• The Korean Journal of Applied Statistics
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• v.37 no.1
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• pp.49-59
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• 2024

The popularity of data science, influenced by the trends from the United States around 2010, has significantly impacted the education of various statistics departments at domestic universities. However, it is challenging to find research papers in domestic academic journals that address the efficient teaching of data science topics in relation to computing environment. This article will discuss and propose the establishment of a suitable computing infrastructure for the education and research in statistics and data science departments in domestic universities.

• Journal of Multimedia Information System
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• v.9 no.2
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• pp.171-176
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• 2022

Today, it is imperative to educate students on how to best prepare themselves for the new data driven era of the future. Undergraduate education plays an important role in providing students with more Data Science opportunities and expanding the supply of Data Science talent. This paper surveys and analyzes the curricula of Data Science-related bachelor's degree programs in the United States. The 'required' and 'elective' courses in a curriculum for obtaining a B.S. degree were evaluated by course weight to indicate its necessity. As a result, it was possible to find out which courses were important in Data Science programs and which areas were emphasized for B.S. degrees in Data Science. We found that courses belong to the Data Science area, such as data management, data visualization, and data modeling, were more required for Data Science B.S. degrees in the United States.

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.439-448
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• 2022

This study aims to search for education-related datasets provided by public data portals and examine what data types are constructed through classification using topic modeling methods. Regarding the data of the public data portal, 3,072 cases of file data in the education field were collected based on the classification system. Text mining analysis was performed using the LDA-based topic modeling method with stopword processing and data pre-processing for each dataset. Program information and student-supporting notifications were usually provided in the pre-classified dataset for education from the data portal. On the other hand, the characteristics of educational programs and supporting information for the disabled, parents, the elderly, and children through the perspective of lifelong education were generally indicated in the dataset collected by searching for education. The results of data analysis through this study show that providing sufficient educational information through the public data portal would be better to help the students' data science-based decision-making and problem-solving skills.

• Journal of The Korean Association For Science Education
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• v.21 no.5
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• pp.855-866
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• 2001

An important issue for qualified science teacher education should be a proper system of pre-service education for the science teacher. There are various types of science teacher education systems in accordance with their socio-cultural backgrounds. In this paper, science teacher education systems were analysed into 3 different types: Focusing Undergraduate Certification of Education (FUCE), Open Undergraduate Certification of Education (OUCE), and Post Graduate Certification of Education (PGCE). Science teacher education systems and their outcomes, such as the quality of the science teacher, were discussed with their socio-cultural backgrounds, compared by the 3 types of science teacher education systems. For this the results of meta-analysis from TIMSS-R and OECD data sets were used. Special interests focused on countries; Japan, Korea, the United Kingdom and the United States, which would represent stereotypes of science teacher education systems and different backgrounds of oriental and western culture.

• Journal of Practical Engineering Education
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• v.12 no.2
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• pp.265-273
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• 2020

In this paper, to design a basic data science practice curriculum as a liberal arts subject for non-majors, we proposed an educational method using an Excel(spreadsheet) data analysis tool. Tools for data collection, data processing, and data analysis include Excel, R, Python, and Structured Query Language (SQL). When it comes to practicing data science, R, Python and SQL need to understand programming languages and data structures together. On the other hand, the Excel tool is a data analysis tool familiar to the general public, and it does not have the burden of learning a programming language. And if you practice basic data science practice with Excel, you have the advantage of being able to concentrate on acquiring data science content. In this paper, a basic data science practice curriculum for one semester and weekly Excel practice contents were proposed. And, to demonstrate the substance of the educational content, examples of Linear Regression Analysis were presented using Excel data analysis tools.

• 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.

• Journal of Creative Information Culture
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• v.7 no.4
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• pp.265-277
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• 2021

Data is the core of AI technology. With the development of technology, AI technology is also accelerating as the amount of data increases explosively than before. However, compared to the interest in AI education, research on data education with AI is still insufficient. According to the case analysis of exsisting AI data education, there were cases of educating the process and part of data science, but it was hard to find studies related to data collection. Cause physical computing tools have a positive effect on AI education for elementary school students, data collection cases using tools were studied, but researches related to data collection were rare. Therefore, in this study, an efficient data collection method using physical tools was designed. A structural diagram of a data collection program was created using COBL S, a modular physical computing teaching tool, and examples of program screens from the service side and the user side were configured. This study has limitations in that the establishment of an AI education platform that can be used in conjunction with future program production and programs should be prioritized as a proposal in terms of design.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1107-1117
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• 2006

In this thesis, we conduct a comprehensive analysis of the current situation and the inherent problems found in modern statistics education in Korea. We investigate the American probability and statistics curriculum currently used in Wisconsin and discuss the overall state of statistics education in The United States. Through comparison of both the Korean and Wisconsin model, we explore the future direction of statistical education.

• Journal of the Korean earth science society
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• v.42 no.3
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• pp.325-343
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• 2021

This study aims to develop two science education programs using Angbuilgu and ancient astronomical data, are Korean astronomical heritage, and explore its educational possibility through the pilot application. Considering the TSK compositional characteristics of Angbuilgu and ancient astronomical data, linkage with science curriculum, and linkage with NOS, Angbuilgu was developed as a hands-on activity for elementary school students and ancient astronomical data as a science inquiry activity for middle and high school students. The educational availability of the developed program was confirmed by pilot application to elementary and high school groups. Through the Angbuilgu activity, the students refined their conceptual knowledge by correcting misconceptions about the solar motion by season and then confirmed the possibility of connection with the concept of the celestial coordinate system. Students recognized the scientific value of Angbuilgu and understood the nature of interactions STS. In the ancient astronomical data activity, students experienced inductive and deductive inquiry methods and utilized various information and strategies. Through the activities, students improved their scientific understanding and attitude towards TSK.

• Journal of Korean Elementary Science Education
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• v.24 no.4
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• pp.360-379
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• 2005

The purpose of this study was to investigate beginning elementary teachers' beliefs about the nature of science. Defining teachers' beliefs as a broad construct, we tried to examine the teachers' understandings about the nature of science. The methodology of this study was a qualitative approach through semi-structured interviews. In an urban area of Korea, five beginning elementary teachers were chosen. The cross-case and grounded theory study design were adopted for the data analysis. The results of data analysis were checked by teachers for internal validity. This study identified the teachers' beliefs about the nature of science suggested by many researchers. The results of this study showed that: 1) beginning elementary teachers did not well understand and were unfamiliar with the meanings of various terms about the nature of science; 2) their beliefs abut the nature of science were broad and various; 3) they understood some parts of the nature of science; 4) there were differences within their understandings about subconcepts of the nature of science.