• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.984-987
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• 2009

데이터가 기업 및 기관 활동의 중요한 자산으로 인식이 높아지고 있지만 저 품질 데이터로 인한 막대한 손실과 비용의 증가는 큰 문제가 되고 있다. 본 논문에서는 교육과학기술부와 KISTI에서 2007년부터 범부처 차원에서 수행중인 국가R&D 정보자원의 데이터 품질관리를 위해 각 부처와 협의하고 수행해 온 국가R&D 데이터 품질관리 체계 수립과 포털 사이트 구축에 관하여 알아본다. 범부처 국가R&D정보 자원의 데이터 품질관리체계 수립과 범부처 적용 지침 및 가이드라인 제시를 위해 NTIS사업단 및 15개 부처(16개 대표전문기관)의 실무팀장 및 DB 관리자 중심으로 총 33명의 설문을 실시하여 품질관리체계 현황을 조사 분석하였다. 또한 부처(기관)별로 국가R&D표준정보 데이터품질 지표 마련과 주기별 데이터 품질 및 개선도 자체점검을 지원하기 위해, 데이터 점검기준과 절차를 마련하고 이를 기반으로 부처(기관)와 협력하여 데이터품질 점검을 기반을 마련하였다. 이렇게 마련된 품질관리체계와 프로세스를 지원하기 위한 자동화 솔루션을 운영하고자 본 논문에서는 NTIS 데이터 품질관리 체계 및 프로세스, 기능이 통합된 웹 포털 구축에 대해서도 알아본다.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.167-173
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• 2021

The purpose of this study is to discuss the types of algorithms and data categories in AI education for elementary school students. The study surveyed 11 pre-elementary teachers after providing education and practice on various data, artificial intelligence algorithm, and AI education platform for 15 weeks. The categories of data and algorithms considering the elementary school level, and educational tools were presented, and their suitability was analyzed. Through the questionnaire, it was concluded that it is most suitable for the teacher to select and preprocess data in advance according to the purpose of the class, and the classification and prediction algorithms are suitable for elementary AI education. In addition, it was confirmed that Entry is most suitable as an AI educational tool, and materials that explain mathematical knowledge are needed to educate the concept of learning of AI. This study is meaningful in that it specifically presents the categories of algorithms and data with in AI education for elementary school students, and analyzes the need for related mathematics education and appropriate AI educational tools.

• Journal of The Korean Association of Information Education
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• v.22 no.1
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• pp.169-176
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• 2018

CS Unplugged education at the base of computer science is emphasized as an instrument for teaching the basic principles of elementary SW education, but these materials for elementary education are very lacking. So We'll present the data error detection and correction materials for elementary school classes. Based on previous studies related to this topic, we developed learning materials for elementary higher grade students using Hamming code. We introduces the card magic in the introduction part. 'error detection and correction' learning materials based on the principle of Hamming code, were composed as activity-based education. The results of the questionnaire survey showed that it had a positive effect on improving learners' understanding of computer science.

• Journal of The Korean Association of Information Education
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• v.21 no.2
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• pp.219-230
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• 2017

In this study, we developed a data science education program using spreadsheet, applied it after educational method to improve elementary school student 's Computational Thinking, and then verified its effect. Based on the results of preliminary requirement analysis conducted by Rossett's request analysis the educational program was developed based on the procedure of the ADDIE model which is the representative model of the teaching design based on the result of prior requirement analysis of 205 elementary school students and computer teaching major 20 incumbent elementary school teachers, applying Rossett's requirement analysis model. In order to verify the effect of the developed educational program, we are promoting 42 hours of lecture for a total of 6 days for 20 students of applicants who volunteered for volunteer votes of educational donation programs implemented at ${\bigcirc}{\bigcirc}$University, We analyzed the educational effect using the results of pre-post test. As a result of the analysis, we learned that the educational program developed in this study is effective for improving elementary school student 's Computational Thinking.

• Journal of the Korean Society for information Management
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• v.35 no.4
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• pp.7-36
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• 2018

This study aimed to analyze the content of Records Data Management (RDM) training programs provided by 51 out of 121 university libraries in North America that implemented RDM services, and to provide implications from the results. For the content analysis, 317 titles of classroom training programs and 42 headings at the highest level from the tables of content of online tutorials were collected and coded based on 12 data literacy competencies identified from previous studies. Among classroom training programs, those regarding data processing and analysis competency were offered the most. The highest number of the libraries provided classroom training programs in relation to data management and organization competency. The third most classroom training programs dealt with data visualization and representation competency. However, each of the remaining 9 competencies was covered by only a few classroom training programs, and this implied that classroom training programs focused on the particular data literacy competencies. There were five university libraries that developed and provided their own online tutorials. The analysis of the headings showed that the competencies of data preservation, ethics and data citation, and data management and organization were mainly covered and the difference existed in the competencies stressed by the classroom training programs. For effective RDM training program, it is necessary to understand and support the education of data literacy competencies that researchers need to draw research results, in addition to competencies that university librarians traditionally have taught and emphasized. It is also needed to develop educational resources that support continuing education for the librarians involved in RDM services.

