• Journal of Information Science Theory and Practice
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• v.11 no.1
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• pp.14-30
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• 2023

The purpose of this study is to compare research trends in the information and communication technology (ICT) field between North and South Korea and analyze the differences by using data mining. Frequency analysis, clustering, and network analysis were performed using keywords from seven South Korean and two North Korean ICT academic journals published for five years (2015-2019). In the case of South Korea (S. Korea), the frequency of research on image processing and wireless communication was high at 16.7% and 16.3%, respectively. North Korea (N. Korea) had a high frequency of research, in the order of 18.2% for image processing, 16.9% for computer/Internet applications/security, and 16.4% for industrial technology. N. Korea's natural language processing (NLP) sector was 11.9%, far higher than S. Korea's 0.7 percent. Student education is a unique subject that is not clustered in S. Korea. In order to promote exchanges between the two Koreas in the ICT field, the following specific policies are proposed. Joint research will be easily possible in the image processing sector, with the highest research rate in both Koreas. Technical cooperation of medical images is required. If S. Korea's high-quality image source is provided free of charge to N. Korea, research materials can be enriched. In the field of NLP, it calls for proposing exchanges such as holding a Korean language information conference, developing a Korean computer operating system. The field of student education encourages support for remote education contents and management know-how, as well as joint research on student remote evaluation.

• Journal of Korean Home Economics Education Association
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• v.30 no.3
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• pp.111-127
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• 2018

The purpose of this study was to analysis the home economics education curriculum from the first national curriculum to the 2015 revised curriculum using text mining techniques used in big data analysis. The subjects of the analysis were 10 curriculum texts from the first national curriculum to the 2015 revised curriculum via the National Curriculum Information Center. The major findings of this study were as follows; First, the number of data from the 4th curriculum to the 2015 revised curriculum gradually increased. Second, as a result of extracting core concept of the curriculum, there were core concept words that were changed and maintained according to the curriculum. 'Life' and 'home' were core concepts that persisted regardless of changes in the curriculum, after the 2007 revised curriculum, 'problem', 'ability', 'solution' and 'practice' were emphasized. Third, through core concept network analysis for each curriculum, the relationship between core concepts is represented by nodes and lines in each home economics curriculum. As a result, it was confirmed that the core concepts emphasized by the times are strongly connected with 'life' and 'home'. Based on these results, this study is meaningful in that it provides basic data to form the identity and the existing direction of home economics education.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.129-138
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• 2023

The purpose of this study is to explore factors that directly affect the employment of college graduates. To this end, employment data of graduates of private four-year university in Daegu metropolitan area and Gyeongsangbuk-do province were collected from 2019 to 2021, filtered data using a RapidMiner, and analyzed by applying a decision tree model. As a result of the study, long-term internship for more than 12 weeks, TOEIC score of 787.5 or higher was advantageous for employment, and if there was no TOEIC score, the graduation average score was 3.67 or higher, so the possibility of employment was high. Even if the TOEIC score was low, it was advantageous for employment if participating in the contest and continuous professor counseling, and even if the average graduation score was low, the possibility of employment was high if actively participating in the comparison program. This study can present a job education guide based on actual data to university management and use it to establish policies to support employment of college students.

• The Journal of Sustainable Design and Educational Environment Research
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• v.19 no.2
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• pp.11-20
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• 2020

The goal of this study was to investigate the implementation and related issues of the school space innovation issued by key Korean mass media using text mining. To accomplish this goal, this study collected 519 news articles associated with the school space innovation issued by 54 Korean mass media companies. Based on this data, this study performed the frequency analysis and network analysis regarding the keywords. Based on the findings, the characteristics of school space innovation are summarized as follows: First, school space innovation has progressed in response to future education. Second, users are actively participating in school space innovation. Third, experts are supporting the innovation of school space by establishing a cooperative system. Fourth, the community is actively considering the innovation of school space. Fifth, the main projects of the Ministry of Education and the Provincial Offices of Education are actively conducted in a mix of top-down and bottom-up approaches. The findings of this study will contribute to providing a clear direction for contemporary school space innovation and implications for future research agenda and implementation.

