• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.618-620
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• 2021

The core competence is further growing in importance as a concept that must be continuously developed by individuals and should be reflected in the school curriculum. In this study, we analyze the relationship between core competence and graduation credits (learning ability) of students who have completed a core competence-centered curriculum for graduates of D-University, and reflect it in the curriculum of D-University and university education policy. The purpose is to improve. We plan to utilize the results of future analysis as materials for human resource development that matches the human resources image of D-University.

• Journal of Creative Information Culture
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• v.5 no.2
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• pp.157-164
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• 2019

Big data is a field that has been utilized and developed in various fields in our society recently. Big data analysis techniques are frequently used to analyze various big data in various fields of politics, economy, and society to grasp various meanings hidden in the data. However, big data analysis is used some case studies of in fields of analysis of educational data, but analysis of the curriculum and direction is still inadequate. Therefore, this study aims to identify and analyze the core concepts of middle school informatics textbooks using big data analysis techniques. Text mining was used for big data analysis for informatics textbook analysis. Through the core concepts of middle school informatics textbooks identified using this techniques, we could confirm the concepts to be emphasized in the textbooks and the possibility of using big data in the field of education.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.685-696
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• 2022

This study explores convergence curriculum for design and data science, and applies data science knowledge on undergraduate design classes for designer's data literacy. First, related studies about data literacy education for non-data science major's, and data driven design project cases are explored, then design competency and data competency based on NCS are studied. Then this study developed 3 step design-data convergence curriculum model for designers' data literacy. The curriculum model is applied on case study classes, which are Big data and UX design(2) classes. The learning results and student's feedback of the case study classes are collected and analyzed to prove the design-data convergence curriculum, and the results provide findings and implications of the design-data convergence class case study.

• Korea Trade Review
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• v.44 no.4
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• pp.67-85
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• 2019

This study analyzes the trade issues and curriculum issues of universities in the 4th Industrial Revolution era with the aim of finding strategies to improve the curriculum of international commerce and to cultivate trade manpower by matching them with the trade job competencies required by trade enterprises. To this end, trade college students, GTEP partners, industry-academia partners, and expert groups of N university were asked to provide information on trade curriculum for the current curriculum. The resulting data were analyzed by questionnaire frequency analysis and FGI method to reveal that both students and graduates are interested in improving the trade curriculum of the university, and that companies are also demanding talents who are responsible for the comprehensive process of trade practice and can perform sincerely and comprehensively. Therefore, we have established a new curriculum that is suitable for the 4th industrial age, opened a certificate acquisition course suitable for the needs of the company, and developed the commercial practice, trade simulation, capstone design, and PBL teaching method. Ways are suggesting to reduce mismatch between universities and companies.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.3
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• pp.587-592
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• 2020

This paper analyzed the curriculum of computer and software-related majors educating the core IT-related skills needed for the 4th Industrial Revolution. The analysis was conducted on 158 majors classified as applied software, computer science and computer engineering according to the standard classification of university education units by the Standard Classification Committee of the Korean Council of University Education. The current status of introduction of curricular divided into the fields of Internet of Things(IoT) & mobile, cloud & big data, artificial intelligence(AI), and information security was analyzed among the contents of education in the relevant departments. According to the analysis, an average of 81.6% of the majors for each group of curricular organized related subjects into the curriculum. The Curriculum Response Index for the 4th industrial revolution(CRI4th) by major, calculated by weighting track operations by education sector, averaged 27.5 point out of 100 point. And the IoT & mobile sector had the highest score of 42.3 points.

