• 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.

• The Korean Journal of Applied Statistics
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• v.31 no.2
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• pp.167-188
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• 2018

Minard's figurative map is an infographic on Napoleon's Russian Campaign of 1812. Tufte (The Visual Display of Quantitative Information, Graphics Press, 1983) declared that Napoleon's March "may well be the best statistical graphic ever produced." We can use this data map as storytelling material for data visualization education. In this paper, with Minard's figurative map, we study four themes (infographics, information design, Minard, and the Russian Campaign) in data visualization education.

• 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 Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1696-1707
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• 2021

With the recent growth of information technology, various literacy such as digital literacy, data literacy, AI literacy is being studied. In this paper, we focus on data visualization literacy as visualization is an essential part of big data analysis and is used in several mobile apps. Visualization Literacy Assessment Test(VLAT) was developed in 2016 and we introduce how the test was developed and modified to a Korean version, K-VLAT. K-VLAT is consisted of 12 visualizations and 53 questions through a website. Additionally, to understand the research trend in visualization literacy we analyzed 81 papers that had cited the VLAT publication. We categorized the research into 4 categories with 11 sub-categories. The area of studies visualization literacy related to was understanding the relation with cognition, expanding the literacy measures, relation with education, utilization for developing user-centric dashboards or using the test to show effectiveness of visualizations. At last, we discuss about different ways to utilize K-VLAT for future research.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.203-211
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• 2024

Utilizing programming languages for data visualization can enhance the efficiency and effectiveness in handling data volume, processing time, and flexibility. However, practice is required to become proficient in programming. Therefore public data-based the problem bank was developed to practice data visualization in a programming automatic assessment system. Public data were collected based on topics suggested in the curriculum and were preprocessed to make it suitable for users to visualize. The problem bank was associated with the mathematics curriculum to learn various data visualization methods. The developed problems were reviewed to expert and pilot testing, which validated the level of the questions and the potential of integrating data visualization in math education. However, feedback indicated a lack of student interest in the topics, leading us to develop additional questions using student-center data. The developed problem bank is expected to be used when students who have learned Python in primary school information gifted or middle school or higher learn data visualization.

• Journal of The Korean Association of Information Education
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• v.23 no.3
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• pp.197-206
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• 2019

In this study, we analyzed the effects of data visualization education with using Python on the improvement of computing thinking ability of the 6th grade students of elementary school. Based on the results of the needs analysis of 60 elementary school teachers and 120 elementary school students, we developed the data visualization education program. In the developed educational program, 24 elementary school students were trained for 6 days and 36 hours in total. Thereafter, students were subjected to pre- and post-comparison tests. As a result of the analysis, it was found that the data visualization education with using Python is effective in improving the Computational cognition, Fluency, Originality, Elaboration of the 6th grade students in elementary school.

• Journal of The Korean Association of Information Education
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• v.23 no.4
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• pp.283-292
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• 2019

In this study, an unplugged education method which focuses on the data visualization training was applied to third grade students of an elementary school and analyzed its impact on enhancing their computational thinking. The analysis was conducted on 60 elementary school teachers and 124 third grade students and the unplugged education program based on the data visualization procedure was developed. The education program developed was carried out with 24 third grade students for 36 hours over six days. The effect of the program applied was analyzed through the pre-to-post comparison performed with perceptive strength test and creativity test in order to examine the enhancement in computational thinking. According to the analysis result, the unplugged education method which focuses on the data visualization training has significant effect on the 'computational perception' and 'creativity' of third grade students.

• Proceedings of The KACE
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• 2017.08a
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• pp.143-145
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• 2017

최근 IT 기술이 발전함에 따라 교육형태도 많이 발전되고 있다. 특히 IT 기기를 활용할 수 있는 온라인 교육에 집중되고 있다. 온라인 교육 시스템 중 하나인 MOOT(Massive Open Online Textbook)이 주목받고 있다. MOOT는 텍스트 중심의 교육 기반이며, 온라인 교재 내에 실습환경이 있어 언제 어디서나 학습자가 자기주도적인 학습을 할 수 있도록 도와준다. 온라인을 통해 학습하기 때문에 수많은 학습자의 학습현황을 쉽게 파악할 수 없는 문제점이 제기되었다. 따라서 본 논문에서는 데이터 결과를 한 눈에 파악할 수 있도록 시각화를 제안하여, MOOT시스템 내에서 학습한 고려대학교 343명의 학생 데이터를 기반으로 학습자 데이터 시각화를 설계하였다.

• Journal of The Korean Association of Information Education
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• v.24 no.6
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• pp.607-614
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• 2020

In this study, a scratch focused on data visualization was applied to 26 elementary school pre-service teachers to analyze the effect on improvement of creativity. Based on the results of the needs analysis conducted on 60 in-service elementary school teachers, the program using scratches according to the data visualization procedure was developed. With the developed educational program, 26 elementary school pre-service teachers were taught for 42 hours for a total of 4 months. In order to examine whether their creativity was improved, a creativity test was conducted and the effectiveness of the applied program was analyzed through a pre/post comparison tests. As a result of the analysis, it was found that the software education using scratch-oriented data visualization for elementary school pre-service teachers had significant effects on the fluency, sophistication, creativity average, and creativity index among the sub-elements of their creativity.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.05a
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• pp.121-122
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• 2009

인체 데이터를 살펴볼 수 있는 환경은 의학적으로 중요하고, 교육적으로도 필요하다. 의대 학생의 경우 인체 데이터를 사용해서 실습을 해 볼 수 있다면, 실제 수술 등의 의료 행위에 큰 도움을 받을 수 있다. 인체 데이터 시뮬레이션을 하기 위해서는 여러 수준의 시스템이 필요하다. 첫 단계가 데이터를 시각화하여 관찰할 수 있는 환경을 제공하는 시각화 플랫폼이다. 본 논문에서는 기존 시각화 플랫폼을 이용하여 인체 데이터를 보여주는 변환 방식에 대해서 밝힌다. 기존에는 기계적인 제약 사항으로 인해 많은 양의 3차원 데이터를 인터넷을 통한 서비스에 어려움이 있었다. 현재는 개인 피씨의 성능 향상에 의해 3차원 데이터도 인터넷으로 일정 부분 서비스가 가능하다. 시각화 플랫폼을 현재의 환경에서 활용하여 인체 데이터를 관찰할 수 있도록 구현하는 것이 본 논문의 목표이다.