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

<p>With the informatization of education, the traditional English teaching evaluation method is increasingly unable to meet the needs of cultivating talents in colleges and universities. In this paper, we constructed an informatized English teaching evaluation system using two modules: students’ classroom learning status evaluation and teachers’ teaching quality evaluation. Using informationized face detection and expression recognition technology, the evaluation axis of students’ classroom learning status is established as “students’ head-up rate - students’ expression - students’ concentration - classroom learning status”. The fuzzy comprehensive judgment model based on a genetic algorithm was established by constructing a judgment matrix and calculating the weights of teaching quality evaluation indexes using a hierarchical analysis method. The experimental and control groups analyzed the English teaching evaluation system’s application. Regarding English achievement, the post-experimental scores of the students in the experimental class were 8.57 points higher than those of the control class, with a highly significant difference (P&lt;0.01). In terms of student literacy, students in the experimental class showed significant improvement in four indicators, including learning motivation, learning situation and cognition, and their attitudes toward the quality of English teaching were in the range between satisfaction and comparative satisfaction, and the overall performance of the application practice of the English education evaluation system was good.</p>
</abstract>

With the informatization of education, the traditional English teaching evaluation method is increasingly unable to meet the needs of cultivating talents in colleges and universities. In this paper, we constructed an informatized English teaching evaluation system using two modules: students’ classroom learning status evaluation and teachers’ teaching quality evaluation. Using informationized face detection and expression recognition technology, the evaluation axis of students’ classroom learning status is established as “students’ head-up rate - students’ expression - students’ concentration - classroom learning status”. The fuzzy comprehensive judgment model based on a genetic algorithm was established by constructing a judgment matrix and calculating the weights of teaching quality evaluation indexes using a hierarchical analysis method. The experimental and control groups analyzed the English teaching evaluation system’s application. Regarding English achievement, the post-experimental scores of the students in the experimental class were 8.57 points higher than those of the control class, with a highly significant difference (P<0.01). In terms of student literacy, students in the experimental class showed significant improvement in four indicators, including learning motivation, learning situation and cognition, and their attitudes toward the quality of English teaching were in the range between satisfaction and comparative satisfaction, and the overall performance of the application practice of the English education evaluation system was good.

Exploring the Innovation of Informative English Teaching Evaluation in the Age of Mathematical Intelligence

Linyi Vocational University of Science and Technology

Applied Mathematics and Nonlinear Sciences

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

With the informatization of education, the traditional English teaching evaluation method is increasingly unable to meet the needs of cultivating talents in...

Exploring the Innovation of Informative English Teaching Evaluation in the Age of Mathematical Intelligence

Publicado en línea: 03 may 2024

Páginas: -

Recibido: 07 abr 2024

Aceptado: 16 abr 2024

DOI: https://doi.org/10.2478/amns-2024-0944

Palabras clave
English teaching evaluation, Face detection, Expression recognition, Hierarchical analysis, Fuzzy comprehensive judgment model, Genetic algorithm

© 2024 Lanna He et al., published by Sciendo

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

Exploring the Innovation of Informative English Teaching Evaluation in the Age of Mathematical Intelligence

Publicado en línea: 03 may 2024

Páginas: -

Recibido: 07 abr 2024

Aceptado: 16 abr 2024

DOI: https://doi.org/10.2478/amns-2024-0944

Palabras claveEnglish teaching evaluation, Face detection, Expression recognition, Hierarchical analysis, Fuzzy comprehensive judgment model, Genetic algorithm

© 2024 Lanna He et al., published by Sciendo

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

Palabras clave
English teaching evaluation, Face detection, Expression recognition, Hierarchical analysis, Fuzzy comprehensive judgment model, Genetic algorithm