• 한국데이터정보과학회:학술대회논문집
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• 2004.10a
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• pp.87-92
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• 2004

본 연구에서는 2003년부터 시행된 일본 고등학교 학습지도요령의 수학과 구성과 성격을 연구하였다. 또한, 교육과정상의 확률통계교육의 구성과 성격 및 편제에 대하여 고찰한 결과, 새 교육과정에 따른 교과위주의 교육과정의 구성과 내용 및 편제의 특징은 통합학습시간 신설로 미국식 주제 교육의 도입, 완전학교 주 5 일제실시, 중고 일관교육, 단위제 고등학교학교 신설, 종합 학교의 설치로 설명된다. 확률통계 교육의 내용과 범위는 과거 교육과정과 크게 달라진 점은 없으나, 7교과 분야 가운데 3 교과 부분에 자료 위주의 실용통계계산 교육과 통계소프트웨어교육 강화가 그 특징이다.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.667-671
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• 2024

Professional job training for government officers emphasizes establishing desirable values as public officials and improving professionalism in public service. To provide customized education, some studies are analyzed factors affecting education satisfaction. However, there is a lack of research predicting education satisfaction with educational contents. Therefore, we propose a deep learning-based regression model that predicts government officer education satisfaction with educational contents. We use education information data for government officer. We use one-hot encoding to categorize variables collected in text format, such as education targets, education classifications, and education types. We quantify the education contents stored in text format as TF-IDF. We train our deep learning-based regression model and validate model performance with 10-Fold Cross Validation. Our proposed model showed 99.87% accuracy on test sets. We expect that customized education recommendations based on our model will help provide and improve optimized education content.

• 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.

• Journal of The Korean Association of Information Education
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• v.26 no.1
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• pp.45-53
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• 2022

The need for artificial intelligence education has emerged, and countries around the world are announcing artificial intelligence strategies. Artificial intelligence education is reflected in the main points of the 2022 revised curriculum general published in Korea. Along with this interest, programs related to artificial intelligence education are being developed, but it is difficult to find artificial intelligence programs for lower grades of elementary school. This study aims to develop a data collection education program for the lower grades of elementary school through a series of analysis-design-development-application-evaluation processes and apply it to first-grade elementary school students to verify its effectiveness. Through the developed program, it is expected that students will be able to understand and feel interested in artificial intelligence, and develop an attitude of collecting data in their daily lives through the process of searching for various types of data in their daily lives.

• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.37-46
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• 2022

The purpose of this study is to provide basic data onto preparing soft landing plan of future education policy by exploring direction of future education for the common good using big data and keyword network analysis. Based on the big data provided by Textom, data was collected under the keyword 'future education + common Good' and then keyword network analysis was performed. As a result of the research, it was found that 'common good', 'social', 'KAIST future warning', 'measures', 'research', 'future education', 'politics' were common keywords in the social awareness of future education for the common good. The results of this study suggest that the social awareness of future education for the common good is related to factors related to human, physical environment, social response, academic interest, education policy, education plan, and related variables, It was closely related. Based on these results, we suggested implications for the support for the preparation of a soft landing plan of future education for the common good.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.183-184
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• 2022

본 연구는 장애인 평생교육 관련 언론사 뉴스 빅데이터를 한국언론재단의 빅카인즈(BIGKinds) 시스템을 이용하여 분석하였다. 본 연구에서는 2000년 1월 1일부터 2020년 12월 31일까지 20년간, 총 54개 언론사에서 보도한 '장애인 평생교육' 관련 뉴스 기사들을 추출하였다. 그 분석대상 뉴스 빅데이터를 대상으로 키워드 트렌드 분석, 언어 네트워크 지도 구현, 연관어 분석(워드클라우드 제시) 등을 진행하였다. 본 연구 결과는 장애인 평생교육 관련 정책 입안 연구 및 실증적인 연구(평생교육 참여 요인 및 효과 등)의 기초자료로 활용될 수 있을 것으로 기대된다.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.691-704
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• 2021

The development of AI technology has brought about a big change in our lives. The importance of AI and data education is also growing as AI's influence from life to society to the economy grows. In response, the OECD Education Research Report and various domestic information and curriculum studies deal with data literacy and present it as an essential competency. However, the definition of data literacy and the content and scope of the components vary among researchers. Thus, we analyze the semantic similarity of words through Word2Vec deep learning natural language processing methods along with the definitions of key data literacy studies and analysis of word frequency utilized in components, to present objective and comprehensive definition and components. It was revised and supplemented by expert review, and we defined data literacy as the 'basic ability of knowledge construction and communication to collect, analyze, and use data and process it as information for problem solving'. Furthermore we propose the components of each category of knowledge, skills, values and attitudes. We hope that the definition and components of data literacy derived from this study will serve as a good foundation for the systematization and education research of AI education related to students' future competency.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.673-676
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• 2002

XML은 모든 분야의 데이터를 저장하고 다른 형태의 데이터로 변화될 수 있는 강한 힘을 지니고 있다. 웹에서의 가상 교육에 대한 데이터도 XML로 저장한다면 한번 저장된 데이터는 어떤 사이트에서든 조금의 수정없이 바로 사용할 수 있다. 물론 이 데이터 구조가 미리 정의되어 모든 사이트에서 이 구조대로 XML 데이터를 만들어야 가능하다. 현재 사이버 교육 사이트들의 강좌 데이터는 데이터베이스에, 데이터베이스에서 데이터를 가져오는 것은 ASP, 가져온 데이터를 사용자에게 서비스하는 최종 산출물은 HTML로 구성되어 있어 이 데이터는 더 이상 가공을 할 수 없게 된다. 즉 각각의 사이버 교육 사이트들의 데이터는 서로 공유될 수 없다. 본 논문은 현재 사이버스쿨의 한계를 벗어날 수 있도록 새로운 표준으로 제안되어진 XML을 이용하여 사이버 강좌 관리시스템을 위한 통일된 XML 데이터 구조를 정의하고 웹에서 어떻게 사용해야 하는지 모델을 제시하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.803-805
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• 2003

교육용 컨텐츠의 중복 개발에 따른 국가적으로 많은 비용이 소요되고 있으며, 이를 해결하기 위해서는 전국적인 컨텐츠 공유시스템의 도입이 절실히 필요하다. 컨텐츠 공유를 위해서는 메타데이터에 대한 이해와 선행 연구가 필요하다. 이 논문에서는 국내 표준 메타 데이터에 관한 선행 연구를 기반으로 하여 교육용 컨텐츠 공유 시스템을 설계 및 구현하고 이를 2개의 교육청에 현장 적용한 결과와 전국 교육정보 공유시스템에 방향을 제시한다.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.917-925
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• 2021

This study aims to specify a constructivism-based instructional method using a modular data analysis tool. The value and meaning of a modular data analysis tool have been examined to be applied in the national curriculum for artificial intelligence education and the process of cultivating problem-solving ability based on computational thinking. The modular data analysis tool visually expresses the cognitive thinking process that forms the schema in equilibrating through assimilation and adjustment. Artificial intelligence education has features that embody abstract knowledge and structure the data analysis module through the represented schema as a BlackBox implemented as an algorithm. Therefore, the value of the modular data analysis tool could be examined because it has the advantage of connecting the conceptual and implicit schema.