Analysis and Application of Civic Context Construction for University English Courses Combined with Cluster Analysis

This paper applies the cluster analysis method to classify different Civics contexts in university English courses, and improves the accuracy of Civics context text clustering by extracting the word stems of English Civics context texts. The text similarity calculation is used to remove feature words from the preprocessed text, to converge into a collection of feature words. The texts containing English Civic and Political Context are clustered and analyzed, and the clustering effect of Civic and Political Context texts is judged according to the clustering evaluation. The status quo of Civic and Political integration into English curriculum is explored from different dimensions, and corresponding optimization strategies are proposed with the converged data. The results show that the Civic-Political contexts of English courses are mainly divided into three categories, and based on the clustering of the Civic-Political contexts of university English courses, the contexts of “living, learning and doing” are relatively independent. The contexts “history, culture and society” and “science and technology” are closer. In integrating Civics and Politics into English teaching, the mean value of the dimension of teaching method is 4.212, which is in a better integration situation.