Design of English Teaching Capability Evaluation Model Under Big Data Analysis

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Liqin He, Chaojie Hu, Ling Nie, Chunxia Li, Honglian Liu

Abstract

Traditional methods of evaluating English teaching capability involve a considerable degree of subjective human judgment, leading to classification errors in big data information. To improve the comprehensiveness and accuracy of English teaching capability evaluation, it is necessary to construct a corresponding evaluation model based on big data. This paper employs the k-means clustering analysis algorithm to devise a system structure design for English teaching capability, applies constrained parameter big data structure analysis, and proposes utilizing a quantitative recursive approach to evaluate the teaching capabilities of big data information models based on cluster analysis. The simulation results demonstrate that the method designed in this paper can enhance the comprehensiveness and precision of English teaching capability evaluation, thereby contributing to the advancement of information fusion analysis capabilities.

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