Evaluation of Teaching Quality of English Courses in Comprehensive Universities under Multiple Indicators

Abstract

With the continuous development of internationalization and the task of cultivating graduates with high comprehensive quality for the society, the importance of English teaching in comprehensive universities has been increasing. In this paper, based on the analysis of the evaluation subjects of university English teaching quality, 16 evaluation indexes are constructed from five aspects: teaching content, teaching method, teaching process, teaching literacy, and teaching effect, and the Particle Swarm Optimization-Least Squares Support Vector Machine (PSO-LSSVM) algorithm is used to comprehensively evaluate the teaching quality, and finally English teaching in universities is selected as the object of empirical research. The research results show that PSO-LSSVM algorithm has high applicability in evaluating ECCU and can provide over reference for universities to improve teaching quality and develop reform programs. Due to the lack of training data, although the evaluation index system in this paper is scientific and feasible, it still needs to be further adjusted and optimized according to the specific practice situation.