Educational Practice Based on the Integration of Support Vector Machines and English Curricula

Abstract

At present, IT (Information Technology) with computer network as its core has begun to integrate into CET (College English Teaching) practice, which has brought unprecedented influence on ELT (English Language Teaching). This paper adopts the strategy of active learning to build SVM, overcomes the shortcomings of typical SVM, and comprehensively considers various actual situations to build an assessment model of college English classroom instructional quality. The experimental results show that the classification accuracy of this algorithm can reach 96.21% on Zoo data set and 94.36% on Iris data set. This study is of great theoretical and practical value for improving the level of college English classroom teaching in the IT ecological environment.