Evaluating the Effectiveness of the Practical and Applied Integration Teaching System of College English Based on Decision Tree and Rule Association Analysis

Abstract

Abstract In this paper, the basic framework of data mining is first proposed, and the data mining model based on the ID3 algorithm decision tree is constructed by analyzing the information gain of the attributes to divide each subset recursively, and the model is utilized to mine the data related to the teaching of practical application of English in the university effectively. Then, the attributes of support, confidence, and interest from the Apriori rule association algorithm are utilized to measure students’ evaluation of English teaching. Finally, the applicability of this paper’s algorithm was evaluated by indicators such as classification accuracy and computing speed, and the effectiveness of the English practical application integrated teaching system was verified in terms of the dimensions of students’ English literacy, learning interest, and classroom problems. The results show that the mean values of students’ English basic knowledge, English application ability, English core skills, and English awareness attitude are 4.02, 4.15, 4.06, and 3.99, respectively, and the students’ learning interest has been improved by at least 50%, indicating that the teaching effect is good.