Abstract
For outsiders to higher education institutions (HEIs) in South Korea, predicting the outcomes of the International Education Quality Assurance System (IEQAS)—a Korean institutional accreditation system for HEIs—is challenging. The annual IEQAS accreditation has been conducted behind closed doors; the assessment process is confidential, and there is little access to the data for the public and individuals. However, many stakeholders, such as overseas applicants to Korean HEIs, may want to predict whether particular universities will pass the upcoming IEQAS. Hence, we sought an alternative method for the outsiders to predict a binary result of the IEQAS accreditation by utilizing disclosure data that the Korean government has published. To best predict the outcomes, we mapped out a threefold discrete model combining logistic regression, discriminant analysis, and neural network. We collected the information disclosed by the Ministry of Education in 2019 on 138 Korean private HEIs and then analyzed the secondary public dataset in line with the discrete method that ensures generalizability. Results showed (i) three education investment factors, and one school operations factor appeared as key predictors among the tested indices; (ii) education cost per student within education investment proved to be the most crucial element; and (iii) while leveraging the disclosed data turned out to be reliable, neural network’s predictive accuracy was higher than those reported using logistic regression and discriminant analysis. By processing the publicly available disclosure data, our self-study model may effectively assist in predicting IEQAS outcomes, and it can also be used as a diagnostic, prior to accreditation, by local HEIs in other nations to check their preparedness and likelihood of success within similar contexts.
Highlights
Introduction and motivationSince the early 2000s, the South Korean government has implemented diverse higher education projects to attract foreign students at the national level
Through the lens of pragmatism, we suggest an underlying question and two sub-questions: Can the alternative method using public disclosure data provide reliable results to predict the Korean national accreditation system in higher education? (i) To what extent can this method using public data predict the outcomes of International Education Quality Assurance System (IEQAS)
We reviewed the published data of 138 higher education institutions (HEIs) in two classes, comparing different key items in descriptive statistics between the ACC institutes (n = 77) and the NAC institutes (n = 61)
Summary
Since the early 2000s, the South Korean government has implemented diverse higher education projects to attract foreign students at the national level. Does the IEQAS examine the administrative capacity of an individual institute in managing international students, but the government-led initiative considers competitive education courses in the institute. It is a robust institutional measure against the actions of many HEIs when “hunting for” new overseas students in
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
