• Journal of The Korean Association For Science Education
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• v.11 no.2
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• pp.133-142
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• 1991

The purpose of this study is to develop a data base system for the information on research and development of science education. As the first step of this study and development, a classification system for the research and development materials was devised after discussing the process of science education and the research and development of science education. The classification system has nine main categories : 1. area, 2. subject, 3. behavior, 4. skill, 5. support, 6. type, 7. materials, 8. language, and 9. the others, each of which has one or two levels of subcategory. This classification system was revised and supplemented through the theoretical analysis by speci.diSts and the practical classification of master's theses and doctoral dissertations from the Department of Science Education, Seoul National University. But it still needs more revision and enlargement through the continuous application and analysis.

• The Korean Journal of Health Service Management
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• v.4 no.2
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• pp.85-95
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• 2010

This study was to understand perception level and education need on hospice, and to development effective education contents of hospice for medical students. Descriptive survey research design was used. Participants were 426 and the data collecting period was from July. 22. to July. 29. in 2008. The data were analyzed using descriptive analysis, chi-square test, Wilcoxon's signed rank test. The participants experiencing in hospice education program demonstrated higher perception level and education need about hospice than non-participants. Also, The participants experiencing in hospice education showed more concerning on effective education contents of hospice than non-participants. Therefore, hospice education program must be prepared in a continual and systematic way in order to provide for effective education of medical students in Korea.

• Journal of information and communication convergence engineering
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• v.18 no.4
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• pp.216-221
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• 2020

Artificial intelligence (AI), an essential skill of the Fourth Industrial Revolution, is being actively taught in higher education; however, AI education is only in the preparatory stage in elementary, middle, and high schools. Investigating various newspaper articles related to AI education to date can aid in basic data collection, which is an important process in the preparatory stage. Accordingly, 13,378 newspaper articles were collected from a total of 21 newspapers, and five topics were extracted using the latent Dirichlet allocation (LDA)-based topic model along with frequency analysis. Newspaper articles from the early 2000s expanded to technologies related to the Fourth Industrial Revolution. Accordingly, education in AI fields should be linked with education in AI-based technology. In addition, efforts should be made to secure the continuity and sequence of AI education in cooperation with related higher institutions and companies.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.162-171
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• 2020

The purpose of this study is to examine the social perception of disaster safety education for young children based on Textom big data and to explore the direction of young children's disaster safety education. Researchers collected and analyzed online text data using the keywords 'young children+disaster+safety education' from portal websites from 2014 to 2017. The raw data were then subjected to first and second data refinement process. Based on the frequency analysis results, 50 keywords were selected, and the selected keywords were converted into matrix data for network analysis. The results of the study are: first, the most frequently appeared keyword together with young children's disaster safety education was 'education', followed by 'experience', 'kindergarten', 'prevention', and 'school.' Second, keywords with high centrality in the analysis of centrality also were 'education', 'experience', and 'prevention'. In addition, keywords like 'prevention', 'life', and 'evacuation' appear higher in connection-centricity than frequency ranking, which means that the degree of connection between the words is high. These results suggest that young children need education in during early childhood in order to improve their disaster safety skills, and disaster safety education should be accomplished through 'prevention' and 'experience' in early childhood education institutions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.83-92
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• 2023

The purpose of this research is to develop a creative education program that utilizes AI education program based on big data for general education high schools, and to investigate its effectiveness. In order to achieve the purpose of the research, we developed a creative education program using artificial intelligence based on big data for first-year general high school students, and carried out on-site classes at schools and a validation process by experts. In order to measure the creative problem-solving ability and class satisfaction of high school students, a creative problem-solving ability test was conducted before and after the program application, and a class satisfaction test was conducted after the program. The results of this study are as follows. First, AI education program based on big data were statistically effective to improve the creative problem solving ability according to independent sample t test about 'problem discovery and analysis', 'idea generation', 'execution plan', 'conviction and communication', and 'innovation tendency' except 'execution', 'the difference between pre- and post-scores of male student and female student' on first year high school students. Secondly, in satisfaction conducted after classes of AI education program based on big data, the average of 'Satisfaction', 'Interest', 'Participation', 'Persistence' were 3.56 to 3.92, and the overall average was 3.78. Therefore, it was investigated that there was a lesson effect of the AI education program based on big data developed in this research.

• Journal of Practical Engineering Education
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• v.12 no.1
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• pp.23-29
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• 2020

Data generated by the development of ICT, the diversification of ICT devices and services and the expansion of social media are categorized as big data characterized by the amount, variety and speed of the data. The spread of the use of big data is expected to have the effects of identifying the status quo by analyzing data in all industries, predicting the future, and creating opportunities to apply it. However, while it is imperative for these things to be done, the nation still lacks professional training institutions or curricula. In this case study, we will investigate and compare the state of education for the training of big data personnel in Korea, find out what level and level of education is being trained to nurture balanced professionals, and prepare an opportunity to think about how it can help students create value at a time when the need for education is growing in the wake of awareness of big data.

• Journal of Creative Information Culture
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• v.5 no.3
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• pp.215-223
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• 2019

The wave of the information age gradually accelerates, and fusion analysis solutions that can utilize these knowledge data according to accumulation of various forms of big data such as large capacity texts, sounds, movies and the like are increasing, Reduction in the cost of storing data accordingly, development of social network service (SNS), etc. resulted in quantitative qualitative expansion of data. Such a situation makes possible utilization of data which was not trying to be existing, and the potential value and influence of the data are increasing. Research is being actively made to present future-oriented education systems by applying these fusion analysis systems to the improvement of the educational system. In this research, we conducted a big data analysis on Twitter, analyzed the natural language of the data and frequency analysis of the word, quantitative measure of how domestic windows education problems and outcomes were done in it as a solution.

• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.81-94
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• 2024

This study explores and conducts an in-depth comparison of the epistemic characteristics in different data types utilized in the science inquiries of preservice teachers regarding noise as a risk in everyday life. Focusing on primary and secondary data in the context of science inquiries about noise, we examined how these data types differ in science inquires in terms of inquiry design, data collection, and analyses. The findings reveal that sensor-based primary data enable direct measurement and observation of key phenomena. Conversely, secondary data rely on predetermined measurement methods within a public data system. These differences require different epistemic considerations during the inquiry process. Based on these findings, we discuss the educational implications concerning teaching approaches for science inquiries, teacher education for inquiry teaching, and the development of risk response competencies in preparation for the VUCA (Volatility, Uncertainty, Complexity, and Ambiguity) era.

• School Mathematics
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• v.19 no.4
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• pp.691-712
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• 2017

It is an important to develop teachers' statistical reasoning or thinking by teacher education. In this study, the "comparing two data sets" tasks is focused as a way to develop pre-service elementary teachers' reasoning about core ideas of statistics such as distribution, variability, center, and spread. 6 teams of each 4 pre-service elementary teachers participated on the tasks and their presentations are analyzed based on Pfannkuch's (2006) teachers' inference model in comparing two data sets. As a result, they paid attention to the distribution and variability in the statistical problem solving by the "comparing two data sets" tasks, and used their contextual knowledge to make a statistical decision. In addition, they used some statistics and graphs as the reference for statistical communication, which is expected to provide implications for improving statistical education. The finding implies that the "comparing two data sets" tasks can be used to develop statistical reasoning of pre-service elementary teachers. Some recommendations are suggested for teacher education by these tasks.

• 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.