• Korean Journal of Social Welfare
• /
• v.61 no.4
• /
• pp.191-215
• /
• 2009

The purposes of this study were to investigate the factors that influence the school drop-out of North Korean refugee youth and to generate recommendations for social work practice and the resettlement policies of the government to ameliorate the high school drop-out rate among North Korean refugee youth. This study examined the effects of the environmental factors such as the quality of parenting practice, peer attachment and the kind of school a youngster attends, and personal characteristics such as self-respect and acculturation stress level, and academic efficacy on the school drop-out intention. Gender, duration of stay in Korea, family economic status were established as control variables. The drop-out intention was used as a proxy for drop-out behavior. The study findings indicate that the personal characteristics such as gender, self-respect and acculturation stress, academic efficacy were the significant influencing factors, whereas environmental factors such as quality of parenting, peer attachment did not exert any statistically significant effect on the drop-out intention. At the conclusion, the implications of the study findings for research, social work practice and the government policies were discussed.

• Journal of The Korean Association of Information Education
• /
• v.11 no.2
• /
• pp.205-218
• /
• 2007

This study investigates the reasons of dropout in a survey of 348 dropouts from a cyber university located in Seoul, Korea. Most common reasons are time constraints due to work or family-related needs. Difficulties in adjusting to online learning environment and uncertainties regarding the value of a cyber university degree also played important roles. Drop-out students who pointed to these two reasons also suffered from lack of communication and interaction with other students and professors. Efforts to address these issues are in order as well as the development of time-efficient learning strategies and financial aids.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2018.05a
• /
• pp.37-40
• /
• 2018

빅데이터 산업 부상과 함께 교육 데이터 분석 분야가 새롭게 주목받고 있다. 교육 현장에서 학습 데이터의 양과 종류는 꾸준히 증가하고 있고 이를 분석하기 위한 정보기술도 계속 발전하고 있다. 한편, 학교 교육은 사회적 성취와 밀접한 관련이 있어 사회이동의 중요한 수단이 되는 만큼 학교 교육으로부터 이탈할 위험이 있는 학생들을 조기에 발견하여 이탈을 방지하는 것은 매우 중요하다. 본 논문은 대학생의 중도탈락을 예방하기 위해 로지스틱 회귀분석과 다층 퍼셉트론 기법을 이용해 학습 데이터를 분석하여 예측 모델을 생성하고 해당 모델을 평가한다. 평가 결과, 다층 퍼셉트론 모델이 로지스틱 회귀분석 모델에 비해 정확도와 재현율은 우수하였지만 정밀도는 약간 저조하였다.

• Digital Contents
• /
• no.7 s.98
• /
• pp.21-29
• /
• 2001

대부분의 사이버 대학이 아직까지 사이버 교육에 적합한 양질의 교육용 콘텐츠나 교수진이 턱없이 부족한 것으로 알려져 개강 후 심각한 학습부진은 물론 중도 이탈하는 학생들이 늘어나는 현상이 벌어지고 있다. 또 사이버대학을 관장하는 교육인적자원부 역시 뚜렷한 정책 대안을 마련하지 못해 상당한 난항을 겪고 있는 등 많은 문제점 또한 지적되고 있다. 이에 국내 사이버대학의 현황과 문제점을 지적하고 그 대책과 발전방향을 모색해 보고자 한다.

• Korean Journal of Culture and Social Issue
• /
• v.13 no.2
• /
• pp.33-54
• /
• 2007

This study was performed to develop a group counseling program for the South Koreans and the North Korean defectors to identify mutual cultural characteristics and personal traits, and to acquire adaptation capacity for the other's culture and interpersonal relationship. And then we validated the effect of this group program. This program was based on the existing program even if that was not validated through research work. Actually this program was for encouraging the South Koreans and the North Korean defectors to acquire interpersonal ability through mutually dependent and cooperative work based on the equal status naturally and to adjust themselves to corresponding culture. Each session continued for 1.5 hour per week. And the sessions were done for 4 weeks. This research was analysed, and the results were compared with control group's results. The results showed that treatment group revealed significantly positive outcomes than control group. But, five participants among the North Korean defectors were dropped out in the course. So North Korean defectors' credibility got lowered.

