CONCOR 빅데이터 분석 기반의 비대면 교육 활성화 방안 연구: 데이터 리터러시 관점 (A Study for Activation of Non-Face-to-Face Education based on CONCOR Big Data Analytics: Data Literacy Perspectives)

서지정보

· 발행기관 : 한국인터넷전자상거래학회
· 수록지 정보 : 인터넷전자상거래연구 / 21권 / 6호 / 119 ~ 132페이지
· 저자명 : 정대현, 김상희

초록

Recently, ‘ontact’ has newly emerged as the hottest keyword in the non-face-to-face era. In this study, the author aims to analyze the CONCOR big data in an attempt to investigate possible ways to promote non-face-to-face education from the data literacy perspectives. In this study, data crawling involves use of Textom to collect and analyze data during the last year, 2020 from Naver (blog, café, news, web doc, knowledge-in, academic information), Google and Youtube. Regarding non-face-to-face and face-to-face issues, the collected big data is analyzed by the UCINET solution analysis method, thus yielding a matrix of keywords and the resulting 50 keywords most frequently used are suggested depending on the node size by using the visualization method. Finally, those areas applicable to various fields are suggested as a result.
According to the CONCOR analysis results, five big groups are suggested. First, keywords including task, platform, implementation, quality, satisfaction, data and so on form a group that is named as ‘platform implementation’. Second, keywords including untact, video, new deal, free, subscription and so on form a group that is named as ‘ontact market’. Third, keywords including real time, online, face-to-face, contents, problems and so on form a group that is named as ‘online contents’. Fourth, keywords including Youtube, program, education, experts, education center and so on form a group named as ‘channel diversity’. Fifth, keywords including internet, digital, knowledge, smart, development and so on form a group that is named as ‘digitalization’.

영어초록

Recently, ‘ontact’ has newly emerged as the hottest keyword in the non-face-to-face era. In this study, the author aims to analyze the CONCOR big data in an attempt to investigate possible ways to promote non-face-to-face education from the data literacy perspectives. In this study, data crawling involves use of Textom to collect and analyze data during the last year, 2020 from Naver (blog, café, news, web doc, knowledge-in, academic information), Google and Youtube. Regarding non-face-to-face and face-to-face issues, the collected big data is analyzed by the UCINET solution analysis method, thus yielding a matrix of keywords and the resulting 50 keywords most frequently used are suggested depending on the node size by using the visualization method. Finally, those areas applicable to various fields are suggested as a result.
According to the CONCOR analysis results, five big groups are suggested. First, keywords including task, platform, implementation, quality, satisfaction, data and so on form a group that is named as ‘platform implementation’. Second, keywords including untact, video, new deal, free, subscription and so on form a group that is named as ‘ontact market’. Third, keywords including real time, online, face-to-face, contents, problems and so on form a group that is named as ‘online contents’. Fourth, keywords including Youtube, program, education, experts, education center and so on form a group named as ‘channel diversity’. Fifth, keywords including internet, digital, knowledge, smart, development and so on form a group that is named as ‘digitalization’.

참고자료

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