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A study on development of support index for supporting adaptive and preventive counseling based on logit model
Journal of the Korean Data & Information Science Society 2019;30:323-33
Published online March 31, 2019;
© 2019 Korean Data and Information Science Society.

Heegeon Shin1 · Hosoo Nam2

1Department of Nursing, Dongseo University, 2Division of Mechatronics Engineering, Dongseo University
Correspondence to: Professor, Division of Mechatronics Engineering, Dongseo University, Busan, 47011, Korea. E-mail:
Received January 17, 2019; Revised January 31, 2019; Accepted January 31, 2019.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
In this study, we have tried to improve the effectiveness of counseling through developing support index and utilized the index for student counseling from whom encountered various issues during their college life. In order to develop the support index, about 20,419 records were analyzed based on the results of learning from the training data for the last six years. Individual factors for students were set as descriptive variables, and students’ academic continuity and dropout were analyzed through logistic regression. As a results, firstly, the input of explanatory variables was significant in the model fit (p < .001). Secondly, the number of breaks, the number of academic records, and economic factor1 have a strong impact on the support index, but the number of enrollment semester, the average of grades, and the number of scholarships have a negative effect on the support index. Lastly, economic factor2 and the total amount of scholarships were shown significant, but the impact on the support index was minimal. Based on the results, the support index, which indicates the degree of support required was proposed to increase the efficiency of student counseling.
Keywords : Logistic regression, logit model, preventive counseling, support Index, supervised learning.