• 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 of Information Education
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• v.25 no.5
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• pp.713-721
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• 2021

As the Ministry of Education has introduced AI education in earnest in the 2022 revised curriculum, there is growing sympathy for the need for data-related education along with AI education. In order to develop the competence to understand and utilize artificial intelligence properly, the understanding and utilization competence of data must be based on it. In this study, a data-driven problem solving SW education program using microbit was developed by synthesizing the results of demand analysis and previous research analysis. The data-driven problem solving education program was developed with educational elements that can be applied to elementary school students among the contents of data science. Through the program developed in this study, education that combines various topics and subjects can be linked based on real-life data. Furthermore, based on an understanding of data, it will lay the foundation for a more substantial AI education program.

• Knowledge Management Research
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• v.19 no.1
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• pp.133-146
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• 2018

This study develops an Education framework for users who need public open data for workplace etiquette education in a timely manner by mobile application. It facilitates utilizing efficiently Workplace etiquette contents that scattered in various platforms such as blogs, Youtube and web-sites run by private education agencies. Furthermore, it makes Public open data for workplace etiquette through gathering 'metadata', which is a comprehensive source of workplace etiquette. Accordingly, framework changes recognition about necessity of workplace etiquette education positively and suggests method that can promote effective workplace etiquette education. If the system in the study can provide public open data of workplace etiquette education, many young job applicants and workers will have a proper perception on it and sound workplace etiquette culture will be settled in the companies. Public data has been rising as a vital national strategic asset these days. Hopefully the public data will pave a way to discover the blue ocean in the market and open up a new type of businesses.

• Journal of The Korean Association of Information Education
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• v.3 no.1
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• pp.75-85
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• 1999

The purpose of the paper is to apply a Data Mining method to Data Base System for more efficient educational data used in elementary and secondary education. First, this study investigated the whole contents of Data Mining and technique relation to Machine Learning. Mainly Data Base Systems in education are general life checking, record of health, and score reports. We suggested Data Mining method and Machine Learning when we search for information of usefulness in a particular representational form or a set of such representations in data. Also, we propose the problem and the solution when using data mining techniques in education.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.393-400
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• 2021

Data science is a scientific discipline that defines problems while finding meaningful information from collected data to solve problems. Along with artificial intelligence technology, the field of data utilization is gradually expanding, and awareness of the importance of data science education is also increasing. Despite the rapid growth of the domestic data industry market, it has recently been predicted that the shortfall of data experts will reach 31.4% within the next 5 years according to an analysis of the current status of the data industry by the Korea Data Agency. In the field of elementary education, various studies have been conducted to introduce data science in order to improve students' computational thinking and creativity. This paper proposed the contents of data science lectures developed for the purpose of educating elementary school teachers, who are mostly non-majors in the computer field. The developed contents were applied to a group of elementary school teachers attending graduate school for artificial intelligence convergence education. Points for improvement were derived by identifying the contents that were difficult for learners to understand and analyzing the causes of difficulty.

• Korean Medical Education Review
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• v.24 no.2
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• pp.156-171
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• 2022

The purpose of this study was to establish a model for constructing longitudinal data for medical school, and to structure cohort and longitudinal data using data from Yonsei University College of Medicine (YUCM) according to the established input-environment-output (I-E-O) model. The study was conducted according to the following procedure. First, the data that YUCM has collected was reviewed through data analysis and interviews with the person in charge of each questionnaire. Second, the opinions of experts on the validity of the I-E-O model were collected through the first expert consultation, and as a result, a model was established for each stage of medical education based on the I-E-O model. Finally, in order to further materialize and refine the previously established model for each stage of medical education, secondary expert consultation was conducted. As a result, the survey areas and time period for collecting longitudinal data were organized according to the model for each stage of medical education, and an example of the YUCM cohort constructed according to the established model for each stage of medical education was presented. The results derived from this study constitute a basic step toward building data from universities in longitudinal form, and if longitudinal data are actually constructed through this method, they could be used as an important basis for determining major policies or reorganizing the curricula of universities. These research results have implications in terms of the management and utilization of existing survey data, the composition of cohorts, and longitudinal studies for many medical schools that are conducting surveys in various areas targeting students, such as lecture evaluation and satisfaction surveys.

