• Journal of Industrial Convergence
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• v.21 no.6
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• pp.23-35
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• 2023

This study aimed to examine the effect of bicultural acceptance attitudes in Korean culture and mother's countries, which are sub-factors of multicultural adolescents' bicultural acceptance, on their intention of school dropout through self-esteem. For the analysis, the 1,105 subjects were selected from the 8th(2018) the Multicultural Adolescents Panel Study(MAPS). The data collected were analyzed by various research methods including correlation analysis, regression analysis and sobel test. The main results are as follows. First, bicultural acceptance of multicultural adolescents reduced their intention of school dropout. Second, self-esteem had a partial mediating effect in the causal relationship between multicultural adolescents' bicultural acceptance in Korean culture and intention of school dropout. Third, the effect of bicultural acceptance in mother's countries of multicultural adolescents on intention of school dropout was completely mediated by their self-esteem. On the basis of the findings, practical programs to decrease the intention of school dropout and to enhance self-esteem of multicultural adolescents were suggested.

• Korean Journal of Social Welfare Studies
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• v.42 no.3
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• pp.57-83
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• 2011

The aim of this study is to elucidate the meaning of school dropout which teenager unmarried mothers have been experiencing. Thus, the researchers conducted in-depth interviews of 6 unmarried mothers to portray vividly their voices and the data were analyzed using a qualitative case study. Acording to the results, the meaning of school dropout of teenager unmarried mothers was redefined as the matter of "identity and status deprivation". Also, their school dropout expediences should be analyzed in the more extended perspective beyond the negative meaning of the existing studies. This meant " the one sided exclusion from academic community." This could be drawn with the implications that the exclusion acted as the inner mechanism of another social exclusion and their school dropout served as the bondages of their lifetime. That is, the problem of school dropout has the meaning of 'the present tense' and 'the future tense' simultaneously. Within this context, the phenomenon in which they experienced was acting as the foundation of a continuous exclusion and discrimination. Also, it was found that our society applied its standards to them unilaterally and they came to live as otherness through their pregnancy. Based on these results, this study has an important significance in that it overcame the limitations of previous research and investigated their subjective worlds.

• Korean Journal of Child Studies
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• v.30 no.6
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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.

• Journal of the Korea Society of Computer and Information
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• v.23 no.5
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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.

• Journal of the Korean Society of Child Welfare
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• no.59
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• pp.209-234
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• 2017

This study viewed schools as a cause of students dropping out and posited that dropping out of high school would vary depending on the characteristics and influencing factors of the school from which students were dropping out. Therefore, focusing on schools, we longitudinally investigated the change patterns of school dropout across high schools in the country, and the types of changes in dropping out of high school. In addition, we predicted the general characteristics of schools according to the type of school students were dropping out from, looked at the changes in the major factors (i.e., school violence and school counseling) affecting school dropout, and reviewed schools' long-term efforts and outcomes in relation to school dropout. For this purpose, KERIS EDSS's "Secondary School Information Disclosure Data" were used. The final model included data collected five years20122016) from high schools across the country. The results were as follows. First, in order to examine the longitudinal change patterns of dropping out of high schools, a latent growth models analysis was conducted, and it revealed that, as time passed, the dropout rate decreased. Second, growth mixture modeling was used to explore types according to the change patterns of the school students were dropping out from. The results showed three types: the "remaining in school" type, the "gradually decreasing school dropout" type, and the "increasing school dropping out". Third, the multinomial logistic regression was conducted to predict the general characteristics of schools by type. The results showed that public schools, vocational schools, and schools with a large number of students who have below the basic levels in Korean, English and mathematics were more likely to belong to the "increasing school dropout" type. Further, the larger the total number of students, the higher the probability of belonging to the "remaining in school" type or the "gradually decreasing school dropout" type. Lastly, growth mixture modeling was used to analyze the trend of school violence and school counseling according to the three types. The focus was on the "gradually decreasing school dropout" type. In the case of the "gradually decreasing school dropout" type, it was found that as time passed, the number of school violence cases and the number of offenders gradually decreased. In addition, in terms of change in school counseling the results revealed that the number of placement of professional counselors in schools increased every year and peer counseling was continuously promoted, which may account for the "gradually decreasing school dropout" type.

• Journal of Information Processing Systems
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• v.17 no.3
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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.

• Journal of the Korean Society of School Health
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• v.34 no.3
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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.

• Journal of The Korean Society of Integrative Medicine
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• v.12 no.2
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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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• v.4 no.3
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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.

• Fashion & Textile Research Journal
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• v.25 no.2
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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.