Decision Tree Algorithm in Computer Aided English Teaching Scoring System

With the continuous improvement of the information management level of colleges and universities, more and more evaluation information is obtained through the online teaching evaluation system. The evaluation data and other college databases form a large database with rich information. Faced with these sources, university administrators not only pay attention to the evaluation results, but also pay attention to other information hidden behind the evaluation results. This article aims to study your application in the English computer-assisted scoring system based on the decision tree algorithm. Use ID3 algorithm to extract and analyze scoring data, export scoring data for judgment, create decision tree scoring rules to predict scoring levels, and analyze many related factors that affect scoring. In the analysis result, the absolute correctness rate of the decision tree under Example 50 is 88%, indicating that the customization effect is very good. It may be very interesting to explain the relationship between the many factors that affect English learning. It can not only help students understand the learning situation in the English classroom, but also help English teachers solve the problems in English teaching in a targeted manner, thereby improving the learning quality of English teachers and students' enthusiasm for learning English.