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

<p>In recent years, with the rapid development of the Internet and education informatization, online teaching has become a popular education mode in the information age, providing learners with very rich teaching resources. In this paper, we construct a personalized system and co-recommendation technology for English teaching resources, and we improve the traditional co-recommendation algorithm and propose hybrid recommendations. The performance of the system is evaluated experimentally to compare the effectiveness of the performance of the four systems. The improved recommendation algorithm is superior to the other three recommendation algorithms in each dataset in the system. The average grade mean of the experimental class assisted by the hybrid recommendation system in teaching English in colleges and universities in the latter two experiments is 27.54, which is higher than that of the comparison class of 25.33, and the T-value is 1.81>1.645. The improved personalized recommender system has good validity and stability in both performance and practical application.</p>
</abstract>

In recent years, with the rapid development of the Internet and education informatization, online teaching has become a popular education mode in the information age, providing learners with very rich teaching resources. In this paper, we construct a personalized system and co-recommendation technology for English teaching resources, and we improve the traditional co-recommendation algorithm and propose hybrid recommendations. The performance of the system is evaluated experimentally to compare the effectiveness of the performance of the four systems. The improved recommendation algorithm is superior to the other three recommendation algorithms in each dataset in the system. The average grade mean of the experimental class assisted by the hybrid recommendation system in teaching English in colleges and universities in the latter two experiments is 27.54, which is higher than that of the comparison class of 25.33, and the T-value is 1.81>1.645. The improved personalized recommender system has good validity and stability in both performance and practical application.

Personalized Recommendation System for English Teaching Resources in Colleges and Universities Based on Collaborative Recommendation

Applied Mathematics and Nonlinear Sciences

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

In recent years, with the rapid development of the Internet and education informatization, online teaching has become a popular education mode in the...

Personalized Recommendation System for English Teaching Resources in Colleges and Universities Based on Collaborative Recommendation

Publicado en línea: 05 ago 2024

Páginas: -

Recibido: 04 abr 2024

Aceptado: 19 jun 2024

DOI: https://doi.org/10.2478/amns-2024-2210

Palabras clave
Teaching resources, Hybrid recommendation, Personalized system, Collaborative recommendation

© 2024 Zhihua Qu, published by Sciendo

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

Personalized Recommendation System for English Teaching Resources in Colleges and Universities Based on Collaborative Recommendation

Publicado en línea: 05 ago 2024

Páginas: -

Recibido: 04 abr 2024

Aceptado: 19 jun 2024

DOI: https://doi.org/10.2478/amns-2024-2210

Palabras claveTeaching resources, Hybrid recommendation, Personalized system, Collaborative recommendation

© 2024 Zhihua Qu, published by Sciendo

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

Palabras clave
Teaching resources, Hybrid recommendation, Personalized system, Collaborative recommendation