• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.441-442
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• 2014

최근 IT 시장에서는 빅 데이터가 새로운 패러다임으로 주목받으면서 모든 분야에서 빅 데이터를 활용하기 위해 많은 노력을 기울이고 있다. 빅 데이터를 활용한 스마트교육에서는 학생들의 모든 학습활동 자료가 쉽게 수집될 수 있을 뿐만 아니라 모든 학생의 자료 또한 수집이 가능하다. 빅 데이터를 통한 학습자 맞춤형 교육은 현재 진행되는 스마트 교육의 진정한 효과로써 나타날 수 있을 것으로 여겨진다. 따라서 본 논문에서는 학습자의 학업 성취도 향상의 요인인 학습 내용에 대한 관심과 흥미를 기준으로 분석한 빅 데이터를 활용하는 개인 맞춤형 교육 시스템을 설계하였다.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.233-241
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• 2023

This study analyzes the construction status of digital employment services in Korea and presents the direction of continuous advancement and development of digital employment services based on overseas cases and the latest digital technology development trends. Find out the specific digitalization promotion strategies and current status of major countries such as Belgium, Australia, the United Kingdom, Germany, France, and the United States. In addition, in order to present a plan for the development of digital employment services in Korea, we will propose a plan to expand digital employment services to online employment centers through individual and customized employment services, data openness, and expansion of public-private collaboration through digital employment services using AI and big data.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.4
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• pp.341-349
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• 2016

To meet the requirements in the global age, the necessity and importance of global education in the field of education is rapidly increasing. However, according to the viewpoint on global education, a general consensus of its definition and model is not clear yet and the substantial outcome falls short of our expectation due to high cost, low effectiveness, and lack of persistency in the process of global education. Furthermore, there has been little research on global education for fostering global capabilities of pre-teachers. In this research, we compared and analyzed the ongoing global education programs for training global teachers in domestic universities. Also, through a study on IT fusion education system for tackling the difficulties in global education, we examined appropriate IT fusion education methods. In particular, beased on big data analysis techniques, we presented a recommendation system to complete a global curriculum, which can help a dual-degree or exchange student program.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.240-243
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• 2021

Recently, there have been research results of applying Big data and AI technologies to the evaluation and individual learning for education. It is information technology innovations that collect dynamic and complex data, including student personal records, physiological data, learning logs and activities, learning outcomes and outcomes from social media, MOOCs, intelligent tutoring systems, LMSs, sensors, and mobile devices. In addition, e-learning was generated a large amount of learning data in the COVID-19 environment. It is expected that learning analysis and AI technology will be applied to extract meaningful patterns and discover knowledge from this data. On the learner's perspective, it is necessary to identify student learning and emotional behavior patterns and profiles, improve evaluation and evaluation methods, predict individual student learning outcomes or dropout, and research on adaptive systems for personalized support. This study aims to contribute to research in the field of education by researching and classifying machine learning technologies used in anomaly detection and recommendation systems for educational data.

• Journal of the Korean Dietetic Association
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• v.23 no.2
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• pp.192-201
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• 2017

This study compared the Center for Children's Foodservice Management in 2012, 2014, and 2016 using big data and opinion mining. The data on the Center for Children's Foodservice Management were collected from the portal site, Naver, from January 1 to December 31 in 2012, 2014, & 2016 and analyzed by keyword frequency analysis, influx route analysis of data, polarity analysis via opinion mining, and positive and negative keyword analysis by polarity analysis. The results showed that nursery had the highest rank every year and education supported by Center for Children's Foodservice Management has increased significantly. The influx of data has increased through the influx route analysis of data. Blog and $caf\acute{e}e$, which have a considerable amount of information by the mother should be helpful for use as public relations and participation recruitment paths. By polarity analysis using opinion mining, the positive image of the Center for Children's Foodservice Management was increased. Therefore, the Center for Children's Foodservice Management was well-suited to the purpose and the interests of the people has been increasing steadily. In the near future, the Center for Children's Foodservice Management is expected have good recognition if various programs to participate with family are developed and advertised.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.480-482
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• 2021

The core competence is an increasingly important concept that should be reflected in school education in the abilities that need to be developed over a lifetime. In this study, we analyzed the relationship between core competence and employment of students who took core competence-based training courses for those who graduated from D-University, and reflected it in the improvement of the D-University education course and the university education policy. We plan to utilize the results of future analysis as a material for raising the employment rate and developing human resources that match the human resources image of D-University.

• 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 Industrial Convergence
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• v.20 no.6
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• pp.27-35
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• 2022

The purpose of this study is to analyze the metaverse-related issues in the news big data from an educational perspective, explore their characteristics, and provide implications for the educational applicability of the metaverse and future education. To this end, 41,366 cases of metaverse-related data searched on portal sites were collected, and weight values of all extracted keywords were calculated and ranked using TF-IDF, a representative term weight model, and then word cloud visualization analysis was performed. In addition, major topics were analyzed using topic modeling(LDA), a sophisticated probability-based text mining technique. As a result of the study, topics such as platform industry, future talent, and extension in technology were derived as core issues of the metaverse from an educational perspective. In addition, as a result of performing secondary data analysis under three key themes of technology, job, and education, it was found that metaverse has issues related to education platform innovation, future job innovation, and future competency innovation in future education. This study is meaningful in that it analyzes a vast amount of news big data in stages to draw issues from an education perspective and provide implications for future education.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.105-111
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• 2022

Multiple-choice survey types have been mainly performed to analyze students' needs for online classes. However, in order to analyze the exact needs of students, unstructured data analysis by answer for essay question is required. Big data is applied in various fields because it is possible to analyze unstructured data. This study aims to investigate and analyze what students want subjects or topics for software lecture in general education that process on non-face-to-face online teaching methods. As for the experimental method, keyword analysis and association analysis of big data were performed with unstructured data by giving a subjective questionnaire to students. By the result, we are able to know the keyword what the students want for software lecture, so it will be an important data for planning and designing software lecture of liberal arts in the future as students can grasp the topics they want to learn.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.1-7
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• 2019

The objective of this study is to examine the trends in big data. Research abstracts were extracted from 4,019 articles, published between 1995 and 2018, on Web of Science and were analyzed using topic modeling and time series analysis. The 20 single-term topics that appeared most frequently were as follows: model, technology, algorithm, problem, performance, network, framework, analytics, management, process, value, user, knowledge, dataset, resource, service, cloud, storage, business, and health. The 20 multi-term topics were as follows: sense technology architecture (T10), decision system (T18), classification algorithm (T03), data analytics (T17), system performance (T09), data science (T06), distribution method (T20), service dataset (T19), network communication (T05), customer & business (T16), cloud computing (T02), health care (T14), smart city (T11), patient & disease (T04), privacy & security (T08), research design (T01), social media (T12), student & education (T13), energy consumption (T07), supply chain management (T15). The time series data indicated that the 40 single-term topics and multi-term topics were hot topics. This study provides suggestions for future research.