• Title/Summary/Keyword: 에듀 테크

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Online Course Evaluation Method by Using Automatic Classification Technology (자동 분류 기술을 활용한 온라인 강의 평가 방법)

  • Lee, Yong-Bae
    • Journal of The Korean Association of Information Education
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    • v.24 no.4
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    • pp.291-300
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    • 2020
  • Although the need for international online courses and the number of online learners has been rapidly increasing, the online class evaluation has been mostly relying on the quantitative survey analysis. So a more objective evaluation method has to be developed to more accurately assess online course satisfaction. This study highlights the benefits of using big data analysis from the bulletin board messages of online learning system as a method to evaluate the online courses. In fact, automatic classification technology is recognized as an important technology among big data analysis techniques. Our team applied this technique to evaluate the online courses. From the delphi analysis results, suggested method was concluded that the evaluation items and classification results are suitable for online course evaluation and applicable in schools or institutions. This study has confirmed that the rapidly accumulating big data analysis technology can be successfully applied to the education sector with the least change. It also diagnosed a meaningful possibility to expand the big data analysis for further application.

A Study on Research Trends in Metaverse Platform Using Big Data Analysis (빅데이터 분석을 활용한 메타버스 플랫폼 연구 동향 분석)

  • Hong, Jin-Wook;Han, Jung-Wan
    • Journal of Digital Convergence
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    • v.20 no.5
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    • pp.627-635
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    • 2022
  • As the non-face-to-face situation continues for a long time due to COVID-19, the underlying technologies of the 4th industrial revolution such as IOT, AR, VR, and big data are affecting the metaverse platform overall. Such changes in the external environment such as society and culture can affect the development of academics, and it is very important to systematically organize existing achievements in preparation for changes. The Korea Educational Research Information Service (RISS) collected data including the 'metaverse platform' in the keyword and used the text mining technique, one of the big data analysis. The collected data were analyzed for word cloud frequency, connection strength between keywords, and semantic network analysis to examine the trends of metaverse platform research. As a result of the study, keywords appeared in the order of 'use', 'digital', 'technology', and 'education' in word cloud analysis. As a result of analyzing the connection strength (N-gram) between keywords, 'Edue→Tech' showed the highest connection strength and a total of three clusters of word chain clusters were derived. Detailed research areas were classified into five areas, including 'digital technology'. Considering the analysis results comprehensively, It seems necessary to discover and discuss more active research topics from the long-term perspective of developing a metaverse platform.