JOURNAL ARTICLE

Maturity Evaluation Model of Higher Education Quality Management Based on OBE Concept of Teaching Operation State Monitoring System.

  • Published In: International Journal of High Speed Electronics & Systems, 2025, v. 34, n. 4. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Li, GuoFang 3 of 3

Abstract

In order to realize the quantitative management of higher education quality, an evaluation method of higher education quality management maturity based on OBE concept is proposed. Construct a phase space distribution structure model of higher education quality management maturity, establish a parameter set of higher education quality management maturity distribution index, adopt OBE concept to construct a fuzzy association rule distribution set, extract association regularity features, classify multi-dimensional attribute features, conduct data partition scheduling in the fuzzy clustering center according to the differences of statistical features, construct a feature decomposition model, and reorganize the ontology structure of higher education quality management maturity. The binary structure characteristics are reconstructed in the virtual database, and fuzzy clustering is carried out under the OBE concept according to the reconstruction results, so as to realize the optimal evaluation of the maturity of higher education quality management. The experimental simulation results show that this method has good feature clustering and high reliability in evaluating the maturity of higher education quality management. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of High Speed Electronics & Systems. 2025/12, Vol. 34, Issue 4, p1
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2025
  • ISSN:0129-1564
  • DOI:10.1142/S0129156425402116
  • Accession Number:186254785
  • Copyright Statement:Copyright of International Journal of High Speed Electronics & Systems is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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