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Statistical Model of Online Educational Resource Allocation for Coordinated Development of Regional Economy

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e-Learning, e-Education, and Online Training (eLEOT 2021)

Abstract

In order to improve the statistical ability of online education allocation resources, a statistical model of online education allocation resources for the coordinated development of regional economy is proposed. Based on the principle of comparability and practicability in the selection of statistical indicators of online education allocation resources, this paper constructs a statistical indicator system of online education allocation resources, assigns the weight of statistical indicator system of online education allocation resources by using the specific steps of analytic hierarchy process, and calculates the allocation level of educational resources of each school in six administrative regions by using the weighted index and model, According to the results of the cluster analysis of the types of school resource allocation, by introducing the difference coefficient, the balance of the allocation of various types of school education resources in the region is determined. Through the establishment of the statistical model of online education resource allocation, the statistics of online education resource allocation is realized. The experimental results show that the statistical model of online education resource allocation for the coordinated development of regional economy has relatively high statistical ability in terms of statistical efficiency and student satisfaction.

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Correspondence to Xin Tang .

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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Tang, X., Qiao, Jh. (2021). Statistical Model of Online Educational Resource Allocation for Coordinated Development of Regional Economy. In: Fu, W., Liu, S., Dai, J. (eds) e-Learning, e-Education, and Online Training. eLEOT 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 390. Springer, Cham. https://doi.org/10.1007/978-3-030-84386-1_22

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  • DOI: https://doi.org/10.1007/978-3-030-84386-1_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-84385-4

  • Online ISBN: 978-3-030-84386-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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