• Journal of Engineering Education Research
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• v.26 no.4
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• pp.22-35
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• 2023

As information and communication technology has developed remarkably, it has become possible to analyze various types of large-volume data generated at a speed close to real time, and based on this, reliable value creation has become possible. Such big data analysis is becoming an important means of supporting decision-making based on scientific figures. The purpose of this study is to develop a big data analysis tool that can analyze large amounts of data generated through engineering education. The tasks of this study are as follows. First, a database is designed to store the information of entries in the National Creative Capstone Design Contest. Second, the pre-processing process is checked for analysis with big data analysis tools. Finally, analyze the data using the developed big data analysis tool. In this study, 1,784 works submitted to the National Creative Comprehensive Design Contest from 2014 to 2019 were analyzed. As a result of selecting the top 10 words through topic analysis, 'robot' ranked first from 2014 to 2019, and energy, drones, ultrasound, solar energy, and IoT appeared with high frequency. This result seems to reflect the current core topics and technology trends of the 4th Industrial Revolution. In addition, it seems that due to the nature of the Capstone Design Contest, students majoring in electrical/electronic, computer/information and communication engineering, mechanical engineering, and chemical/new materials engineering who can submit complete products for problem solving were selected. The significance of this study is that the results of this study can be used in the field of engineering education as basic data for the development of educational contents and teaching methods that reflect industry and technology trends. Furthermore, it is expected that the results of big data analysis related to engineering education can be used as a means of preparing preemptive countermeasures in establishing education policies that reflect social changes.

• Journal of Korea Multimedia Society
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• v.19 no.9
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• pp.1710-1722
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• 2016

With the advancement of information and communications technologies and the universal dissemination of smartphones, ICT-utilizing education is also getting the limelight. In the recent ICT-utilizing education, teachers and learners produce massive digital data by consulting massive information on the Internet, and the produced data is filtered in the process of education and utilized for the current and next educational programs. In order to construct the data well-suited for education from massive data available on the Internet, it is important to verify the quality of the educational data. To this end, we propose an educational website that can provide the data satisfying visual needs demanded by learners in terms of utilizing a digital curation system. In this paper, we also present a design and implementation of the website that non-ICT majors can easily use, which in turn enables them to conduct the education of creative personality utilizing image and video contents.

• 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 Association of Information Education
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• v.25 no.3
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• pp.459-469
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• 2021

In this paper, a case study of basic data science practice education for field teachers and pre-service teachers was studied. In this paper, for basic data science education, spreadsheet software was used as a data collection and analysis tool. After that, we trained on statistics for data processing, predictive hypothesis, and predictive model verification. In addition, an educational case for collecting and processing thousands of public big data and verifying the population prediction hypothesis and prediction model was proposed. A 34-hour, 17-week curriculum using a spreadsheet tool was presented with the contents of such basic education in data science. As a tool for data collection, processing, and analysis, unlike Python, spreadsheets do not have the burden of learning program- ming languages and data structures, and have the advantage of visually learning theories of processing and anal- ysis of qualitative and quantitative data. As a result of this educational case study, three predictive hypothesis test cases were presented and analyzed. First, quantitative public data were collected to verify the hypothesis of predicting the difference in the mean value for each group of the population. Second, by collecting qualitative public data, the hypothesis of predicting the association within the qualitative data of the population was verified. Third, by collecting quantitative public data, the regression prediction model was verified according to the hypothesis of correlation prediction within the quantitative data of the population. And through the satisfaction analysis of pre-service and field teachers, the effectiveness of this education case in data science education was analyzed.