Teaching Quality Evaluation System for College Teachers Based on Artificial Intelligence Facial Expression Recognition Technology

Abstract

Artificial intelligence is gradually entering the field of education, and evaluating and improving teachers' classroom performance has become an important content in the education industry. To evaluating teachers' teaching quality scientifically and objectively is also an important foundation in the field of education, with reference to long way of evaluation, such as questionnaire survey, classroom observation and other solutions are empirical, not comprehensive, such as defects, to a large extent affect the authenticity of the teacher's teaching quality evaluation, for the improvement of teaching quality also cannot provide effective data support. However, the development of information science, psychology and other disciplines has brought new solutions to this problem, and the use of the data of facial expressions collected in class to study the teaching situation has become a way to be considered. In the existing intelligent monitoring equipment design of classroom management system, based on the use of artificial intelligence technology of face detection and face recognition to automatic tracking and analyzing the change of the mood and behavior of students in the process of teaching, through to the students of class status (for example: confusion, curiosity, exclusion, drowsiness, understanding, etc.) of the intelligent analysis, establish a more objective, scientific and precision level of teacher's teaching quality evaluation system, so that the teaching mode of evaluation, monitoring and improvement to provide corresponding reference.