A study of student performance under English teaching using a decision tree algorithm

With the popularity of English, more and more attention has been paid to students' English learning. In order to understand student learning and make accurate predictions about student performance, this paper analyzed student performance under English teaching by using a decision tree algorithm, i.e. the C4.5 algorithm. The calculation process of the algorithm was simplified by the Taylor series, and an example was analyzed. The results showed that the running time of the improved C4.5 algorithm was improved by 22.86% compared with the C4.5 algorithm, the precision rate was above 75%, the recall rate was above 85%, and the F1-measure value was above 80%. The experimental results verified the effectiveness of the improved C4.5 method in studying student achievement. This work is beneficial to the further optimization of decision tree algorithms and provides some reference for the application of intelligent algorithms in the field of education.