• Journal of the Korean Society of Earth Science Education
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• v.17 no.2
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• pp.123-136
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• 2024

This study examines the performance expectations (PEs) and clarification statements of each PE in the 2022 revised national science and mathematics education standards from a data visualization competency perspective. First, the authors intensively reviewed data visualization literature to define key competencies and developed a framework comprising four main categories: collection and pre-processing skills, technical skills, thinking skills, and interaction skills. Based on the framework, the authors extracted a total of 191 mathematics and 230 science PEs from the 2022 revised science and mathematics education standards (Ministry of Education Ordinance No. 2022-33, Volumes 8 and 9) as the main data set. The analysis process consisted of three steps: first, the authors organized the data (421 PEs) by the four categories of the framework and four grade levels (3-4th, 5-6th, 7-9th, and 10th grade); second, the numbers of PEs in each grade level were standardized by the accomplishing period (1-3 years) of each PE depending on the grade level; lastly, the data set was represented by heatmaps to visualize the relationship between the four categories of visualization competency and four grade levels, and the differences between the competency categories and grade levels were quantitatively analyzed using the Mann-Whitney U test and independent sample Kruskal-Wallis tests. The analysis results revealed that in mathematics, there was no significant difference between the number of PEs by grade. However, on average, the number of PEs categorized in 'thinking skills' was significantly lower than those in the technical skills (p = .002) and interaction skills categories (p = .001). In science, it was observed that as grade level increased, PEs also increased (pairwise comparison: Grades 5-6 vs. 7-9, p = .001; Grades 5-6 vs. Grade 10, p = .029; Grades 3-4 vs. 7-9, p = .022). Particularly, the frequency of PEs in 'thinking skills' was significantly lower than in the other skills (pairwise comparison: technical skills p = .024; collection and pre-processing skills p = .012; interaction skills p = .010). Based on the results, two implications for revising national science and mathematics standards and teacher education were suggested.

• Journal of The Korean Association of Information Education
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• v.26 no.6
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• pp.481-490
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• 2022

With the development of computing technology, the big data era has arrived, and we live with a lot of data around us. Elementary school students are no exception. Therefore, it is very important to learn to process data from elementary school. Since elementary school students have intuitive thinking, data visualization, which expresses data directly in pictures, is an important learning element. In this study, we study how effective elementary school students can visualize data in their daily lives to improve their information processing capabilities. Adata visualization program was developed by organizing and visualizing data using data visualization tools for the 8th class, which can be done by third graders in elementary school, and then experiencing the process of interaction. As a result of applying the developed program to 186 students in 7 classes, knowledge information processing competency factors were evaluated before and after class. As a result of the pre- and post-test, there was a significant difference in knowledge information processing capabilities. Therefore, the data visualization program developed in this study is effective.

• 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.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.201-207
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• 2021

As artificial intelligence gradually expands into jobs, iIt is necessary to nurture talents with AI literacy capabilities required for non-majors. Therefore, in this study, based on the necessity and current status of AI education, AI literacy competency improvement education was conducted for non-majors so that AI learning could be sustainable in relation to future majors. For non-majors at University D, problem-solving solutions through project-based data analysis and visualization were applied over 15 weeks, and the AI ability improvement and effectiveness of learners before and after education were analyzed and verified. As a result, it was possible to confirm a statistically significant level of positive change in the learners' data analysis and utilization ability, AI literacy ability, and AI self-efficacy. In particular, it not only improved the learners' ability to directly utilize public data to analyze and visualize it, but also improved their self-efficacy to solve problems by linking this with the use of AI.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.301-319
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• 2022

In recent decades, research became more data-intensive in the fast-paced information environment. Researchers are facing new challenges in managing their research data due to the increasing volume of data-driven research and the policies of major funding agencies. Information professionals have begun to offer various data support services such as training, instruction, data curation, data management planning and data visualization. However, the emerging field of data librarians, including specific roles and competencies, has not been clearly established even though librarians are taking on new roles in data services. Therefore, there is a need to identify a set of competencies for data librarians in this growing field. The purpose of this study is to consider varying core competencies for data librarians. This exploratory study examines 95 online recruiting advertisements regarding data librarians posted between 2017 and 2021. This study finds core competencies for data librarians that include skills in technology, communication and interpersonal relationships, training/consulting, service, library management, metadata knowledge and knowledge of data curation. Specific core technology skills include knowledge of statistical software and computer programming. This study contributes to an understanding of core competencies for data librarians to help future information professionals prepare their competencies as data librarians and the instructors who develop and revise curriculum and course materials.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.285-293
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• 2021

