Journal of Information Technology Applications and Management

Korea Data Strategy Society (한국데이터전략학회)
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Analysis of Factors for Private Universities Educational Restitution Rate using Data Mining : Focusing on the Panel Fixed Effect Model and Non-parametric Regression Estimation

데이터 마이닝을 활용한 사립대학 교육비 환원요인 분석 : 패널 고정효과모형과 비모수회귀추정을 중심으로

  • Chae, Dong Woo (Department of Finance, Graduate School of Hoseo University) ;
  • Lee, Mun-Bum (Graduate School of Management Of Technology(MOT) of Hoseo University) ;
  • Jung, Kun-Oh (Department of Global Commerce, Hoseo University)
  • Received : 2020.12.01
  • Accepted : 2020.12.14
  • Published : 2020.12.31
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Abstract

The Educational Restitution Rate is an important parameter that determines the quality of university education. This paper analyzed data from 148 private universities over the 10 years from 2009 to 2018 using data mining techniques in Korea. A significant causal relationship is detected in the fixed effect model as a result of the panel estimation. And the scale of faculty expansion and fund management, which are the university evaluation indicators, and the size of basic funds, respectively, have a positive effect on the ERR, which is within the confidence interval. In the analysis, the more private universities improve the tuition dependence rate, the more decisively positive affecting ERR. As a result of nonparametric regression estimation, when the faculty expansion ratio is reinforced, the effect of economies of scale is detected in some sections, the improvement of the tuition dependence rate, and the result value is generated through the improvement that results are derived at a certain point in time. We hope that the university based on this study can be a basic Indicators for the diagnosis of basic competencies and policy of student-centered education.

Keywords

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