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The effectiveness of children’s English enlightenment network teaching based on multi-modal teaching model

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Abstract

To enhance the efficacy of traditional English enlightenment education for children, this research delves into a multi-modal teaching approach and incorporates a hidden Markov model to refine the precision of speech recognition. Within the input recognition module, voice input is combined with operational input, resulting in a multi-modal fusion perception module designed to amalgamate students’ learning and operational intent. Concurrently, a multi-modal natural interaction module for intention understanding is formulated to augment the quality of interaction during the teaching. The research findings revealed that the accuracy of the speech input recognition model surpassed that of the conventional model, increasing from 57.14 to 71.05%. The success rate of interactive perception across the seven learning dimensions within the fusion perception module surpassed 95%. Additionally, the success rate of the intention-based multi-modal interaction module exceeded 98%. The English teaching model developed in the study demonstrates superior teaching performance, effectively enhancing the efficacy of early childhood English education.

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Data availability

The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request.

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  1. School of English Language, Zhejiang Yuexiu University, Shaoxing, 312000, China

    Lan Zhang

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  1. Lan Zhang
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Correspondence to Lan Zhang.

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Zhang, L. The effectiveness of children’s English enlightenment network teaching based on multi-modal teaching model. SOCA (2024). https://doi.org/10.1007/s11761-024-00398-8

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