• Journal of the Korea Society of Computer and Information
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• v.22 no.10
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• pp.9-17
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• 2017

The student dropout prediction is an indispensable for many intelligent systems to measure the educational system and success rate of all university. Therefore, in this paper, we propose an intelligent dropout prediction system that minimizes the situation by adopting the proactive process through an effective model that predicts the students who are at risk of dropout. In this paper, the main data sets for students dropout predictions was used as questionnaires and university information. The questionnaire was constructed based on theoretical and empirical grounds about factor affecting student's performance and causes of dropout. University Information included student grade, interviews, attendance in university life. Through these data sets, the proposed dropout prediction model techniques was classified into the risk group and the normal group using statistical methods and Naive Bays algorithm. And the intelligence dropout prediction system was constructed by applying the proposed dropout prediction model. We expect the proposed study would be used effectively to reduce the students dropout in university.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.137-146
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• 2023

The dropout of university freshmen is a very important issue in the financial problems of universities. Moreover, the dropout rate is one of the important indicators among the external evaluation items of universities. Therefore, universities need to predict dropout students in advance and apply various dropout prevention programs targeting them. This paper proposes a method to predict such dropout students in advance. This paper is about a method for predicting dropout students. It proposes a method to select dropouts by applying logistic regression using a shift sigmoid classification function using only quantitative data from the first semester of the first year, which most universities have. It is based on logistic regression and can select the number of prediction subjects and prediction accuracy by using the shift sigmoid function as an classification function. As a result of the experiment, when the proposed algorithm was applied, the number of predicted dropout subjects varied from 100% to 20% compared to the actual number of dropout subjects, and it was found to have a prediction accuracy of 75% to 98%.

• Journal of Engineering Education Research
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• v.15 no.5
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• pp.98-107
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• 2012

As the dropout rate of university students is gradually increasing, the studies on exploring the status, characteristics, reasons, and countermeasures of dropout of university students are currently grabbing high attention. This paper analyzes the relationship between the admission types and dropout of university students, mainly focused on engineering students. The analysis shows that the dropout rate of engineering students admitted through the scheduled-time admission procedures is quite higher than that of students admitted through non-scheduled-time admission procedures, the dropout rate of engineering students admitted from the vocational high schools is higher than that of students from the academic high schools, and the dropout rate of engineering students admitted from the liberal art high school tracks is higher than that of students from the natural science high school tracks. From the results, we could find out that student-support programs need to be carefully provided for the engineering university students according to their admission types and underlying backgrounds.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.2
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• pp.550-563
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• 2016

This study examined well-being as a mediator between self-discrepancy and dropout intention of junior college Student. 270 students in Busan answered the questionnaire about self-discrepancy, well-being, dropout intention. Structural equation modeling indicated that there were the complete mediating effect of well-being in the relationship between self-discrepancy and dropout intention. It indicated discrepancy between individuals' representation of their actual self(their actual self-state) and their representation of individual's hopes and aspirations(their ideal self-guide) affects junior college students' dropout intention, and well-being mediate process of self-discrepancy leading to dropout intention. This conclusion provide the significant implications that help preparing psychosocial intervention strategy for junior college students to decrease dropout intention and intervention strategy to enhance their well-being.

• Journal of Korean society of Dental Hygiene
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• v.22 no.2
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• pp.143-151
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• 2022

Objectives: This study investigates dropout intention and the structural relationship between the dental hygienist role and satisfaction with the study major perceived by dental hygiene students. Methods: A survey was conducted on 269 dental hygiene students. The survey items covered general characteristics, department choice motivation, the desirability of dental hygienist career, practice clinical experience, perception of dental hygienist role, satisfaction with study major, and dropout intention. Independent sample t-test, one-way ANOVA, Mann-Whitney U test, multiple linear regression analysis, and structural equation modeling were used for statistical analysis. Results: The dropout intention level of dental hygiene students was 2.4 out of 5.0. Satisfaction with study major partially mediates perception of dental hygienist role and dropout intention (direct effect=0.182, p=0.024, indirect effect=-0.437, p=0.010). Perception of dental hygienist role (β=-0.255, p=0.010) and satisfaction with study major (β=-0.661, p=0.010) showed a negative relationship with dropout intention. The factor most affecting dropout intention was satisfaction with study major. Dropout intention was high when selecting a major based on external motivations (β=-0.448, p<0.001). Conclusions: Perception of dental hygienist role and satisfaction with study major directly or indirectly affect dropout intention. Therefore, improving satisfaction with study major and improving the perception of dental hygienists will help reduce dropout intention.

