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

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.