Abstract
The ever-changing rules and regulations, pedagogy and teaching methods of countries all over the world ensure that great changes have taken place in the education system. However, the introduction of BD entry technology also has a significant impact on China's education methods and education evaluation. This paper discusses how the data environment of school and school system changes. This paper discusses the typical application of data analysis, expounds the differences of BG, reviews the value of learning analysis in building prediction model, and illustrates the situation of frontier work in CU with examples. The results show that: in the evaluation index system of education informational, the largest proportion of security is 0.637, and the smallest proportion of resources is 0.452.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chen, G.: Research on the integration of information technology and practical writing teaching in higher vocational colleges. Revista de la Facultad de Ingenieria 32(12), 1090–1094 (2017)
Yi, W., Wei, X.: Suggestions and countermeasures of integration of production and education in higher vocational colleges. Int. J. Softw. Eng. Appl. 11(5), 109–114 (2017)
Graebe, J.: Identifying and resolving conflicts of interest for individuals in a position to control educational content. J. Contin. Educ. Nurs. 49(3), 102–104 (2018)
Suzuki, R., Nakamiya, Y., Watanabe, M., et al.: Relationship between stress coping mechanisms and depression in kidney transplant recipients. Transplant. Proc. 51(3), 761–767 (2019)
Nthontho, M.A.: Schools as legal persons: implications for religion in education. S. Afr. J. Educ. 38(Supplement 2), 1–8 (2018)
Lee, E.J., Jeong-Eun, J.O., Yun, M.H.: The effects of education for resolving the information gap on the lifelong learning competence of the middle aged. J. Fish. Marineences Educ. 29(5), 1313–1330 (2017)
Kirchhof, G., Lindner, J.F., Achenbach, S., et al.: Stratified prevention: opportunities and limitations: report on the 1st interdisciplinary cardiovascular workshop in Augsburg. Clin. Res. Cardiol. 107(3), 193–200 (2018)
Hafezi, M.A., Yazdipour, M., Matlabi, D.: What are the aims of managers in developing digital libraries? Iran. J. Inf. Process. Manag. 32(3), 817–841 (2017)
Ruijie, L.I., Weifu, C., Yinye, Y., et al.: First principle calculation of electromagnetic mechanism for Fe2Si bulk material. J. Wuhan Univ. Technol.-Mater. Sci. Ed. 34(001), 64–68 (2019)
Baker, A.: Reviewing big data and learning analytics in higher education: current theory and practice. J. Scholarship Teach. Learn. Christ. High. Educ. 8(1), 8 (2018)
Zeide, E.: The structural consequences of big data-driven education. Big Data 5(2), 164–172 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Ke, C., Wang, B. (2023). Information Education Evaluation System Under Big Data Technology. In: Abawajy, J.H., Xu, Z., Atiquzzaman, M., Zhang, X. (eds) Tenth International Conference on Applications and Techniques in Cyber Intelligence (ICATCI 2022). ICATCI 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 170. Springer, Cham. https://doi.org/10.1007/978-3-031-29097-8_115
Download citation
DOI: https://doi.org/10.1007/978-3-031-29097-8_115
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-29096-1
Online ISBN: 978-3-031-29097-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)