• 산업융합연구
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• 제21권6호
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• pp.23-35
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• 2023

본 연구의 목적은 다문화청소년의 이중문화수용이 학업중단의도에 미치는 영향과 자아존중감의 매개효과를 설명하는 데 있다. 분석을 위해 다문화패널(MAPS) 8차년도(2018) 자료를 사용하였으며 1,105명을 대상자로 선정하여 회귀분석과 sobel test 등의 분석방법을 통해 검증하였다. 분석결과, 첫째, 다문화청소년의 이중문화수용은 학업중단의도를 낮추는 것으로 나타났다. 둘째, 다문화청소년의 한국문화수용과 학업중단의도와의 관계에서 자아존중감은 부분매개 역할을 하는 것으로 확인되었다. 셋째, 다문화청소년의 외국문화수용과 학업중단의도와의 관계에서 자아존중감은 완전매개 역할을 하는 것으로 나타났다. 이상의 연구결과를 토대로 다문화청소년의 학업중단의도를 낮추고 자아존중감을 향상시키기 위한 실천적 방안을 제시하였다.

• 사회복지연구
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• 제42권3호
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• pp.57-83
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• 2011

본 연구는 10대 미혼모가 경험한 학업중단의 의미를 밝히기 위한 연구이다. 질적연구의 방법으로 분석한 결과, 그들이 경험한 학업중단의 의미가 일차적으로 그들의 "신분과 지위 박탈" 의 문제로 재정의 되었는데, 이는 곧 제도화된 "학력사회로부터의 일방적인 배제" 라는 것을 의미한다. 또 이러한 배제는 또 다른 사회적 배제의 내적 기제로 작동하고 있다는 점, 또한 그들의 여생에서도 그럴 가능성-학업 중단이 평생의 굴레로 작용할 수 있는-이 농후하다는 시사점도 함께 도출할 수 있었다. 이와 함께 10대 미혼모의 학업중단의 문제가 사회적 정상성의 기준에서 벗어난 임신이라는 행동과 맞물려 "사회가 일방적인 기준을 적용했다" 라는 주요한 시사점의 도출을 통해 그들의 임신은 철저히 '타자화' 되는 삶으로 진입할 수밖에 없는 결정적 계기가 되었다는 사실을 발견하였다. 이와 같은 결과를 바탕으로 본 연구는 10대 미혼모들이 경험한 주관적 의미의 세계를 조명했다는 면에서 의의를 가진다.

• 아동학회지
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• 제30권6호
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• pp.391-403
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• 2009

This study examined the concept and status, research issues, and pragmatic and policy issues of school-dropout adolescents. As the number of school-dropout adolescents has been increasing in Korea since 2006, more attentions have been given to these adolescents academically, intervention and policy-wise. Some of the research topics on them include types of school-dropouts, their socio-environmental factors, and reasons for the increase of school-dropouts. In reality, the government is required to provide them with opportunities to cope with their dropping out of schools by preparing the career guidance for them and to resolve the issues of their returning to or continuing in school education and their welfare.

• 한국컴퓨터정보학회논문지
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• 제23권5호
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• pp.65-72
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• 2018

This study analyzes college dropout cases to reduce its rate. The analysis is preferentially carried out by figuring out our current situation of college dropout rate in pertinent cases and all around country's. Based on the current states, statistical analysis is accomplished as follows; analyzing the characteristic differences between the being in school's and the dropouts' by T-Test, determining the influence factor by logistic regression analysis and drawing the target group for special treatments through these statistical analysis. To reduce dropout rate, several measures could be adopted; focused counseling for each target group, special monitoring for students on leave of absence and opening major subjects for improving relationship between students and professors. The measures suggested by the analysis through this study are expected to lower the dropout rates effectively in college or specific fields including engineering science.

