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
- 발행
- 2021 등록KCI API에는 발행일 항목이 없어 원문 등록일을 쓰고 있습니다. 실측으로 발행보다 최대 6년 늦습니다 — 재수집하면 발행연월로 바뀝니다.
- 소속·발행
- 부산대학교
- 출처
- 국내 KCI
- DOI
- 10.37272/JIECR.2021.12.21.6.119
- 원문
- 원문 보기 ↗
개념
키워드
Bigdata, CONCOR, Non-Face-to-Face, Data Literacy, Topic Modeling, Bigdata, CONCOR, Non-Face-to-Face, Data Literacy, Topic Modeling
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’. Th