Title: High quality management of higher education based on data mining

Authors: Lihui Yang; Xiuhong Qin; Wenhong Liu

Addresses: Academic Affairs Office, Hebei Women's Vocational College, Shijiazhuang, 050091, China ' Institute of Innovation and Entrepreneurship, Hebei Women's Vocational College, Shijiazhuang, 050091, China ' Academic Affairs Office, Hebei Women's Vocational College, Shijiazhuang, 050091, China

Abstract: In order to improve the quality of higher education, student satisfaction, and employment rate, a data mining based high-quality management method for higher education is proposed. Firstly, construct a high-quality evaluation system for higher education based on the principles of education quality evaluation. Secondly, the association rule mining method is used to construct a university education quality management model and determine the weight of the impact indicators for high-quality management of university education. Finally, the fuzzy evaluation method is used to determine the high-quality evaluation function of higher education, and the results of high-quality evaluation of higher education are obtained. High-quality management strategies are developed based on the evaluation results to improve the quality of education. The experimental results show that the student satisfaction rate of this method can reach 99.3%, and the student employment rate can reach 99.9%.

Keywords: association rule mining; indicator weight; fuzzy evaluation; data mining.

DOI: 10.1504/IJBIDM.2024.140906

International Journal of Business Intelligence and Data Mining, 2024 Vol.25 No.3/4, pp.424 - 450

Received: 15 Sep 2023
Accepted: 28 Feb 2024
Published online: 03 Sep 2024 *

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