Browse > Article
http://dx.doi.org/10.9723/jksiis.2018.23.6.067

A Study on Management of Student Retention Rate Using Association Rule Mining  

Kim, Jong-Man (제주대학교 경영정보학과)
Lee, Dong-Cheol (제주대학교 경영정보학과)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.23, no.6, 2018 , pp. 67-77 More about this Journal
Abstract
Currently, there are many problems due to the decline in school-age population. Moreover, Korea has the largest number of universities compared to the population, and the university enrollment rate is also the highest in the world. As a result, the minimum student retention rate required for the survival of each university is becoming increasingly important. The purpose of this study was to examine the effects of reducing the number of graduates of education and the social climate that prioritizes employment. And to determine what the basic direction is for students to manage the student retention rate, which can be maintained from admission to graduation, to determine the optimal input variables, Based on the input parameters, we will make associative analysis using apriori algorithm to collect training data that is most suitable for maintenance rate management and make base data for development of the most efficient Deep Learning module based on it. The accuracy of Deep Learning was 75%, which is a measure of graduation using decision trees. In decision tree, factors that determine whether to graduate are graduated from general high school and students who are female and high in residence in urban area have high probability of graduation. As a result, the Deep Learning module developed rather than the decision tree was identified as a model for evaluating the graduation of students more efficiently.
Keywords
School Age Population Decline; Student Retention Rate; Association Rule; Deep Learning;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 Kim, S. S., "A Exploratory Study on Withdrawal and Transfer of Korean College Students: The Influence of College-Choice Reason and Satisfaction Afterwards," The Journal of Korean Education, Vol. 35, No. 1, pp. 227-249, 2008.
2 Kim, J. M., " Study on Prevention of Student Drop out Rate Using Deep Learning," Jeju National University, KOREA, 2017.
3 Bang, E. H. and Others 7, "Effect of Korean High School Student's Mental Health on Academic Achievement and School Dropout Rate," J Korean Acad Child Adolesc Psychiatry, Vol. 27, No. 3, pp. 173-180, 2016.   DOI
4 Lee, H. J. and Kim, Y. N., "The School Related Factors Affecting High School Dropout Rates," Asian Journal of Education Vol. 13, No. 1, pp. 149-185, 2012.   DOI
5 Sim, H., "A Grounded Theory-Based Analysis on the Factors that Causing Dropout of Students in Korean National Universities," Journal of Education and Culture, Vol. 23, No. 2, pp. 105-128, 2017.   DOI
6 Lee, H. J., "Individual, Family, School and Community Related Variables Predicting Longitudinal School Adjustment in Urban Adolescents," Journal of Education and Culture, Vol. 21, No. 2, pp. 27-56, 2015.
7 Cho, Y. J. and Han, S. G., "An Analysis of Student and Parent Factors Influencing School Adjustment," The Education Assignment Institute of Chonbuk National University, KOREA, pp. 117-144, 2015.
8 Lee, B. H. and Kang, D. K., "A Study of School Maladjustment Action Factors in Secondary School Students," Journal of Education and Culture, Vol. 20, No. 3, pp. 125-148, 2014.   DOI
9 Lee, J. H. and Lee, H. K., "A Study on Unstructured Text Mining Algorithm through R Programming Based on Data Dictionary," Journal of the Korea Industrial Information Systems Research, Vol. 20, No. 2, pp. 113-123, 2015.   DOI
10 Lee, Y. H. and Jeon, H. J., "Students' Information Communication Skill Affecting Relationship among Technology Acceptance, Education Service Quality, Relationship Quality, and Education Service Satisfaction," Journal of the Korea Industrial Information Systems Research, Vol. 16, No. 5, pp. 73-81, 2011.   DOI
11 Lee H. G. and Shin, Y. H., "Protein Disorder/Order Region Classification Using EPs-TFP Mining Method," Journal of the Korea Industrial Information Systems Research, Vol. 17, No. 6, pp. 59-72, 2012.   DOI