Title: A balanced allocation of network teaching resources in higher vocational colleges based on demand prediction

Authors: Yuanyuan Kong; Yunxia Li; Yang Liu

Addresses: Office of Development and Planning, Shandong Polytechnic, Jinan 250104, China ' Department of Civil Engineering, Shandong Polytechnic, Jinan 250104, China ' Planning and Finance Department, Qilu University of Technology, Jinan 250353, China

Abstract: Because the traditional teaching resource allocation method has the problems of low accuracy of resource demand prediction and low balance of resource allocation, this paper studies a new balanced allocation method based on demand prediction. The data of network teaching resources are collected, and the nonlinear demand prediction model of network teaching resources is constructed by using the principle of time series. Based on the output results of the demand prediction model, the resource surplus in the network teaching resource allocation node is obtained, the dynamic weight results of network teaching resources are calculated, and the balanced allocation function of teaching resources is constructed. The experimental results show that this research can achieve the accurate prediction of the demand for teaching resources, and improve the balance of resource allocation, with the distribution balance parameter reaching 0.98.

Keywords: demand prediction; higher vocational network teaching; teaching resources; balanced distribution.

DOI: 10.1504/IJCEELL.2024.135265

International Journal of Continuing Engineering Education and Life-Long Learning, 2024 Vol.34 No.1, pp.66 - 76

Received: 20 Aug 2021
Accepted: 09 Feb 2022
Published online: 03 Dec 2023 *

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