English classroom teaching quality assessment based on machine learning

Abstract

Background

This study uses machine learning technology to evaluate the quality of English classroom teaching, and discusses how the data model based on the characteristics of students and teachers reflects the teaching effect.

Objective

Analyzing the data of 500 students and 50 teachers, it is found that the characteristics of students’ grade, class participation, and assignment submission have an impact on the quality of teaching.

Methods

The prediction model is constructed, and the model is optimized and verified.

Results

The results show that the machine learning model can accurately predict the results of teaching quality evaluation, and improve the objectivity and scientificity of teaching evaluation. In model evaluation, the prediction error of training set and test set is small, and the model is robust and generalization ability in prediction.

Conclusions

The problems and challenges in data collection are also discussed, and suggestions for improvement are put forward. Machine learning provides a new method for teaching quality assessment, has high practical value, and provides a scientific basis for education administrators and teachers to make decisions.