Research Article
The Application of Big Data Technology in the Analysis of Higher Education Optimization Management
@INPROCEEDINGS{10.4108/eai.13-10-2023.2341144, author={Shuaitong Xue}, title={The Application of Big Data Technology in the Analysis of Higher Education Optimization Management}, proceedings={Proceedings of the 3rd International Conference on New Media Development and Modernized Education, NMDME 2023, October 13--15, 2023, Xi’an, China}, publisher={EAI}, proceedings_a={NMDME}, year={2024}, month={1}, keywords={big data technology; optimize management; college students}, doi={10.4108/eai.13-10-2023.2341144} }
- Shuaitong Xue
Year: 2024
The Application of Big Data Technology in the Analysis of Higher Education Optimization Management
NMDME
EAI
DOI: 10.4108/eai.13-10-2023.2341144
Abstract
In order to understand the application of big data technology in the optimization management analysis of higher education, an application research based on big data technology in the optimization management analysis of higher education is put forward. This work is the first to explore the application of big data technology in the learning management of college students, which aims to understand and update design concepts, improve higher education, and support and support the continuous improvement of education and technology management. Everything around and in the development of higher education. Second, a 60-item questionnaire for counselors working in selected text colleges, including three issues: first, behavior management, second, access management skills, and third, management strategies. According to the test results, after data mining, the academic performance of the university's students is above 0.6, which is higher than the average. Among them, the value of character management is the greatest, so it has important applications in student work. Studying the use of big data technology in the management of higher education students is better for reforming higher education and promoting educational development. Support the growth of higher education through big data, big scope, and high-value big data-specific data properties.