• Women's Health Nursing
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• v.26 no.1
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• pp.5-9
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• 2020

Artificial intelligence (AI), which includes machine learning and deep learning has been introduced to nursing care in recent years. The present study reviews the following topics: the concepts of AI, machine learning, and deep learning; examples of AI-based nursing research; the necessity of education on AI in nursing schools; and the areas of nursing care where AI is useful. AI refers to an intelligent system consisting not of a human, but a machine. Machine learning refers to computers' ability to learn without being explicitly programmed. Deep learning is a subset of machine learning that uses artificial neural networks consisting of multiple hidden layers. It is suggested that the educational curriculum should include big data, the concept of AI, algorithms and models of machine learning, the model of deep learning, and coding practice. The standard curriculum should be organized by the nursing society. An example of an area of nursing care where AI is useful is prenatal nursing interventions based on pregnant women's nursing records and AI-based prediction of the risk of delivery according to pregnant women's age. Nurses should be able to cope with the rapidly developing environment of nursing care influenced by AI and should understand how to apply AI in their field. It is time for Korean nurses to take steps to become familiar with AI in their research, education, and practice.

• The Journal of Bigdata
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• v.3 no.2
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• pp.123-130
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• 2018

As the demand for analytics technologies in both industry and academia increases, the demand for analytics experts is also increasing. To meet this trend, universities have begun to develop new analytics curriculum and provide courses for training analytics experts. In this study, we surveyed curriculum of master's analytics programs of 9 Korean universities and 20 overseas universities. As a result of comparing the domestic university program with the overseas university programs, the average number of subjects per school program is more than that of the Korean university program, but it was found to be less in terms of diversity of subjects.

• 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.

• The Mathematical Education
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• v.62 no.2
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• pp.289-302
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• 2023

In today's digital information society, student knowledge and skills to analyze big data and make informed decisions have become an important goal of school mathematics. Integrating big data statistical projects with digital technologies in high school <Artificial Intelligence> mathematics courses has the potential to provide students with a learning experience of high impact that can develop these essential skills. This paper proposes a set of guidelines for designing effective big data statistical project-based tasks and evaluates the tasks in the artificial intelligence mathematics textbook against these criteria. The proposed guidelines recommend that projects should: (1) align knowledge and skills with the national school mathematics curriculum; (2) use preprocessed massive datasets; (3) employ data scientists' problem-solving methods; (4) encourage decision-making; (5) leverage technological tools; and (6) promote collaborative learning. The findings indicate that few textbooks fully align with these guidelines, with most failing to incorporate elements corresponding to Guideline 2 in their project tasks. In addition, most tasks in the textbooks overlook or omit data preprocessing, either by using smaller datasets or by using big data without any form of preprocessing. This can potentially result in misconceptions among students regarding the nature of big data. Furthermore, this paper discusses the relevant mathematical knowledge and skills necessary for artificial intelligence, as well as the potential benefits and pedagogical considerations associated with integrating technology into big data tasks. This research sheds light on teaching mathematical concepts with machine learning algorithms and the effective use of technology tools in big data education.

• Korean Journal of Childcare and Education
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• v.11 no.6
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• pp.177-198
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• 2015

This study is aimed at a comparison analyzing the contents of child 'safety education' in Three-four-year-old Nuri curriculum manual for teachers related activity type and activity form, life theme based on the criteria of analysis. First, the number of contents of child 'safety education' included in the 3 year old Nuri curriculum manual for teachers was 136, and among them, 71(52.2%) were from in big and small group activity. Total 124 contents were in 4-year old group and showed 58(46.8%) contents in big and small group activity. Second, it was identified that the Three-four-year-old Nuri curriculum handled highest number of child 'safety education' activities. Twenty-five activities from 'appliances' among a total of 127 child 'safety education' activities were included and included 21 activities in contents of 'safety for object, tool, and apparatus.' Thirty-three activities among 'health and safety' among a total of 131 child 'safety education' activities were included and it was identified that the highest number of child 'safety education' activities were conducted in 'safety for disease' contents. It will be hope to suggest some of the providing child 'safety education' of Three-four-year-old in education field, and to provide basic data for planning and suggesting directions for various training related to child safety education. Moreover, this study intends to provide basic data for composing necessary manual and program for child 'safety education' and to provide basic data for expanding the safety experience facility.