Proceedings of the 2022 5th International Conference on Humanities Education and Social Sciences (ICHESS 2022)

Research on the Improving the Information-based teaching Ability of Local Normal University Students under the Background of Big Data

Authors
Shwu Li1, Mengdi Wang2, Hongmei Leng3, *
1Guangxi Science & Technology Normal University, Laibin, 546199, Guangxi, China
2Guangxi Vocational College of Technology and Business, Nanning, 530000, Guangxi, China
3Nanning College for Vocational Technology, Nanning, 530008, Guangxi, China
*Corresponding author. Email: 524229315@qq.com
Corresponding Author
Hongmei Leng
Available Online 30 December 2022.
DOI
10.2991/978-2-494069-89-3_15How to use a DOI?
Keywords
big data; normal university students; local universities; data mining and data analysis
Abstract

Countries around the world are experiencing an important digital change and digital competition. All countries are vigorously developing the new generation of broadband mobile communication technology (5G era) with high speed, high stability, low delay and high connection characteristic of integration with their own industries, and are actively preparing for the digital competition and game in the 6G era. The advent of the Internet, smart mobile devices, the Internet of Things, social networking, and connected objects all generate large amounts of data. The amount of data continues to grow geometrically, so that predictions use ZB, YB, GB and so on, such new storage units and storage requirements. In the big data environment, the information system involves complex information exchange, often collecting heterogeneous, symmetric and asymmetric, and unstructured data from the outside for operation. At the same time, the era of big data has been fully explored and utilized during the 14th Five-Year Plan period, which has become the direction of informatization and industrialization integration of all walks of life, and for normal colleges to fully apply information-based teaching to improve their teaching ability and management ability to open up a new research road. Through some characteristics of big data and some application models of big data, this paper provides some ideas about how to apply big data to improve the information-based teaching ability of normal university students, and to lay a solid foundation and a new path for the future stage of prospective teachers.

Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 5th International Conference on Humanities Education and Social Sciences (ICHESS 2022)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
30 December 2022
ISBN
978-2-494069-89-3
ISSN
2352-5398
DOI
10.2991/978-2-494069-89-3_15How to use a DOI?
Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Shwu Li
AU  - Mengdi Wang
AU  - Hongmei Leng
PY  - 2022
DA  - 2022/12/30
TI  - Research on the Improving the Information-based teaching Ability of Local Normal University Students under the Background of Big Data
BT  - Proceedings of the 2022 5th International Conference on Humanities Education and Social Sciences (ICHESS 2022)
PB  - Atlantis Press
SP  - 122
EP  - 129
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-494069-89-3_15
DO  - 10.2991/978-2-494069-89-3_15
ID  - Li2022
ER  -