Systematic Design and Effectiveness Enhancement of English Teaching in Colleges and Universities Combining Decision Tree Modeling

Abstract

Abstract In the process of teaching English in colleges and universities, the variability of students’ performance and the factors affecting this variability have been considered by teachers and students. In this paper, data mining is applied to the systematic design of English teaching in colleges and universities, and the framework of the English teaching system in colleges and universities is constructed by improving the decision tree algorithm. The framework encompasses seven modules, from the login module to the personalized analysis based on the decision tree, which includes the entire process of English learning in colleges and universities. For the model in this paper, the total error rate of the training samples is 2.14, while the overall error rate of the test samples is 1.9. These errors are less than 10%, with high accuracy and stability. In the control test using the teaching system model in this paper, the total score of the experimental class is 5.21 points higher than that of the control class. The listening and speaking scores of the experimental class are significantly improved relative to that of the control class, and the difference between the two scores reaches more than 5. The experimental results show that the college English teaching model constructed in this paper has a significant effect on improving English performance.