APPLYING PRINCIPAL COMPONENT ANALYSIS AND CLUSTERING TO ASSESS ACCREDITATION RESULTS IN HIGHER EDUCATION INSTITUTIONS

Authors

  • Le Phuoc Thanh Quang Nam University, Vietnam

DOI:

https://doi.org/10.51453/2354-1431/2023/976

Keywords:

Principal Component Analysis, Clustering, K-MEANS clustering algorithm,Correlation Coefficient, Higher Education Quality Accreditation

Abstract

Currently, the centers for education accreditation (CEA) have announced university accreditation results by the standard set under Circular 12/2017 / TT-BGDĐT. The accreditation results are standardized in the form of a multi-dimensional database based on these standards. This research is carried out in a combination of two main techniques- principal component analysis and clustering- to present, analyze and extract useful knowledge from the accreditation results. At the same time, the paper points out the educational institutions' strengths and weaknesses based on the standards, the relationship between different fields as well as compare the assessment levels among accreditation centers. This is the foundation to compare and improve the quality in educational institutions.

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References

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Published

2023-06-27

How to Cite

Lê, T. (2023). APPLYING PRINCIPAL COMPONENT ANALYSIS AND CLUSTERING TO ASSESS ACCREDITATION RESULTS IN HIGHER EDUCATION INSTITUTIONS. SCIENTIFIC JOURNAL OF TAN TRAO UNIVERSITY, 9(3). https://doi.org/10.51453/2354-1431/2023/976

Issue

Vol. 9 No. 3 (2023): Natural Science - Engineering - Technology

Section

Natural Science and Technology

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