the classroom and demonstrate their mastery of knowledge points from the expressions. On that basis, it can help teachers understand the real-time learning effect of each student in the classroom, thereby improving teaching quality.