• The Journal of Economics, Marketing and Management
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• v.11 no.3
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• pp.25-35
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• 2023

Purpose: This paper examines whether foreign aid influences public sector efficiency in policy areas of administration, education, and stability. Research design, data and methodology: The study uses panel data of 77 aid recipient developing countries over the period 2000-2020 and employs various panel data techniques to estimate. Results: We found that a percentage change in foreign aid increases administrative efficiency by 0.02 to 0.04 on average ceteris paribus in the short run. On the other hand, a percentage increase in foreign aid decreases education efficiency by 0.005 to 0.006 on average. While the impact of foreign aid on the policy area of stability is insignificant. Conclusions: The empirical results of this study have important implications for both donors and aid recipient countries. It suggests that to get positive influence from foreign aid, in the area of education and stability, the recipient countries need to increase accessibility of secondary schools with quality education especially; technical and vocational. Also, the donor should provide a minimum threshold amount of foreign aid to developing countries for reforming the institutions' capacity building.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.391-394
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• 2023

본 연구에서는 국내 초·중·고 정보교육에서 이뤄지고 있는 데이터 교육 연구 동향을 분석하여, 향후 데이터 교육의 연구 방향을 제안하고자 하였다. 이를 위해 2015년부터 2023년 5월까지 게재된 국내 논문 중 데이터 교육 관련 논문 45편을 발행 연도, 연구 대상, 연구 분야, 데이터 리터러시 요소별로 분석하였다. 분석 결과 데이터 교육은 초등학생을 대상으로 집중적으로 이뤄지고 있었고 개발 및 적용 관련 연구가 가장 많이 이뤄지고 있었다. 또한 데이터 리터러시의 전 요소를 포함한 연구와 인공지능과 관련된 연구의 비중이 높음을 확인할 수 있었다. 따라서 본 연구를 바탕으로 SW·AI 교육을 위한 데이터 교육이 활발히 이뤄지길 기대한다.

• Journal of The Korean Association For Science Education
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• v.12 no.3
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• pp.17-33
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• 1992

The Purpose of this study was to develop a data base system for the information on science education research and development. As a part of this study, an analysis of papers on science education included in five selected jounals related science education was done by the use of the authors classification system for the research and development materials of science education. A total of 640 papers from the first issues to the 1991 issues of the journals were classified and analyzed. The selected five journals were Journal of the Korean Association for Research in Science Education (published by The Korean Association for Research in Science Education, 148 papers), Teaching Physics(published by Korean Physical Society, 164papers), Chemical Education (published by The Korean Chemical Socity, 98 papers), The Korean Journal of Biological Education(published by The Korean Society of Biological Education, 148papers), and Journal of Science Education (published by Science Education Center.College of Education, Seoul National University, 82 papers).

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.42-47
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• 2007

We have studied feasibility of the geostatistical approach to enhance the result of analysis of the sparsely obtained MT(Magnetotelluric) data by combining with gravity data. We have attempted to use geostatistics for integrating the MT data along with gravity data. To evaluate the feasibility of this approach, we have studied about interrelation between geological boundary and density distribution, and corrected density distribution for conversion to more sensitive to geological boundary by minimization of difference between z-directional variogram values of resistivity distribution obtained MT inversion and density distributions. Then, this method has been tested on model and field data. In model test, the results obtained were good agreement with real model. And in a real field data, the result of analysis demonstrate convincingly that our geostatistical approach is effective.

• Journal of Practical Engineering Education
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• v.16 no.2
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• pp.159-165
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• 2024

This study investigates the comprehensive system for collecting intelligent learning activity data tailored to learner-centered personalized education. We compared and analyzed the characteristics of xAPI, Caliper analytics, and cmi5, which are learning activity data collection standards, and established a system that allows not only standardized data but also non-standardized learning activity data to be stored as big data for artificial intelligence learning analysis. As a result, the system was structured into five stages: defining data types, standardizing learning data using xAPI, storing big data, conducting learning analysis (statistical and AI-based), and providing learner-tailored services. The aim was to establish a foundation for analyzing learning data using artificial intelligence technology. In future research, we will divide the entire system into three stages, implement and execute it, and correct and supplement any shortcomings in the design.

• Journal of the Korean Society of Earth Science Education
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• v.17 no.2
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• pp.153-167
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• 2024

This study explored the errors and context occurred during high school students' data analysis processes. For the study, 222 data inquiry reports produced by 74 students from 'A' High School were collected and explored the detailed error types in the data analysis processes such as data collection and preprocessing, data representation, and data interpretation. The results of study found that in the data interpretation process, students had a somewhat insufficient understanding of seasonal variations and periodic patterns about weather elements. And, various types of errors were identified in the data representation process, such as basic unit in graphs, legend settings, trend lines. The causes of these errors are the feature of authoring tools, misconceptions related to weather elements, and cognitive biases, etc. Based on the study's results, educational implications for big data education, a significant topic in future science education, were derived. And related follow-up studies were suggested.

• Journal of Engineering Education Research
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• v.17 no.5
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• pp.51-58
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• 2014

This study proposes an effective data management method for easing the burden on self-study report by analyzing operational data on accredited engineering programs. Four analysis criteria are developed: variability, difficulty level of collecting, urgency of analysis, timeliness. After the operational data are analyzed in terms of the analysis criteria, the data which should be managed in time are extracted according to the analysis results. This study proposes a data management method in which tasks of managing the timely-managed data are performed based on the regular academic schedule, so that the result of this study may be used as a working-level reference material.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.261-266
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• 2021

The spread of cloud computing, digital computing, and the popular social media platforms have led to increased growth of data. That growth of data results in what is known as big data (BD), which seen as one of the most strategic resources. The analysis of these BD has allowed generating value from massive raw data that helps in making effective decisions and providing quality of service. With Vision 2030, Saudi Arabia seeks to invest in BD technologies, but many challenges and barriers have led to delays in adopting BD. This research paper aims to search in the state of Big Data Analytics (BDA) in Saudi higher education sector, identify the barriers by reviewing the literature, and then to apply the design-reality gap model to assess these barriers that prevent effective use of big data and highlights priority areas for action to accelerate the application of BD to comply with Vision 2030.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.209-213
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• 2021

Data mining is the application of specific algorithms for extracting patterns from data and KDD is the automated or convenient extraction of patterns representing knowledge implicitly stored or captured in large databases, data warehouses, the Web, other massive information repositories or data streams. Data mining can be used for decision making in educational system. But educational institution does not use any knowledge discovery process approach on these data; this knowledge can be used to increase the quality of education. The problem was happening in the educational management system, but to make education system more flexible and discover knowledge from it huge data, we will use data mining techniques to solve problem.

• The Journal of Korean Academic Society of Nursing Education
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• v.24 no.4
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• pp.337-346
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• 2018

Purpose: The aim of this study was to understand and describe difficulties and needs experienced by head nurses in the clinical practice education of nursing students. Methods: A qualitative descriptive method was employed. A convenience sampling method was used to recruit participants from four hospitals in South Korea. Twenty-one head nurses participated in the first interview and 17 of them participated in the second interview. Data were collected through two in-depth interviews and field notes were written. Qualitative content analysis method was utilized for data analysis using ATLAS.ti 6.2 software. Results: Thirty-one codes and twelve categories were identified. Four themes emerged from data analysis, which included 'too many tasks', 'limitations of student education', 'many differences', and 'lack of support and resources.' Conclusion: This qualitative study described head nurses' many difficulties and needs in the clinical practice education of nursing students. The results of this study provide valuable understanding and knowledge of head nurses' experiences in students' clinical education, which leads to improvement of the quality of clinical education for nursing students.