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

<p>In this paper, an English teaching cultivation evaluation model based on RBF neural network is designed to solve the problems of poor generalization ability, low evaluation accuracy, and correlation coefficient of the current teaching evaluation model. Before establishing the evaluation model, conditional information entropy is used to screen the evaluation indexes of the English teaching cultivation function, and six dimensions of core literacy and five dimensions of thinking ability are selected as evaluation indexes. A new relative merit matrix is constructed under the constraint of relative merit by using the screened conditional attributes. Selection, crossover, and mutation operations are used in the RBF neural network to select the optimal parameters through the introduction of the genetic algorithm. Finally, the assessment data of students after project-based English teaching are analyzed for values and nurturing functions using the evaluation model. According to the findings, project-based English teaching led to the highest average score of 29.15 for students’ values compared to the dimensions of interest, ability, and personality. In terms of the six dimensions of core literacy and the five dimensions of thinking ability, the score difference between the experimental class and the control class is more than 1.2 points, and the Sig value of each dimension is less than 0.05, which indicates that English teaching based on Project-Based Learning promotes students’ values, core literacy and thinking ability.</p>
</abstract>

In this paper, an English teaching cultivation evaluation model based on RBF neural network is designed to solve the problems of poor generalization ability, low evaluation accuracy, and correlation coefficient of the current teaching evaluation model. Before establishing the evaluation model, conditional information entropy is used to screen the evaluation indexes of the English teaching cultivation function, and six dimensions of core literacy and five dimensions of thinking ability are selected as evaluation indexes. A new relative merit matrix is constructed under the constraint of relative merit by using the screened conditional attributes. Selection, crossover, and mutation operations are used in the RBF neural network to select the optimal parameters through the introduction of the genetic algorithm. Finally, the assessment data of students after project-based English teaching are analyzed for values and nurturing functions using the evaluation model. According to the findings, project-based English teaching led to the highest average score of 29.15 for students’ values compared to the dimensions of interest, ability, and personality. In terms of the six dimensions of core literacy and the five dimensions of thinking ability, the score difference between the experimental class and the control class is more than 1.2 points, and the Sig value of each dimension is less than 0.05, which indicates that English teaching based on Project-Based Learning promotes students’ values, core literacy and thinking ability.

An Analysis of the Values of Project-Based Learning in English Language Teaching and the Cultivating Functions it Displays

Applied Mathematics and Nonlinear Sciences

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

In this paper, an English teaching cultivation evaluation model based on RBF neural network is designed to solve the problems of poor generalization ability,...

An Analysis of the Values of Project-Based Learning in English Language Teaching and the Cultivating Functions it Displays

Publicado en línea: 31 ene 2024

Páginas: -

Recibido: 26 dic 2023

Aceptado: 01 ene 2024

DOI: https://doi.org/10.2478/amns-2024-0308

Palabras clave
RBF neural network, Conditional information entropy, Relative meritocracy, Project-based teaching, Genetic algorithm

© 2024 Liping Zhang, published by Sciendo

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

An Analysis of the Values of Project-Based Learning in English Language Teaching and the Cultivating Functions it Displays

Publicado en línea: 31 ene 2024

Páginas: -

Recibido: 26 dic 2023

Aceptado: 01 ene 2024

DOI: https://doi.org/10.2478/amns-2024-0308

Palabras claveRBF neural network, Conditional information entropy, Relative meritocracy, Project-based teaching, Genetic algorithm

© 2024 Liping Zhang, published by Sciendo

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

Palabras clave
RBF neural network, Conditional information entropy, Relative meritocracy, Project-based teaching, Genetic algorithm