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Experimental study demonstrates improved language fluency and reduced learning fluctuations in distance English learners, highlighting the value of adaptive synchronization and edge computing.
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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Ai et al. (2025) studied this question.
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