Design and practice of university education big data application support system

Jie Gao; Hongmei Li; Yinpeng Li

doi:10.1117/12.2675343

25 May 2023 Design and practice of university education big data application support system

Jie Gao, Hongmei Li, Yinpeng Li

Proceedings Volume 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022); 1263602 (2023) https://doi.org/10.1117/12.2675343
Event: Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 2022, Shenyang, China

Abstract

A new engine for advancing college education reform and development is big data. The construction of a college education big data application is the premise and the core in order to fully utilize the value of educational big data for the reform and development of college education. An important part of the national education modernization construction is deepening the application of big data in education and supporting and leading education and teaching reform. Big data is a fundamental support platform for data collection, storage, filtering, cleaning, fusion, analysis, and specific applications in college education. The design of the higher education big data application support system is the subject of a comprehensive analysis in this paper, which begins with an examination of data management and analysis. Including indepth planning and discussion of the data exchange, data awareness, and data application layers. The big data application support system's application and realization in higher education are then discussed. It can fully fulfill its role in higher education and support the growth and progress of higher education by thoroughly discussing and analyzing the support system for big data applications.

Citation Download Citation

Jie Gao, Hongmei Li, and Yinpeng Li "Design and practice of university education big data application support system", Proc. SPIE 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 1263602 (25 May 2023); https://doi.org/10.1117/12.2675343

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