Experimental Research on English Learning Based on Network Remote Synchronization

In this study, a distributed network synchronous learning system is developed to solve the problems of time zone difference, interaction quality, and evaluation system in distance English learning. The system realizes cross-time zone collaboration through adaptive clock calibration and multimodal interaction protocol and combines the mixed evaluation model of speech emotion recognition, real-time grammar correction, and cognitive load monitoring. The experiment shows that the language fluency of synchronous learning group is significantly improved (p<0.01), and the fluctuation of learning effect is reduced by 58% in high-delay situations, especially for beginners, and the grammar accuracy is improved to 2.3 times that of advanced learners. The study also reveals the nonlinear relationship between network jitter and cognitive load, provides a theoretical basis for optimizing real-time interactive algorithms, and shows the feasibility of edge computing in real-time teaching and provides a quantitative decision-making model for blended curriculum design.

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Publication Details

Journal
International Journal of Web-Based Learning and Teaching Technologies
Published
2025-10-16
DOI
https://doi.org/10.4018/ijwltt.390798
Primary Topic
Robotics and Automated Systems
Type
article
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article

Experimental Research on English Learning Based on Network Remote Synchronization

Qing Ai, Hongyu Guo
International Journal of Web-Based Learning and Teaching Technologies
Robotics and Automated Systems
article

Experimental Research on English Learning Based on Network Remote Synchronization

Qing Ai, Hongyu Guo
article en

Abstract

In this study, a distributed network synchronous learning system is developed to solve the problems of time zone difference, interaction quality, and evaluation system in distance English learning. The system realizes cross-time zone collaboration through adaptive clock calibration and multimodal interaction protocol and combines the mixed evaluation model of speech emotion recognition, real-time grammar correction, and cognitive load monitoring. The experiment shows that the language fluency of synchronous learning group is significantly improved (p<0.01), and the fluctuation of learning effect is reduced by 58% in high-delay situations, especially for beginners, and the grammar accuracy is improved to 2.3 times that of advanced learners. The study also reveals the nonlinear relationship between network jitter and cognitive load, provides a theoretical basis for optimizing real-time interactive algorithms, and shows the feasibility of edge computing in real-time teaching and provides a quantitative decision-making model for blended curriculum design.

International Journal of Web-Based Learning and Teaching TechnologiesVol. 20(1)
South China Agricultural University (CN), Zhejiang Gongshang University (CN)
Openalex Percentile: Top 62%
Robotics and Automated Systems
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