Application Integrated Deep Learning Networks Evaluation Methods of College English Teaching

Jie Guo
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Abstract

INTRODUCTION: The construction of English evaluation methods in colleges and universities, as the essential part of English teaching in colleges and universities, is conducive to the improvement of the quality of English teaching in colleges and universities, which makes the existing English teaching more objective and reasonable, and makes the means of English teaching rich in science. OBJECTIVES: Aiming at the current wisdom teaching evaluation design methods exist evaluation indexes exist objectivity is not strong, accuracy is poor, single method and other problems. METHODS:Proposes a college English teaching evaluation method based on a deep learning network. First, the evaluation index system of English in colleges and universities is constructed by analyzing the principle of selecting evaluation indexes of English in colleges and universities; then, the deep learning network is improved through self-coder and integrated learning methods to construct the evaluation model of English teaching in colleges and universities; finally, the effectiveness and efficiency of the proposed method is verified through simulation experiment analysis. RESULTS: The results show that the proposed method improves the accuracy of the evaluation model. CONCLUSION: Solved the problems of low evaluation accuracy and non-objective system indexes of English teaching evaluation methods in colleges and universities.
应用集成深度学习网络的大学英语教学评价方法
引言:高校英语评价方法的构建作为高校英语教学的重要组成部分,有利于高校英语教学质量的提高,使现有的英语教学更加客观合理,使英语教学的手段更加丰富科学。 目的:1:针对当前智慧教学评价设计方法存在的评价指标存在客观性不强、准确性较差、方法单一等问题。 方法:提出一种基于深度学习网络的大学英语教学评价方法。首先,通过分析高校英语评价指标的选取原则,构建高校英语评价指标体系;然后,通过自编码器和集成学习方法改进深度学习网络,构建高校英语教学评价模型;最后,通过仿真实验分析验证所提方法的有效性和效率。 结果:结果表明,所提方法提高了评价模型的准确性。 结论:解决了高校英语教学评价方法存在的评价精度低、体系指标不客观等问题。
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