• Journal of Distribution Science
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• v.22 no.3
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• pp.71-81
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• 2024

Purpose: This study examines the impact of inclusive policies and green transformation on regional development of mining areas. Research design, data and methodology: We designed and utilized a structured questionnaire to collect data from a population of 300 individuals. The questionnaire was disseminated through Google Forms and consisted of five questions for each research variable. A total of 210 respondents completed the questionnaire, yielding a response rate of 70%. The sample was diverse in terms of gender and educational level Of the 210 respondents, 113 were female (53.8%) and 97 were male (46.2%). In terms of educational background, the sample was composed as follows: 13 individuals with a Doctorate degree (6.2%), 56 with a Master's degree (26.7%), 97 with a Bachelor's degree (46.2%), 22 with a Diploma (10.5%), and 22 with a High School education (10.5%). Results: The research outcomes highlight the significant influence of inclusive policies on driving the Distribution of green economic transformation. Emphasizing the pivotal role of inclusive distribution strategies, especially within the context of mining areas, the study sheds light on their crucial contribution to fostering regional development. Conclusion: These findings hold valuable implications for policymakers, industry stakeholders, and academics promoting environmentally conscious economic transformations.

• Journal of the Korean Home Economics Association
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• v.43 no.11 s.213
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• pp.225-234
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• 2005

The objective of this study was to develop a model for predicting Korean adult consumers who frequently eat food-away-from-home. A total of 7,032 adults aged 19 years and older from the 2001 National Health and Nutrition Survey in Korea were used as subjects. The data were analyzed using a data mining procedure including logistic regression and decile analysis. The model developed in the study was proven to be valid in predicting the consumers who frequently eat food-away-from home(once a day or more often). This model showed that consumers eating food-away-from-home frequently tend to be younger men, living in a big city, working full time, receiving more stress and eating snacks and fried food more frequently. The model could be used to identify targets for nutrition and related education and consumer segments for the marketing of restaurant businesses.

• The Journal of Korean Association of Computer Education
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• v.6 no.2
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• pp.107-120
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• 2003

In Web Based Instruction, as evaluation of learning process means individual student's learning activity, it demands data on learning time, pattern, participation, environment in a specific learning contents. The purpose of this paper is to reflect analysis results of individual student's learning status in achievement evaluation using the most suitable web log mining to settle evaluation problem of learning process, an issue in web based instruction. The contents and results of this study are as following. First, conformity item for learning status analysis is determined and web log data preprocessing is executed. Second, on the basis of web log data, I construct student's database and analyze learning status using data mining techniques.

• Journal of Information Technology Applications and Management
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• v.27 no.6
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• pp.153-170
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• 2020

The Educational Restitution Rate is an important parameter that determines the quality of university education. This paper analyzed data from 148 private universities over the 10 years from 2009 to 2018 using data mining techniques in Korea. A significant causal relationship is detected in the fixed effect model as a result of the panel estimation. And the scale of faculty expansion and fund management, which are the university evaluation indicators, and the size of basic funds, respectively, have a positive effect on the ERR, which is within the confidence interval. In the analysis, the more private universities improve the tuition dependence rate, the more decisively positive affecting ERR. As a result of nonparametric regression estimation, when the faculty expansion ratio is reinforced, the effect of economies of scale is detected in some sections, the improvement of the tuition dependence rate, and the result value is generated through the improvement that results are derived at a certain point in time. We hope that the university based on this study can be a basic Indicators for the diagnosis of basic competencies and policy of student-centered education.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.671-678
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• 2011

Data mining searches for interesting relationships among items in a given database. The methods of data mining are decision tree, association rules, clustering, neural network and so on. The decision tree approach is most useful in classification problems and to divide the search space into rectangular regions. Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, customer classification, etc. When create decision tree model, complicated model by standard of model creation and number of input variable is produced. Specially, there is difficulty in model creation and analysis in case of there are a lot of numbers of input variable. In this study, we study on decision tree using intervening variable. We apply to actuality data to suggest method that remove unnecessary input variable for created model and search the efficiency.

• Journal of Engineering Education Research
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• v.15 no.4
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• pp.41-47
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• 2012

Data mining and knowledge discovery techniques have shown to be effective in finding hidden underlying rules inside large database in an automated fashion. On the other hand, analyzing, assessing, and applying students' survey data are very important in science and engineering education because of various reasons such as quality improvement, engineering design process, innovative education, etc. Among those surveys, analyzing the students' views on science-technology-society can be helpful to engineering education. Because, although most researches on the philosophy of science have shown that science is one of the most difficult concepts to define precisely, it is still important to have an eye on science, pseudo-science, and scientific misconducts. In this paper, we report the experimental results of applying decision tree induction algorithms for analyzing the questionnaire results of high school students' views on science-technology-society (HS-VOSTS). Empirical results on various settings of decision tree induction on HS-VOSTS results from one South Korean university students indicate that decision tree induction algorithms can be successfully and effectively applied to automated knowledge discovery from students' survey data.