Implementation of Classroom Teaching Evaluation System Based on Artificial Intelligence

The intersection of artificial intelligence (AI) and education has emerged as a prominent subject in educational research. The advent of sophisticated computing technologies and the proliferation of intelligent applications have precipitated novel challenges for high vocational classroom teaching. This paper proposed an AI-driven system that efficiently implemented intelligent classroom teaching evaluation. The system's functionality encompasses the perception of dynamic changes in emotional information between teachers and students by collecting actual classroom data. The system consists of data collection, technical processing, application, and user layers from bottom to top. All classroom teaching behavior recognition models were trained using the You Only Look Once (YOLO) v8 algorithm. The evaluation results showed that the facial recognition rate of teachers and students in the classroom reached 97.1%, the recognition rate of five types of emotions reached 93.3%, and the recognition rate of drowsiness reached 99.1%. Therefore, the proposed system boosted the efficacy of classroom teaching evaluation to achieve trajectory tracking of teacher and student growth.