A Constructive and Empirical Study of Individualized Teaching Quality Evaluation for College English Teachers

Abstract

With the rapid development of society and the rapid change of software technology, the original teaching content and teaching mode of college English can no longer meet the learning needs of college students, so how to improve the quality of personalized teaching in the classroom of college English teachers is of great significance to improve the teaching level and other aspects. The article uses the idea of variable power to obtain personalized features, and through the Apriori algorithm, through data mining, so that students can choose courses suitable for themselves while using hierarchical analysis to evaluate and analyze the personalized teaching of English classroom in a university, in addition, using structural equation model to seek for factors affecting the personalized teaching of college English, and then improve the quality of English teaching. After normalization, we get E2 = [0.305 0.463 0.166 0.069], which means that the students’ comprehensive judgment of the personalized teaching quality assessment system of English teachers in the university is good. Finally, through the construction of structural equation modeling, the correlation coefficients between “teaching responsibility,” “teaching level,” and “teaching method” are all above 0.9. Their C.R. values are all greater than 1.96, indicating that the students have good judgment on the personalized teaching quality assessment system of the English teachers in the school. Because the C.R. values are all above 1,96, the correlation between the three factors and teaching quality is more significant.

Keywords

• variable weighting
• apriori
• hierarchical analysis
• structural equation modeling
• 97p10