• Communications for Statistical Applications and Methods
• /
• v.18 no.6
• /
• pp.687-696
• /
• 2011

Customer Lifetime or Customer Lifetime Value is a essential metric of differentiated CRM marketing and differentiated marketing strategy as a company core competency. However, customer lifetime used in companies is easily obtained from a confined simple customer attrition rate at some specific time point regardless of customer characteristics. In this study, in order to overcome the constraints of previous simple methods and to make practical use of it in industries, we suggest a method that estimates a customer lifetime using a customer segment based survival analysis with the censored data of customers; in addition, we apply this method to A mobile telecom company data. A method using customer segment based survival analysis is suggested in this study 1) includes all customers having different subscription dates, 2) reduces individual error, 3) can reflect trends after the observed time point and is more realistic.

• The Journal of the Korea Contents Association
• /
• v.20 no.2
• /
• pp.649-657
• /
• 2020

The purpose of this study is to provide an in-depth understanding of college life in North Korean defectors attending nursing school in South Korea, through a qualitative study method. Between September and October 2017, 8 nursing students of North Korean defectors background who can fully describe their college life were recruited for in-depth interview. Using Colaizzi's phenomenological method of data analysis, 4 theme clusters and 5 subcategories were deduced. The results showed that participants had experienced difficulties in preparing for college admission. Moreover, they had experienced difficulties from differences between North and South Korea, especially regarding verbal language (accent), educational and assessment methods, and culture. Therefore, the establishment and application of an assistant program for nursing students of North Korean defectors background is essential to assist students in adapting to a new college lifestyle and completing their degree.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2023.07a
• /
• pp.335-338
• /
• 2023

국방 무기체계의 운용유지를 위해서는 숙련자에 의한 신뢰성있는 정비 지원이 필요하다. 특히, 고도의 기술력을 바탕으로 연구/제작된 해군 무기체계를 유지하기 위해서는 이와같은 정비 지원이 무엇보다 중요하다. 해군에서는 효과적인 정비지원을 위해 수개의 정비지원부대를 조직하여 운용하고 있다. 원활한 정비지원부대의 운용을 위해 다년간 기술력을 축적한 정비인원의 중도 이탈을 예방하는 것이 요구되므로, 본 논문에서는 머신러닝을 적용하여 해군 정비지원부대의 퇴직자 예측 모델을 제안하였다. 정비인력의 만족도와 관계가 있을 것으로 예상되는 봉급, 특근율 등을 변수로 사용하였고, F1 Score를 통해 모델의 성능을 평가한 결과 0.7이상의 높은 성능을 보였다. 이 모델을 통해 조기 퇴직이 예상되는 그룹의 공통 개선소요를 파악하여 사전 조치가 가능할 것으로 판단하였다.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.11
• /
• pp.1608-1614
• /
• 2022

As competition between universities intensifies due to the recent decrease in the number of students, it is recognized as an essential task of universities to predict students who are underperforming at an early stage and to make various efforts to prevent dropouts. For this, a high-performance model that accurately predicts student performance is essential. This paper proposes a method to improve prediction performance by removing or amplifying abnormal data in a classification prediction model for identifying underperforming students. Existing anomaly data processing methods have mainly focused on deleting or ignoring data, but this paper presents a criterion to distinguish noise from change indicators, and contributes to improving the performance of predictive models by deleting or amplifying data. In an experiment using open learning performance data for verification of the proposed method, we found a number of cases in which the proposed method can improve classification performance compared to the existing method.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.6
• /
• pp.487-492
• /
• 2022

Universities are looking for various methods to enhance educational competence level suitable for the rapidly changing social environment. This study suggests a method to promote academic and educational achievements by reducing drop-out rate from their majors through implementation of pre-survey of satisfaction that revised and complemented survey items. To supplement the CQI method implemented after a general satisfaction survey, a pre-survey of satisfaction was carried out. To consolidate students' competences, this study made prediction and analysis of data with more importance possible using the Random Forest of the machine learning technique that can be applied to AI Medici platform, whose design is underway. By pre-processing the pre-survey of satisfaction, the students information enrolled in classes were defined as an explanatory variable, and they were classified, and a model was created and learning was conducted. For the experimental environment, the algorithms and sklearn library related in Jupyter notebook 3.7.7, Python 3.7 were used together. This study carried out a comparative analysis of change in educational satisfaction survey, carried out after classes, and trends in the drop-out students by reflecting the results of the suggested method in the classes.