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Research on the Application of Information-Based Big Data Fusion Technology in College English Education Design.

Authors :
Chen, Yi
Huang, Jianwen
Source :
Wireless Communications & Mobile Computing; 8/27/2022, p1-11, 11p
Publication Year :
2022

Abstract

English is the most widely used language in the world, and China's economic development has become the second largest country in the world. Therefore, popularizing English in China is the need of national conditions and the desire for talents who are good at English majors. In the current traditional college English education mode and in the external environment, college students' English knowledge has not been substantially expanded, which has seriously caused the social needs not being met and students not being able to show their self-worth. Based on the deficiency of traditional college English teaching mode, this paper designs an efficient and perfect college English education mode by combining information big data fusion technology, so as to ensure that students can really love English and learn English more easily. The results of the experiment are as follows: (1) college English education and students' English learning are analyzed, and the research direction of the experiment is approved, and the functional has been investigated, which lays a foundation for the experimental research of this paper; (2) old-fashioned college English education mode: intelligent big data technology is applied to English education. By using the information big data fusion algorithm to ensure the qualified English teaching effect, it not only helps teachers effectively combine big data resources but also changes the atmosphere of teaching classes, constructs modern language education mode, and promotes students' thinking mode of exploring language learning. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15308669
Database :
Complementary Index
Journal :
Wireless Communications & Mobile Computing
Publication Type :
Academic Journal
Accession number :
158755105
Full Text :
https://doi.org/10.1155/2022/9708138