The mining method of integrating the thinking and political elements of curriculum into English teaching based on big data technology

被引:0
|
作者
Cao M. [1 ]
机构
[1] School of Foreign Languages and Literature, Changji University, Xinjiang, Changji
关键词
Canopy clustering; English teaching; Initial data; k-means algorithm; PCA method;
D O I
10.2478/amns.2023.2.00614
中图分类号
学科分类号
摘要
In order to explore the integration path of curriculum Civics in English teaching, this paper proposes the construction method of students’ Civics behavioral portrait based on big data technology to mine the behavioral data of English majors. The behavioral data of students were collected with the help of various information systems in universities, and the processed data were clustered and analyzed based on the K-means algorithm. For the uncertainty of the K-value and initial center, the PCA method is used to reduce the dimensionality of the initial data, and the density Canopy clustering replaces the pre-processing process in the K-means algorithm. The average purity of clusters reached 0.88. From the mining effect, in the teaching theme of “people and society”, the main Civics elements are social service, science and technology, with heat values of 0.407 and 0.352. Big data the technology has provided strong support for the integration of Civics and English teaching. © 2023 Mei Cao, published by Sciendo.
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