• 한국아동복지학
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• 제59호
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• pp.209-234
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• 2017

본 연구는 학업중단의 원인을 학교로 보고, 고등학생의 학업중단이 학교마다 학교특성과 학업중단의 영향요인이 다를 것으로 보았다. 이에 학교에 초점을 맞춰 전국 고등학교의 학업중단 추세를 확인하고, 고등학교 학업중단의 변화양상에 따른 유형을 종단적으로 탐색하였다. 그리고 도출된 유형별로 학교의 일반적 특성을 예측하고, 학업중단에 영향을 미치는 주요 요인(학교폭력, 학교상담)의 변화 추이를 살펴보면서 학업중단에 대한 학교의 장기간의 노력과 결과를 되짚어 보았다. 이를 위하여 KERIS EDSS의 "중등학교 정보공시데이터"를 활용하였고, 연구에서는 2012년부터 2016년까지 전국 고등학교의 5년 간 자료를 최종 모형에 투입 분석하였다. 연구는 네 가지 목적에 의해 수행되었고, 그에 따른 결과는 다음과 같다. 첫째, 고등학교의 학업중단에 대한 종단적인 변화양상을 탐색하기 위하여 잠재성장모형으로 분석한 결과, 시간이 지날수록 전국 고등학교의 학업중단은 감소하는 추세를 보였다. 둘째, 고등학교의 학업중단 변화양상에 따른 유형을 성장혼합모형으로 분석한 결과, 학업유지형, 학업중단감소형, 학업중단지속형과 같은 3가지 유형이 도출되었다. 셋째, 도출된 유형별 학교의 일반적 특성을 다항로지스틱 분석으로 예측한 결과에서는 국공립일수록, 전문계고일수록, 국영수 기초학력미달 학생 수가 많을수록 학업중단지속형에 속할 확률이 높았고, 전체학생 수가 많을수록 학업유지형이나 학업중단감소형에 속할 가능성이 높은 것으로 나타났다. 마지막으로 도출된 세 유형별로 학교폭력과 학교상담의 변화추이를 다 집단 성장혼합모형으로 분석한 결과에서 특히 학업중단감소형의 추이가 주목된다. 학업중 단감소형은 초기에 높았던 학교폭력 심의건수와 가해학생 수가 시간이 지날수록 매년 감소하는 양상을 보였고, 이와 함께 학교의 전문상담교사 배치수를 매년 늘리고, 또래상담을 지속적으로 활성화시켰음을 확인하였다. 이러한 점이 초기 학업중단이 가장 높았던 고등학교가 학업중단감소형 학교가 된 이유일 것으로 사료된다.

• Journal of Information Processing Systems
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• 제17권3호
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• pp.630-644
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• 2021

Educational data analysis is attracting increasing attention with the rise of the big data industry. The amounts and types of learning data available are increasing steadily, and the information technology required to analyze these data continues to develop. The early identification of potential dropout students is very important; education is important in terms of social movement and social achievement. Here, we analyze educational data and generate predictive models for student dropout using logistic regression, a decision tree, a naïve Bayes method, and a multilayer perceptron. The multilayer perceptron model using independent variables selected via the variance analysis showed better performance than the other models. In addition, we experimentally found that not only grades but also extracurricular activities were important in terms of preventing student dropout.

• 한국학교보건학회지
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• 제34권3호
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• pp.151-160
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• 2021

Purpose: The purpose of this study was to identify predictors of suicidal attempts in adolescents over 5 years after school dropout. Methods: The data of the Panel Survey of School Dropouts (of 2013 to 2017) conducted by the National Youth Policy Institute were analyzed. The analysis used the 2013 survey data as the baseline and examined suicidal attempts from 2013 to 2017. A total of 776 adolescents were included in the analysis. Descriptive statistics, 𝝌² test, t-test, and multiple logistic regression were carried out using SAS 9.2. Results: About 11% (87 out of 776) of the adolescents with an experience of dropout attempted suicide between 2013 and 2017. The risk of suicidal attempts was significantly lower in female (AOR: 0.57, 95% CI: 0.87~0.93) than in male adolescents. The higher the self-esteem, the lower the risk of suicidal attempts (AOR: 0.87. 95% CI: 0.78~0.97). The higher the depression level (AOR: 1.10, 95% CI: 1.05~1.16) and the rate of parental abuse (AOR: 1.09, 95% CI: 1.02~1.18), the higher the risk of suicidal attempts. Conclusion: The findings of the study suggest that those who are male, depressed, have low self-esteem or have been abused by their parents are at high risk of suicidal attempts among the adolescents with dropout experiences. Therefore, early intervention is necessary for those at high risk.

