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Research on Optimization and Allocation of English Teaching Resources

机译:英语教学资源优化与配置研究

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摘要

To rationally allocate teaching resources in English teaching, a teaching resource optimization and allocation management method is proposed based on a convolutional neural network (CNN) and Arduino device. By constructing a 9-layer CNN classification and recognition model and the English education resource library of the Arduino device and applying them to the recognition program design of the Arduino device, the rational optimization and allocation of teaching resources are realized. Simulation results show that the recognition accuracy of the proposed method is over 90 for Arduino devices, and the recognition accuracy is over 80 for real English teaching scenarios, which means that the proposed method has a certain practical application value. Moreover, the interaction mode between English learners and English teaching resources is innovated, which contributes to the optimization and allocation of English teaching resources. Thus a new idea is generated to integrate the English teaching resources.
机译:为了在英语教学中合理分配教学资源,该文提出一种基于卷积神经网络(CNN)和Arduino设备的教学资源优化与分配管理方法。通过构建Arduino设备的9层CNN分类识别模型和英语教育资源库,并将其应用于Arduino设备的识别程序设计,实现教学资源的合理优化和分配。仿真结果表明,所提方法对Arduino设备的识别准确率在90%以上,对真实英语教学场景的识别准确率在80%以上,具有一定的实际应用价值。此外,创新了英语学习者与英语教学资源的互动模式,有助于英语教学资源的优化和配置。从而产生了整合英语教学资源的新思路。

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