• 한국정보교육학회:학술대회논문집
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• 2004.08a
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• pp.446-453
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• 2004

기존의 과학 실험 활동은 도구 조작과 데이터 수집을 하기 위한 절차로서 컴퓨터를 이용한 예가 극히 적었다. 이런 점에 착안하여 다양한 센서를 활용하고 센서를 포함한 로보틱스를 도입하여 새로운 실험 실습 환경을 설계하고자 한다. 본 연구는 고학년을 중심으로 7차 과학과 교육과정에서 센서를 적용할 수 있는 교육 내용을 선정한 후 마이크로 컨트롤러를 이용하여 측정값을 디지털 세그먼트로 나타내고 또한 실험결과를 모니터 상에 그래프로 표현함으로써 학습자의 흥미와 호기심을 유발하고, 데이터 수집의 신속성과, 수업시간 운영의 효율성, 빠른 피드백을 가능하게 할 것이다.

• Journal of The Korean Association For Science Education
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• v.40 no.6
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• pp.657-670
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• 2020

The knowledge-information-processing competency is the most essential competency in a knowledge-information-based society and is the most fundamental competency in the new problem-solving ability. Data-driven science inquiry, which emphasizes how to find and solve problems using vast amounts of data and information, is a way to cultivate the problem-solving ability in a knowledge-information-based society. Therefore, this study aims to develop a teaching-learning model and strategy for data-driven science inquiry and to verify the validity of the model in terms of knowledge information processing competency. This study is developmental research. Based on literature, the initial model and strategy were developed, and the final model and teaching strategy were completed by securing external validity through on-site application and internal validity through expert advice. The development principle of the inquiry model is the literature study on science inquiry, data science, and a statistical problem-solving model based on resource-based learning theory, which is known to be effective for the knowledge-information-processing competency and critical thinking. This model is titled "Exploratory Scientific Data Analysis" The model consisted of selecting tools, collecting and analyzing data, finding problems and exploring problems. The teaching strategy is composed of seven principles necessary for each stage of the model, and is divided into instructional strategies and guidelines for environment composition. The development of the ESDA inquiry model and teaching strategy is not easy to generalize to the whole school level because the sample was not large, and research was qualitative. While this study has a limitation that a quantitative study over large number of students could not be carried out, it has significance that practical model and strategy was developed by approaching the knowledge-information-processing competency with respect of science inquiry.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.279-301
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• 2023

The data-driven research environment is rapidly changing. Accordingly, domestic university libraries are also preparing to establish and operate research data management services to support university researchers. This study was designed to propose a research data management service to support researchers in science and technology specialized university libraries. In order to propose the service, 11 universities specializing in science and technology were selected from overseas and domestic universities and their research data management services were analyzed. Key categories were derived from analysis results, research data management, electronic research notebooks, and RDM training. In particular, the 'research data management' category included DMP, data collection, data management, data preservation, data sharing and publishing, data reuse, infrastructure and tools. And it consists of RDM guides and policies. The results of this study will be helpful in introducing and operating research data management services in science and technology specialized university libraries.

• Journal of The Korean Association of Information Education
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• v.18 no.1
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• pp.25-33
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• 2014

Due to the recent development of educational robot hardwares, processing speed and scalability have been greatly improved. Thus, the robot hardwares that are compatible with temperature sensor for MBL and gyro sensor made a data logging possible. Students can conduct an experiment on scientific research and prediction, collecting and data analysis with robots that can process data logging. Therefore this research constructed and adopted science project class that introduced a Smart r-Learning that utilizes Class SNS and smartphone. As a result of applying a data logging smart r-Learning to elementary school 5th graders, it has shown that the students' logical thinking ability four of the six areas have been improved in t-test.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.87-99
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• 2013

Massive increases in data available to an organization are creating a new opportunity for competitive advantage. In this era of big data, developing analytics capabilities, therefore, becomes critical to take advantage of internal and external data and gain insights for data-driven decision making. However, the use of data in education is in its infancy, in comparison with business and government, and the potential for data analytics to impact education services is growing. In this paper, I survey how universities are currently using education data to improve students' performance and administrative efficiency, and propose new ways of extending the current use. In addition, with the so-called data scientist shortage, universities should be able to train professionals with data analytics skills. This paper discusses which skills are valuable to data scientists and introduces various training and certification programs offered by universities and industry. I finally conclude the paper by exploring new curriculums where students, by themselves, can learn how to find and use relevant data even in any courses.