• The Journal of Korean Medicine
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• v.32 no.4
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• pp.128-138
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• 2011

Objective: This study aimed at providing preliminary data useful in reducing participant dropout and improving the quality of clinical trials, by analyzing the factors related to dropout. Methods: The data came from 15 acupuncture and/or moxibustion clinical trials (n=638; August 2005 to December 2009). Logistic regression analysis was used to reveal factors influencing participant dropout. Results: Gender, age, treatment method (intervention), treatment frequency, availability of follow-up, and presence of compensation treatment for the control group were factors influencing participant dropout. Conclusion: Subsequent studies of large-scale acupuncture and moxibustion clinical trials should address dropout factors that consider the character of each clinical trial, or general characters like participants' gender, age, occupation, and diverse diseases.

• 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.

• The Journal of Bigdata
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• v.4 no.2
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• pp.175-183
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• 2019

Drop-out issue is one of the challenges of cyber university. There are about 130,000 students enrolled in cyber universities, but the dropout rate is also very high. To lower the dropout rate, cyber universities invest heavily in learning analytics. Some cyber universities analyze the possibility of dropout and actively support students who are more likely to drop out. The purpose of this paper is to identify the learning data affecting the dropout prediction index. As a result of the analysis, it is confirmed that number of lessons(progress), credits, achievement and leave of absence have a significant effect on dropout rate. It is necessary to increase the accuracy of the prediction model through post-test on the student dropout prediction index.

• The Journal of Korean Medicine
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• v.37 no.3
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• pp.62-73
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• 2016

Objectives: Dropout and weight regain are common problems in most obesity treatments. The purpose of this study was to review previously published study results of the predictive factors associated with dropout during weight loss treatment and weight loss maintenance after successful weight loss. Methods: Authors searched for the articles related to dropout and weight loss maintenance, published from 2007 to 2016 found on Pubmed, Scopus, RISS, and KISS. A total of 19 articles were finally selected. From the study results, unchangeable and changeable predictors were extracted, and these predictors were examined according to dropout and weight loss maintenance categories. Results: The unchangeable predictors of dropout were younger age, lower education level and female, whereas the changeable predictors of dropout were lower initial weight loss, symptoms of depression and body dissatisfaction. The strongest factor for predicting the dropout was initial weight loss. The unchangeable predictors of weight loss maintenance were old age, male and family history of obesity, whereas the changeable predictors of weight loss maintenance were regular exercise, dietary restraint, self-weighing and low depressive symptoms. Initial weight loss, depressive symptoms, body image, dietary restraint, physical activity, weight loss expectation and social support were considered to be dominant factors for weight loss treatments. Conclusions: Our review results suggest that unchangeable and changeable predictors of dropout and weight loss maintenance should be carefully examined during treatments of obesity.

• The Journal of the Korea Contents Association
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• v.12 no.10
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• pp.216-226
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• 2012

The current study investigated delinquent school- dropout adolescents and general dropouts' differences in individual, social factors and experiences after school dropout. Data was collected through a nationwide survey(N=209) from dropout adolescents. Findings reveal that gender, age, disabilities, work experience parent cohabitation, and residential area were significant in the individual factor. Dropout time, social agency, school return experience, and GED exam pass were significant in the social factors. Groups showed differences in experiences after dropout, and self evaluation while the general group had needs for vocational education. Dropouts wanted to go back to school. Implications such as focusing on differences of each group and developing various education system and policies are needed. Limitations and implications of the study are discussed.