A secure and reliable large-scale online physical education solution based on deep learning for cloud computing

With the continuous expansion of online education scale, its existing problems have gradually emerged. Therefore, it is necessary to develop a secure and reliable large-scale online physical education solution, cultivate higher-order thinking and guide students to learn effectively. This article studies cloud computing and deep learning models. And it proposes an improved model based on Graph Knowledge Tracing (GKT). The improved model can better discover causal relationships and use network structure to track students' knowledge status. Finally, experiments are conducted on the improved model and the classical model, proving that the improved model based on GKT performs well. The improved model based on GKT outperforms other models and has superior convergence speed and accuracy. It has good practicality for large-scale online physical education, helps to obtain interactive information of implicit knowledge in the scheme, and increases the richness of education.

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Publication Details

Journal
International Journal of Computer Applications in Technology
Published
2025-01-01
DOI
https://doi.org/10.1504/ijcat.2025.149359
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
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article

A secure and reliable large-scale online physical education solution based on deep learning for cloud computing

Wenbo Song
International Journal of Computer Applications in Technology
IoT and Edge/Fog Computing
article

A secure and reliable large-scale online physical education solution based on deep learning for cloud computing

Wenbo Song
article en

Abstract

With the continuous expansion of online education scale, its existing problems have gradually emerged. Therefore, it is necessary to develop a secure and reliable large-scale online physical education solution, cultivate higher-order thinking and guide students to learn effectively. This article studies cloud computing and deep learning models. And it proposes an improved model based on Graph Knowledge Tracing (GKT). The improved model can better discover causal relationships and use network structure to track students' knowledge status. Finally, experiments are conducted on the improved model and the classical model, proving that the improved model based on GKT performs well. The improved model based on GKT outperforms other models and has superior convergence speed and accuracy. It has good practicality for large-scale online physical education, helps to obtain interactive information of implicit knowledge in the scheme, and increases the richness of education.

International Journal of Computer Applications in TechnologyVol. 76(3/4)
Jilin Normal University (CN)
Openalex Percentile: Top 63%
IoT and Edge/Fog Computing
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