• 대한통합의학회지
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• 제12권2호
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• pp.155-166
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• 2024

Purpose : This study aims to identify key factors for predicting dropout risk at the university level and to provide a foundation for policy development aimed at dropout prevention. This study explores the optimal machine learning algorithm by comparing the performance of various algorithms using data on college students' dropout risks. Methods : We collected data on factors influencing dropout risk and propensity were collected from N University. The collected data were applied to several machine learning algorithms, including random forest, decision tree, artificial neural network, logistic regression, support vector machine (SVM), k-nearest neighbor (k-NN) classification, and Naive Bayes. The performance of these models was compared and evaluated, with a focus on predictive validity and the identification of significant dropout factors through the information gain index of machine learning. Results : The binary logistic regression analysis showed that the year of the program, department, grades, and year of entry had a statistically significant effect on the dropout risk. The performance of each machine learning algorithm showed that random forest performed the best. The results showed that the relative importance of the predictor variables was highest for department, age, grade, and residence, in the order of whether or not they matched the school location. Conclusion : Machine learning-based prediction of dropout risk focuses on the early identification of students at risk. The types and causes of dropout crises vary significantly among students. It is important to identify the types and causes of dropout crises so that appropriate actions and support can be taken to remove risk factors and increase protective factors. The relative importance of the factors affecting dropout risk found in this study will help guide educational prescriptions for preventing college student dropout.

• IEIE Transactions on Smart Processing and Computing
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• 제4권3호
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• pp.152-157
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• 2015

Various power supply noise sources in a system integrated circuit degrade the performance of a low dropout (LDO) regulator. In this paper, a capacitor-less low dropout regulator for enhanced power supply rejection is proposed to provide good power supply rejection (PSR) performance. The proposed scheme is implemented by an additional capacitor at a gate node of a pass transistor. Simulation results show that the PSR performance of the proposed LDO regulator depends on the capacitance value at the gate node of the pass transistor, that it can be maximized, and that it outperforms a conventional LDO regulator.

• 한국의류산업학회지
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• 제25권2호
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• pp.241-247
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• 2023

This study sought to investigate the effect of academic satisfaction on the dropout intention of cosmetology undergraduates. Analyzing the effect of academic satisfaction on career dropouts showed that the sub-factors of academic satisfaction-evaluation satisfaction, class satisfaction had a statistically significant part effect. Analyzing the effect of academic satisfaction on psychological factors for dropping out showed that the sub-factors of academic satisfaction have a statistically significant effect. Furthermore, regarding the effect of academic satisfaction on environmental factors, the sub-factors of academic satisfaction have a statistically significant effect on wealth. High satisfaction was shown to have no statistically significant effect on dropout intention. The results of the study showed that the higher the degree of satisfaction with the evaluation and the degree of satisfaction with the course of beauty majors, the more negative (-) the impact on dropout. For cosmetology majors, academic satisfaction is a subjective emotion felt through study at university and major. Students with high academic satisfaction are more likely to love their school and their work, and positively influence their intention to stay in school and reduce student dropout rates. Intention to drop out indicates the intention to lose interest and purpose in cosmetology college students. This is directly linked to the dropout rate of school students and requires steady research. Through this research, we hope that active discussions will be held on academic satisfaction and intention to drop out of university students specializing in cosmetology.