• Journal of Industrial Convergence
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• v.19 no.4
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• pp.95-102
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• 2021

This study aims to verify the effect of mother's career-related behavior on the intention of multicultural youths to school dropout intention and the mediating effect of academic adaptation. To this end, 1,121 middle school seniors were sampled in the 7th (2017) data of the Multicultural Youth Panel Survey, and the influence relationship of the model presented as a three-step method of analysis of the mediated effects of Baron & Kenny and the Sobel test were conducted. First, the analysis showed that mother's support, a subfactor of mother's career-related behavior, had a negative effect on dropout intention, and that mother's interference had a positive effect. Second, academi adaptation has been shown to have a negative effect on dropout intention. Third, mother's support, a subfactor of mother's career-related behavior, showed a positive influence on academi adaptation, and mother's interference showed a negative effect. Fourth, academi adaptation has been shown to be mediated in the relationship between career-related behavior and dropout intention. Based on the above results, practical implications were presented.

• The Journal of the Korea Contents Association
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• v.16 no.11
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• pp.63-71
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• 2016

The purpose of this study is to investigate factors affecting dropout intention based on education satisfaction survey analysis of local J university. Total 7,248 survey data which has high trustability were analyzed. Analysis of variance was performed to verify differences between each grade and credits level. There are significant differences between the year grade and credit level. Especially the result show that the satisfaction of freshman is higher than the other grade students. To verify relation between intention to dropout and satisfaction of university education logistic regression analysis method has been applied and satisfaction of academic guidance, vocational guidance, environment of education and self-satisfaction of university life are significantly related to the dropout intention. The most important variable is self-satisfaction of university life which determine dropout intention through decision tree analysis.

• Journal of the Korea society of information convergence
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• v.1 no.1
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• pp.47-54
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• 2008

This study analyzed the status and causes for the dropouts of college based on the survey conducted among 14,210 freshmen attending D College, other than the supernumerary special selection, from 2001 through 2005. A significant difference was shown in all items of general characteristics. The dropout rate of women, generally selected and general highschool graduated were higher than for men, specially selected and special high school graduated, respectively. The most dropouts were due to Not Return(40.16%), followed by Unenrolled(32.98%), Voluntary Leave(26.05%) and Expelled(0.81%) in order. In the distribution of the central tendency values measured from the entire subjects, the high school records and the days of absence showed a positive skewness, while the college records showed a negative skewness with the data mostly around a higher grade. The standard deviation indicating that the dropouts got the scores higher than those of the continuing students demonstrated that there was relatively insignificant difference in scores between two groups. It was demonstrated that both the high school records and the days of absence affected the dropout. The lower the high school records were, and the more the days of absence were, the more influence both items had on the dropout. The influence degree of each item was similar. Lower the scores were in terms other than the first term in the freshmen year, the more influence it had on the dropout. The most dropouts were influenced by the scores of the freshmen year, followed by the credits of the second term, the scores of the first term, the scores of the second term, and the credits of the first term in the freshmen year. Among the general characteristic items, the most dropouts were influenced by the course of study, followed by the gender. The effect of other items was insignificant.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.49-58
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• 2023

Dropouts of students not only cause financial loss to the university, but also have negative impacts on individual students and society together. To resolve this issue, various studies have been conducted to predict student dropout using machine learning. This paper presents a model implemented using DNN (Deep Neural Network) and LGBM (Light Gradient Boosting Machine) to predict dropout of university students and compares their performance. The academic record and grade data collected from 20,050 students at A University, a small and medium-sized 4-year university in Seoul, were used for learning. Among the 140 attributes of the collected data, only the attributes with a correlation coefficient of 0.1 or higher with the attribute indicating dropout were extracted and used for learning. As learning algorithms, DNN (Deep Neural Network) and LightGBM (Light Gradient Boosting Machine) were used. Our experimental results showed that the F1-scores of DNN and LGBM were 0.798 and 0.826, respectively, indicating that LGBM provided 2.5% better prediction performance than DNN.

• Journal of Korea Entertainment Industry Association
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• v.15 no.8
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• pp.279-290
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• 2021

As the university's academic management was not carried out smoothly due to COVID-19, and most of them were conducted as non-face-to-face classes, students' dropout is steadily increasing. In this study focus group interviews were conducted to analyze physics students and professors' recognition of the COVID-19 non-face-to-face class environment. Based on the results, the implications of non-face-to-face classes for physics education were presented. Physics students described their feelings about un-tact teaching as 'the class in which the body is comfortable but the mind is uncomfortable', 'a person who is smarter than me seems to explain a book, reading it' and 'a short clip lecture which may be comfortable but cause losses to me', while the professors also described them as 'a fully transformed class system' and 'a online class putting much burden on me'. Regarding school dropout, students said that the concerns about dropout during non-face-to-face classes were deepened about transfer or transfer. The professors said that the department atmosphere had lost vitality due to the increase in non-face-to-face classes and academic dropouts, and had a lot of worries because of the recruitment rate and external university evaluation. The implications of the COVID-19 non-face-to-face class situation for physics education suggest that it is required to strengthen the interaction between professors and students, finding ways to enhance the sense of reality to supplement laboratory classes and giving opportunities to professors to share their pedagogical contents knowledge in physics.

