Exploring the Reform of English Informatization Teaching and Micro-Class Teaching Mode in College Based on SVM Model in the Background of Big Data

Abstract

This research introduces the SVM model to examine the reform direction in order to increase the effectiveness of English informatics education reform in colleges and universities. Firstly, the optimal hyperplane is defined in the process of constructing support vector machines, and LS-SVM and BT-SVM algorithms are introduced. The kernel function of SVM is sorted out to determine its operation conditions, and thus the BT-SVM algorithm flow is obtained to facilitate the full-text algorithm work. The algorithm model simulation experiments are carried out to confirm the method's viability after outlining the technological methods. In order to further investigate the microlearning and informatization of English instruction in colleges and universities, the simulation experiment findings are employed. The results show that the average score of students' evaluation of teaching content is 90.8, teaching method is 88.5, teaching attitude is 85.7, and the average score of teaching result is 84.5, which is in a satisfactory state in general. The BT-SVM algorithm's accuracy rate in teaching processing is 98.72%, which contributes to increasing the effectiveness of the entire teaching evaluation process. Thus, it is clear that both the computation of teaching evaluation indexes and the efficiency of teaching processing are accurately and efficiently handled by the method presented in this study.