With the advent of the 4th Industrial Revolution, AI utilization capabilities are being emphasized in various industries, but AI education design and curriculum research as universal education is currently lacking. This study offers a design for universal AI education to further cultivate its use in universities. For the AI basic education design, a questionnaire was conducted for experts three times, and the reliability of the derived design contents was verified by reflecting the results. As a result, the main competencies for cultivating AI literacy were data literacy, AI understanding and utilization, and the main detailed areas derived were data structure understanding and processing, visualization, word cloud, public data utilization, and machine learning concept understanding and utilization. The educational design content derived through this study is expected to increase the value of competency-centered AI universal education in the future.

• Journal of the Korean Society of Earth Science Education
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• v.13 no.3
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• pp.330-343
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• 2020

In this study, STEAM program on the subject of 'atmospheric circulation and surface current' was produced based on data and applied to 106 first-year high school students to analyze its effect and problem-solving processes. This program was organized to collect, refine, visualize, and analyze data and to allow communication processes to proceed based on these results. Using this, the concept of circulation in daily life was expanded from a global perspective to identify problems about circulation around the world. As a result of the application of the program, significant changes were identified in knowledge information processing competency. Also, significant changes were made in terms of convergence and creativity, which are sub categories among STEAM core competencies. It also sought to obtain suggestions for data-based STEAM education by analyzing students' responses in the form of a Text network.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.107-116
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• 2018

One of the key mission is to develop and prompte the use National Competency Standards, which is defined to be the systemization of competencies(knowledge, skills and attitudes) required to perform duties at the workplace by the nation for each industrial sector and level. This provides the basis for the design of training and detailed specifications for workplace assessment. To promote the data-driven service improvement, the commercial product Splunk was introduced, and has grown to become an extremely useful platform because it enables the users to search, collect, and organize data in a far more comprehensive, far less labor-intensive way than traditional databases. Leveraging Splunk's built-in data visualization and analytical features, HRD Korea have built custom tools to gain new insight and operational intelligence that organizations have never had before. This paper analyzes the NCS homepage. Concretely, applying Splunk in creating visualizations, dashboards and performing various functional and statistical analysis and structure without Web development skills. We presented practical use and implications through case studies.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.119-143
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• 2022

This preliminary study examined the status of data science-related course syllabi in the American Library Association (ALA) accredited Library and Information Science (LIS) programs. The purpose of this study was to explore LIS course syllabi related to data science, such as course title, course description, learning outcomes, and weekly topics. LIS programs offer various topics in data science such as the introduction to data science, data mining, database, data analysis, data visualization, data curation and management, machine learning, metadata, and computer programming. This study contributes to helping instructors develop or revise course materials to improve course competencies related to data science in the ALA-accredited LIS programs.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.111-112
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• 2022

모든 도시가 발전하고 번창하기 위해서는 핵심기반시설의 재난 및 안전이 선제적으로 확보되어야 한다. 본 논문에서는 환경핵심기반시설을 중심으로 지역사회가 지속 가능한 녹색도시로 거듭나기 위해 재난준비태세 증진에 실제 활용 가능한 위험지도를 드론에 장착한 LiDAR 센서를 통해 수집한 고도 데이터를 바탕으로 제작하였다. 나아가 지진과 같은 재난 발생 시 시설에서부터 확산하는 관리 오염물의 경로 및 범위를 시범 모의하여, 기능 연속성 계획 및 재난대응 가이드와 연계를 하는 방안을 제시함으로 지자체 중심의 통합적 지역사회의 노력이 발현될 수 있도록 기초적 연구를 진행하고, 전략적 활성화 방안을 제시하였다. 본 연구는 끊임없는 성장과 거듭되는 개발로 인해 변화하는 도시의 형상에 따라 리스크를 최신화하여 대응력을 높이고, 이해관계자들에게 시각화된 재난 범위 모의를 제시함으로써 지역사회와 지자체 역량에 따른 협력적 재난대응태세에 필요한 프레임워크 도출 및 계획수립을 가능하게 한다는 점에서 큰 의의를 지닌다. 또한, 각 영역별 전문가들의 자문을 통하여 본 논문에서 제시된 확산 모의의 방법론이 타당함을 확인하였다. 무엇보다 모호한 "가능한 신속한 자원관리"와 같은 추상적인 대응계획이 아닌, 객관적인 재난자원관리계획을 수립할 수 있게 함으로써 추후 국가적 재난 및 안전역량을 계량화시킬 수 있을 것으로 사료된다.