Abstract
In the context of big data, adding data analysis and processing to the teaching system of IT-supported courses of economics and management majors is of great significance to improving the comprehensive quality of students. This article aims to study the teaching system of IT supporting courses based on big data technology. This article adopts the method of experimental investigation to randomly survey the students’ performance of economics and management majors in a certain college that offers big data technology and application majors, and conducts research on this. Experimental data shows that from the perspective of student feedback and test results, students’ interest in learning and learning effects have been greatly improved. The results of the experiment show that the student’s score in the IT-supported course teaching system for economics and management based on big data is 89.89 ± 5.45, which is higher than the traditional learning score of 79.51 ± 5.99. Both in basic knowledge mastery and practical teaching are better than the control group. In the process of exploring the construction of IT supporting teaching system for economics and management majors in the era of big data, there is still a lot of work to be done. In the next teaching and research, we will study the teaching mode and assessment mode of IT supporting courses for economics and management majors under the background of big data. Design, etc. to be discussed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Bonney, L., Plouffe, C.R., Brady, M.: Investigations of sales representatives’ valuation of options. J. Acad. Mark. Sci. 44(2), 135–150 (2016)
Cowan, B., Schwab, B.: Employer-sponsored health insurance and the gender wage gap. J. Health Econ. 45, 103–114 (2016)
Sang, H., Kyoung, K., Eun, C., et al.: System framework for cardiovascular disease prediction based on big data technology. Symmetry 9(12), 293 (2017)
Enderle, G.: How can business ethics strengthen the social cohesion of a society? J. Bus. Ethics 150(3), 1–1 (2018)
Balaban, R.A., Gilleskie, D.B., Tran, U.: A quantitative evaluation of the flipped classroom in a large lecture principles of economics course. J. Econ. Educ. 47(4), 269–287 (2016)
Bosshardt, W., Walstad, W.B.: Economics and business coursework by undergraduate students: findings from Baccalaureate and beyond transcripts. J. Econ. Educ. 48(1), 51–60 (2017)
Li, R.: Communication preference and the effectiveness of clickers in an Asian university economics course. Heliyon 6(4), e03847 (2020)
Colander, D.: Tools, not rules: are we teaching the wrong principles of economics in the introductory course? East. Econ. J. 42(2), 163–168 (2016)
Li, I., Simonson, R.: Capstone senior research course in economics. J. Econ. Educ. 47(2), 161–167 (2016)
Nairn, M.F., Lenka, U.: Talent management: a burgeoning strategic focus in Indian IT industry. Ind. Commer. Train. 49(4), 183–188 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Wang, Y., Zhang, Y. (2021). The Teaching System of IT Support Course Group of Economics and Management Majors Based on Big Data Technology. In: Xu, Z., Parizi, R.M., Loyola-González, O., Zhang, X. (eds) Cyber Security Intelligence and Analytics. CSIA 2021. Advances in Intelligent Systems and Computing, vol 1342. Springer, Cham. https://doi.org/10.1007/978-3-030-70042-3_73
Download citation
DOI: https://doi.org/10.1007/978-3-030-70042-3_73
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-70041-6
Online ISBN: 978-3-030-70042-3
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)