Research on Intelligent Evaluation Model of Classroom Teaching Based on Machine Learning Algorithm

This paper proposes an intelligent evaluation model of classroom teaching based on SVM algorithm, aiming to improve the automation, objectivity and accuracy of the evaluation process. First, this paper designs an intelligent model framework suitable for classroom teaching evaluation, and combines machine learning technology to collect, extract features and analyze teaching data. By using SVM, the model can be used to evaluate the effectiveness of classroom instruction. In the course of the experiment, people used the multi-dimension teaching data, including the interaction in class, the homework, the test results, and so on. The experimental results show that the proposed model can effectively evaluate the teaching quality of teachers and the learning status of students. The accuracy of model prediction reached 89.5%, which is 15% higher than that of traditional manual evaluation methods. In addition, the evaluation model based on SVM shows strong robustness and adaptability in different teaching scenarios, and can quickly adapt to changes in the teaching environment.