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Ideological-Political Education of Colleges and Schools in the Large-Data Times

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Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1117))

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Abstract

In recent years, education is becoming more and more important in the society. Meanwhile, ideological-political education in colleges and schools has attracted the attention of schools and parents. Because ideological politics learning is the basis of learning in various disciplines, but ideological and political learning is very tedious and boring. Traditional ideological politics education is always carried out in the form of meetings, talks and so on, and the results achieved are more and more important. Therefore, this paper studies the ideological-political education in the large-data times, analyzes the traits of large data times and the new connotation and traits of the ideological politics education in universities in the large-data times, and puts forward the countermeasures to strengthen the ideological politics education in colleges and schools in the large-data times. First, universities should actively improve the application of big data technology in the education process, and second, establish a high school. University ideological politics education big data sharing platform, and finally come to the conclusion that ideological politics education in the large-data times can improve the ideological and political level of students, so that students have more enthusiasm for ideological and political learning.

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Acknowledgement

This article is supported by <Multi-dimensional class management in colleges and universities promotes comprehensive education—From the perspective of “parent class”> the project, the project number is 2018XGJPF3010.

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Correspondence to Huizi Fang .

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Fang, H. (2020). Ideological-Political Education of Colleges and Schools in the Large-Data Times. In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) Big Data Analytics for Cyber-Physical System in Smart City. BDCPS 2019. Advances in Intelligent Systems and Computing, vol 1117. Springer, Singapore. https://doi.org/10.1007/978-981-15-2568-1_155

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