• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.88-95
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• 2021

This study aims to provide implications for establishing support policies for students by empirically analyzing data on university students dropouts. To this end, data of students enrolled in D University after 2017 were sampled and collected. The collected data was analyzed using topic modeling(LDA: Latent Dirichlet Allocation) technique, which is a probabilistic model based on text mining. As a result of the study, it was found that topics that were characteristic of dropout students were found, and the classification performance between groups through topics was also excellent. Based on these results, a specific educational support system was proposed to prevent dropout of university students. This study is meaningful in that it shows the use of text mining techniques in the education field and suggests an education policy based on data analysis.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.171-178
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• 2020

Many countries are establishing and operating blended learning that combines the advantages of online and offline education. However, online education lecture-based Mooc courses have a very low level, with a graduation rate of less than 5-10%. Therefore, in order to increase the graduation rate of students taking online Mooc distance education lectures that anyone can easily take lectures anytime, anywhere on the web-based basis, it is necessary to introduce automatic analysis of students' understanding level of lectures and an automatic academic warning system. Moreover, in order to enter an advanced education country, it is necessary to develop an automatic judgment SW for wrong answer rate, automatic summary SW for lectures, and automatic analysis SW education for lecture-based weak subjects based on mixed learning levels. In order to improve this problem, in this paper, we proposed and simulated an automatic summarization system for lecture contents, an automatic warning system for incorrect answers, and an automatic judgment algorithm for weak subjects.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.4
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• pp.971-983
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• 2016

This study is a preliminary research to develop an individual learning coaching program for college students who received academic probation. It aims to test applicability as a program in the future, and t revise it and make up for its problems. To achieve the research aim, this study, based on self-directed learning, constructed the program dividing it into two kinds: the first basic learning special lecture and the second individual learning coaching. This program used those students in universities in Gyeongbok province who received two or more scholastic probations from the second semester of 2012 to the second semester of 2014, and who were judged by professors who had interviewed them as those who needed learning coach. The researcher of this study introduced those students about the program and schedule. And, this study did in-depth analysis for the six students who attended the first and second parts of the program. It was found that those students understood the importance and necessity of self-directed learning, and tried to apply it to actual learning process and overcome learning difficulty. Based on such findings, this study suggested the development of a program for students who receive academic probation and ideas on how to develop it.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.624-633
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• 2020

This study investigated the effects of major selection motives and occupational values on employment preparation behavior among paramedic students. The study also assessed the role of mentoring in enhancing preparation for employment. During the period of five days, from December 2 to 6, 2019, 300 students randomly selected by the researcher, were provided with a self-administered questionnaire, after taking written consent from them. The responses of 286 respondents were analyzed using the SPSS WIN 12.0 program. Fourteen responses were not included in the analysis due to lack of credible answers. The analysis revealed that personal motivation, intrinsic and extrinsic work values had a positive effect on employment preparation behavior and mentoring had a moderating effect. Therefore, continuous individual and group counseling is required to improve employment preparation behavior and special lectures and mock interviews in a mentoring program based on major selection motivations and occupational values are necessary.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.395-402
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• 2024

The purpose of this study is to verify the effect of the intensive support program for junior college students with low academic performance on students' learning motivation and self-learning efficacy, and to explore its meaning. This study was conducted with 46 students who participated in the JUMP-UP program supported by the D University Teaching and Learning Development Center in Busan for backers and students with low grades. The research question of this study is, first, does the JUMP-UP program affect the reinforcement of the learning motivation of junior college students? Second, does the JUMP-UP program affect the self-learning efficacy of junior college students? As a result of examining the effectiveness by conducting a survey before and after participating in the JUMP-UP program, the JUMP-UP program showed statistically significant changes in all items of participating learners' learning motivation and self-learning efficacy. Through this, it can be seen that an intensive support program such as the JUMP-UP program is valuable as a support program suitable for improving the learning motivation and self-learning efficacy of vocational college students suffering from low academic performance.