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Design of Foreign Language Teachers' Teaching Language Teaching Evaluation Model Based on Association Mining

机译:基于协会挖掘的外语教学教学教学评价模型设计

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In order to improve the quality of foreign language teachers' teaching evaluation, a teaching language teaching evaluation model based on association rule mining is proposed, which combines the data analysis method with the optimization design of the teaching language quantitative evaluation model. A time series analysis model of the statistical data flow of foreign language teachers' teaching language teaching evaluation is constructed, and the data structure of foreign language teachers' teaching language evaluation is analyzed. The phase space of the statistical data of foreign language teaching evaluation is reconstructed, and the association rule feature of foreign language teacher teaching language teaching evaluation is extracted in the reconstructed phase space. The extracted features are used as the clustering center for information fusion and the adaptive regression analysis is used to realize the optimal design of the teaching evaluation model. The simulation results show that this method can improve the accuracy of teaching evaluation of foreign language teachers, and the whole evaluation process has good convergence and strong anti-interference ability.
机译:为了提高外语教师教学评估的质量,提出了一种基于关联规则挖掘的教学语言教学评估模型,将数据分析方法与教学语言定量评价模型的优化设计相结合。构建了外语教学教学教学评估统计数据流的时间序列分析模型,分析了外语教师教学评估的数据结构。重建外语教学评估统计数据的相位空间,外语教师教学语言教学评估的关联规则特征在重建的相空间中提取。提取的特征用作信息融合的聚类中心,并且使用自适应回归分析来实现教学评估模型的最佳设计。仿真结果表明,该方法可以提高外语教师教学评估的准确性,整个评估过程具有良好的收敛性和强烈的抗干扰能力。

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