• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.25-30
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• 2021

With the introduction of AI education in the 2022 Revised Curriculum emphasizing the need for data related education, it is necessary to improve students' data based problem solving skills. This study seeks to study SW education methods to improve students' data based problem solving skills in accordance with these needs. Based on the ADDIE model, the demand analysis survey was conducted on teachers to analyze their needs. Based on the results of the demand analysis, we designed education programs under the theme of data based problem solving skills using microbit. In this study, we raise the importance of data based problem solving and the need for its capabilities. Subsequent studies need to reveal how data based problem solving SW education will demonstrate significant effects on problem solving skills.

• 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.

• Communications of Mathematical Education
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• v.19 no.4 s.24
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• pp.805-822
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• 2005

In Korea, many local university mathematics faculty knew that the institution faced serious student shortage problems and the restructuring and cut actions for such a mathematics major programs. In general, undergraduate mathematics education in korea is in the crisis. In general, lots of mathematics departments in korea was not prepared for such a severe risk. In this article, university mathematics education and research business are studied in the context of the size of korea-usa population, economy(such as GDP), SCI indices. Korea-usa university mathematics education profile data are presented to compare korea-usa university mathematics education business. Lots of precious data on mathematics education are being helped to prepare for the university mathematics education crisis.

• Journal of The Korean Association of Information Education
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• v.19 no.4
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• pp.517-524
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• 2015

In this paper, to find out the direction of interest related to the SW education, SW education news data were gathered and its contents were analyzed. The topic analysis of SW education news was performed by collecting the data of July 23, 2013 to October 19, 2015. By analyzing the relationship among the most mentioned top 20 words with the web crawling using R, the result indicated that the 20 words are the closely relevant data as the thickness of the node size of the 20 words was balancing each other in the co-occurrence matrix graph focusing on the 'SW education' word. Moreover, our analysis revealed that the data were mainly composed of the topics about SW talent, SW support Program, SW educational mandate, SW camp, SW industry and the job creation. This could be used for big data analysis to find out the thoughts and interests of such people in the SW education.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.463-471
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• 2020

Humanity faces the fourth industrial revolution, a time of technological revolution by the collaboration of various industries including the fields of artificial intelligence(AI) and big data. Many countries are focused on fostering AI talent to prevail in the coming technological revolution. While Korea also provides some strategies to enhance the cultivation of AI talent, it is still difficult for Korean undergraduate students to get involved in AI studies. Through on the implementation of 'Big data analysis based AI education', which allows an easier approach to AI education, this paper examined the changes in the attitudes of undergraduate students regarding general AI education. 'Big data analysis based AI education' was provided at undergraduate level for 5.5 weeks (15 hours). The attitudes of undergraduate students were analyzed by pre-postmortem. The results showed there was a significant improvement in confidence and self-directed in regard to receiving AI education. With these results, further active research to develop basic AI education that also increases confidence and self-initiative can be expected.

• Journal of The Korean Association of Information Education
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• v.26 no.6
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• pp.553-566
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• 2022

This study collects social data and academic research data from portal sites and RISS, and analyzes TF-IDF, N-Gram, semantic network analysis, and CONCOR analysis to analyze the social awareness and current aspects of 'AI Literacy' and 'AI Convergence Education'. Through this, we tried to understand the social awareness aspect and the current situation, and to suggest implications and directions. In the social data, the collection of 'AI Convergence Education' was more than twice that of 'AI Literacy', indicating that awareness of 'AI Literacy' was relatively low. In 'AI Literacy', the keyword 'human' in social data showed no cluster to which it belonged, indicating a lack of philosophical interest in and awareness of humanities and AI. In addition, the keyword 'Ministry of Education' showed high frequency, importance, and centrality of connection only in the social data of 'AI convergence education', confirming that 'AI convergence education' is closely related to government policy.

• Korean Journal of Computational Design and Engineering
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• v.20 no.3
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• pp.254-262
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• 2015

This study proposes an approach to Product Data Management (PDM) education for collaborative product data management, which can support collaborative product development process. This approach introduces social media and a PDM system into a framework for PDM education supported by consistent product development process and product data model. It has been applied to two PDM classes and the result shows that the social media in PDM education can support not only experiences of the collaborative product data management but also interactive and informal communications among instructors and participants using integrated social media with product data during courses.

• Journal of Korean Public Health Nursing
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• v.30 no.2
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• pp.221-235
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• 2016

Purpose: This study explored experiences of diabetes education among educators of diabetes. Methods: Data were collected from individual in-depth interviews with 10 nurses and 2 dieticians with had at least 3 years of experience in diabetes education. Data collection was conducted between May 2014 and February 2015. All interviews were recorded and stored as digital audio files, which were then transcribed verbatim. Data were analyzed through qualitative content analysis. Results: Analysis showed that four categories could be derived from the data: 1) barriers of diabetes education from an educator's perspective, 2) barriers of diabetes education form a patient's perspective, 3) facilitating factors of diabetes education from an educator's perspective, and 4) facilitating factors of diabetes education from a patient's perspective. Conclusion: This study suggests the necessity to strengthen the policy systems and financial support at a national level to provide diabetes education with higher quality to patients. In addition, it is required to develop various diabetes education programs with consideration to patient characteristics.

• Research in Community and Public Health Nursing
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• v.15 no.4
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• pp.528-538
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• 2004

Purpose: This study was conducted to investigate the level of awareness about health education in the manpower of public health center. in order to suggest a basis data for the development of a job-training program. Method: The subjects were 96 manpowers of public health centers. Data were collected from August 2nd. 2002 to September 20th using a self reported questionnaire survey. The data were analyzed using frequency. percentile and $x^2-test$. Results: The most necessary of health education according to health promotion service is 'quitting smoking' during the adolescent period. The most necessary of health education media according to health promotion service is 'reducing alcohol intake'. The most efficient media of health education is 'beam projector'. The most necessary capacity of health educator is 'planning capacity of health education'. The most necessary support implementing health education is 'manpower supply'. Conclusion: The level of awareness of health education in the manpower of the public health center are expected to provide basic data for developing job-training programs that might improve advanced knowledge and techniques of health education.

• 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.