• Journal of Technologic Dentistry
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• v.41 no.3
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• pp.221-232
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• 2019

Purpose: This experiment aims to provide the fundamental resources in developing a programme intended to prevent students from dropping out of their academics by promoting students to develop an optimistic psychological state, through analysis of the factors that influence students' commitment to their major. Methods: A self-administered questionnaire was conducted from $19^{th}$ of November of the year 2018, till $1^{st}$ of December of the same year, with dental technology students located in W city as the subject. 261(93.2%) of the participants' responses were used for the final analysis. Results: A negative association between factors of commitment to major and factors of academic dropout decision were portrayed to be of statistical significance (p<.01), and factors of commitment to major that influence dropping out of their academics were shown to be that of 'autotelic experience' (p<.001) with a negative ( - ) relationship, and 'change in a sense of time' (p<.01) with a positive ( + ) relationship of statistical significance, while the explanatory power of the model was shown to be 33.6%. Conclusion: In order to prevent dental technology students from dropping out of their academics, following their entrance, To achieve this, the department must consider the implementation of, aside from subject matters of the major, other various extra-curricular programmes, and programmes in which the supervisor is consistently providing consultations that are tailored to each individual student.

• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.89-92
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• 2008

This study analyzed the status and causes for the dropouts of college based on the survey conducted among 14,210 freshmen attending D College, other than the supernumerary special selection, from 2001 through 2005. A significant difference was shown in all items of general characteristics. The dropout rate of women, generally selected and general high school graduated were higher than for men, specially selected and special high school graduated, respectively. The most dropouts were due to Not Return(40.16%), followed by Unenrolled(32.98%), Voluntary Leave(26.05%) and Expelled(0.81%) in order. In the distribution of the central tendency values measured from the entire subjects. the high school records and the days of absence showed a positive skewness. while the college records showed a negative skewness with the data mostly around a higher grade. The standard deviation indicating that the dropouts got the scores higher than those of the continuing students demonstrated that there was relatively insignificant difference in scores between two groups.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.306-312
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• 2021

The main goal of higher education institutions is to present a high level of quality education to its students. This study uses data mining techniques to extract educational data from cumulative databases and used them to make the right decisions. This paper also aims to find the factors affecting students' academic performance in Majmaah University, KSA, during 2010 - 2017 period. The study utilized a sample of 6,158 students enrolled from two colleges, males and females. The results showed a high percentage of stumbling and dismissed between graduate and regular students where more than 62.5% failed to follow the plan. Only 2% of students scored distinction during their study of all graduated since their grade point average, secondary level, was statistically significant, where p<0.05. Dismissed percentage was higher among males. These results promoted some recommendations in which decision-makers could take them in considerations for better improvement of academic achievements: including of specialized programs to follow-up in regards to stumbling and failure. Utilization of different communication tools are needed to activate academic advisory for dismiss and dropout evaluation.

• Journal of Engineering Education Research
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• v.27 no.1
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• pp.3-12
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• 2024

The degree-linked programs for employees, operated by joint training centers in specialized universities that have implemented work-study integrated programs, are educational programs that require an annual government budget of around 80 billion KRW. However, the 70+ universities running these programs face issues such as a decline in academic achievement and an increase in dropout rates among students. In this paper, I conducted multiple regression analysis based on observed and measured information to examine whether the participating students in these programs are achieving an appropriate level of academic performance and to identify the factors that universities need to invest in to achieve that level. To do this, I hypothesized a causal relationship between the university's input factors and students' academic achievement, and used the SPSS program to analyze the statistical data, confirming the validity of the hypothesis. The collected data for the study were obtained through a survey developed using a Likert 4-point scale, which quantified the distribution of grades among students enrolled in IT-related departments offering the degree-linked programs for employees and the emotional contact efforts made by the universities to motivate them for academic success. Particularly, through the results of multiple regression analysis, it was confirmed that these input factors, unlike those for students in general education programs, require more personalized and frequent interactions.

• Asia-Pacific Journal of Business
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• v.13 no.3
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• pp.361-373
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• 2022

Purpose - This paper analyzes the student determinants of college non-completion and estimates the effects of each determinant on college non-completion. Design/methodology/approach - We use student panel data from a large Korean university from 2011 to 2021. Our results are from estimation of fixed-effects logit model. Findings - The results show that grade point average, participation in extracurricular activities, the number of counseling sessions with teachers, and financial aid are the main determinants of college non-completion. Academic probation, which is defined as any person who has a cumulative grade point average below a one point seven five, increases the non-completion rate by 2.6 percentage points and an one-point rise in extracurricular activities index reduces the rate by 0.1 percentage points. The effects of each determinant are heterogeneous across student sub-groups which are separated by gender, nationality, and academic discipline. Research implications or Originality - Tailored support programs for academically discouraged students that incorporate student characteristics and backgrounds are necessary to increase college completion rates and degree attainment.