An Evaluation Method of English Teaching Based on Machine Learning

The evaluation of English teaching is becoming increasingly popular. An English teaching evaluation approach based on machine learning is developed in order to improve the accuracy of the English teaching evaluation and reduce the inaccuracy of the English teaching evaluation. Firstly, the specific meaning of the English classroom teaching evaluation is analyzed, the selection principle of the English classroom teaching evaluation index is designed, and the selection of the English teaching evaluation index is completed. Second, the machine learning technology is examined, and the analytic hierarchy process is used to produce the judgment of the English teaching assessment index. Then, using the principal component analysis, calculate the eigenvalues and eigenvectors of the evaluation indicators to determine the contribution of the English teaching quality assessment indicators. Finally, create the English teaching evaluation weight calculation model using the machine learning approach, and acquire the English teaching evaluation’s complete results using the fuzzy evaluation method. The experimental results show that when the number of iterations is 60, the normalized mean square error of the effectiveness of the method is 0.03, and when the number of tests is 30, the effectiveness of the method is 0.99; this shows that the method can improve the effectiveness of the English teaching evaluation. It can effectively reduce the error of the English teaching evaluation.