<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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 <italic>E</italic><sub>2</sub> = [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.</p>
</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.

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

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

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...

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

Data publikacji: 22 maj 2024

Zakres stron: -

Otrzymano: 07 lut 2024

Przyjęty: 20 kwi 2024

DOI: https://doi.org/10.2478/amns-2024-1155

Słowa kluczowe
Variable weighting, Apriori, Hierarchical analysis, Structural equation modeling

© 2024 Ting Zhu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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

Data publikacji: 22 maj 2024

Zakres stron: -

Otrzymano: 07 lut 2024

Przyjęty: 20 kwi 2024

DOI: https://doi.org/10.2478/amns-2024-1155

Słowa kluczoweVariable weighting, Apriori, Hierarchical analysis, Structural equation modeling

© 2024 Ting Zhu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Variable weighting, Apriori, Hierarchical analysis, Structural equation modeling