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

<p>The optimized sparrow search algorithm (ISSA) is built on top of the deep neural network (DNN) in this paper, along with a new deep recurrent neural network (DRNN) algorithm that is proposed by improving the DNN. Ultimately, an ISSA-DRNN-based model for assessing the quality of English course teaching has been established. To examine the application impact of the ISSA-DRNN-based English course quality teaching evaluation model, SA University has been chosen as the study location. Two groups have been created: an experimental group and a control group. The experimental group’s academic level scores grew by 5.1 points in terms of English achievement, whereas the control group’s average score increased by 0.36 points, indicating a very significant difference (P&lt;0.01). The four characteristics of satisfaction with teaching effectiveness—interest in learning, ability improvement, desire to learn behavior, and course satisfaction— showed significant differences (P&lt;0.05) among students in the experimental group. In the self-assessment of English literacy, the dimensions with the most important proportion of “relatively large” ratings are learning motivation and class participation, accounting for 43.73% and 42.92%, respectively. The dimensions with the highest proportion of “substantial” grades are English learning ability and learning motivation, accounting for 21.03% and 20.63% in that order.</p>
</abstract>

The optimized sparrow search algorithm (ISSA) is built on top of the deep neural network (DNN) in this paper, along with a new deep recurrent neural network (DRNN) algorithm that is proposed by improving the DNN. Ultimately, an ISSA-DRNN-based model for assessing the quality of English course teaching has been established. To examine the application impact of the ISSA-DRNN-based English course quality teaching evaluation model, SA University has been chosen as the study location. Two groups have been created: an experimental group and a control group. The experimental group’s academic level scores grew by 5.1 points in terms of English achievement, whereas the control group’s average score increased by 0.36 points, indicating a very significant difference (P<0.01). The four characteristics of satisfaction with teaching effectiveness—interest in learning, ability improvement, desire to learn behavior, and course satisfaction— showed significant differences (P<0.05) among students in the experimental group. In the self-assessment of English literacy, the dimensions with the most important proportion of “relatively large” ratings are learning motivation and class participation, accounting for 43.73% and 42.92%, respectively. The dimensions with the highest proportion of “substantial” grades are English learning ability and learning motivation, accounting for 21.03% and 20.63% in that order.

Teaching Quality Assessment of English Courses in Colleges and Universities Based on ISSA-DRNN

Applied Mathematics and Nonlinear Sciences

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

The optimized sparrow search algorithm (ISSA) is built on top of the deep neural network (DNN) in this paper, along with a new deep recurrent neural network...

Teaching Quality Assessment of English Courses in Colleges and Universities Based on ISSA-DRNN

Publié en ligne: 03 mai 2024

Pages: -

Reçu: 11 avr. 2024

Accepté: 19 avr. 2024

DOI: https://doi.org/10.2478/amns-2024-1024

Mots clés
Deep neural network, Sparrow search algorithm, ISSA-DRNN, Teaching quality assessment, English language program

© 2024 Guoying Yu et al., published by Sciendo

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

Teaching Quality Assessment of English Courses in Colleges and Universities Based on ISSA-DRNN

Publié en ligne: 03 mai 2024

Pages: -

Reçu: 11 avr. 2024

Accepté: 19 avr. 2024

DOI: https://doi.org/10.2478/amns-2024-1024

Mots clésDeep neural network, Sparrow search algorithm, ISSA-DRNN, Teaching quality assessment, English language program

© 2024 Guoying Yu et al., published by Sciendo

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

Mots clés
Deep neural network, Sparrow search algorithm, ISSA-DRNN, Teaching quality assessment, English language program