정보교육학회논문지 (Journal of The Korean Association of Information Education)

  • 제25권6호
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  • Pages.935-945
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  • 2021
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  • 1229-3245(pISSN)
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  • 2733-8428(eISSN)
한국정보교육학회 (Korea Association of Information Education)
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빅데이터 분석을 통한 아두이노 강의에 대한 사회적 인식

Social perception of the Arduino lecture as seen in big data

  • 투고 : 2021.10.16
  • 심사 : 2021.11.21
  • 발행 : 2021.12.31
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초록

이 연구의 목적은 빅데이터 분석 방법을 이용하여 아두이노 강의에 대한 사회적 인식을 분석하는 데 있다. 이를 위해 네이버 사이트의 블로그, 카페, 뉴스 채널에서 '아두이노+강의'를 검색 키워드로 2012년 1월부터 2021년 5월까지의 데이터를 텍스톰 사이트로 수집하였다. 수집된 데이터는 텍스톰 사이트를 이용하여 정제하였으며, 텍스톰 사이트, Ucinet 6, Netdraw 프로그램을 이용하여 텍스트 마이닝 분석과 의미 연결망 분석을 수행하였다. 빈도 분석, TF-IDF 분석, 연결 중심성 등의 텍스트 마이닝 분석 결과 '교육', '코딩' 등이 상위 키워드임을 확인하였다. 의미 연결망 분석을 위해 CONCOR 분석을 수행한 결과 '아두이노 관련 교육', '피지컬 컴퓨팅 관련 강의', '아두이노 특강', 'GUI 프로그래밍' 등 4개의 군집을 확인할 수 있다. 이 연구를 통해 인터넷상에서 아두이노 강의와 관련하여 일반 대중들의 여러 가지 의미 있는 사회적 인식을 확인할 수 있었다. 이 연구의 결과는 아두이노 강의를 준비하는 교수자나 해당 주제를 연구하는 연구자, 나아가 소프트웨어 교육이나 코딩 교육과 관련 정책을 수립하는 정책 입안자들에게 의미 있는 시사점을 제공하는 자료로 활용될 것이다.

The purpose of this study is to analyze the social perception of Arduino lecture using big data analysis method. For this purpose, data from January 2012 to May 2021 were collected using the Textom website as a keyword searched for 'arduino + lecture' in blogs, cafes, and news channels of NAVER website. The collected data was refined using the Textom website, and text mining analysis and semantic network analysis were performed by opening the Textom website, Ucinet 6, and Netdraw programs. As a result of text mining analysis such as frequency analysis, TF-IDF analysis, and degree centrality it was confirmed that 'education' and 'coding' were the top keywords. As a result of CONCOR analysis for semantic network analysis, four clusters can be identified: 'Arduino-related education', 'Physical computing-related lecture', 'Arduino special lecture', and 'GUI programming'. Through this study, it was possible to confirm various meaningful social perceptions of the general public in relation to Arduino lecture on the Internet. The results of this study will be used as data that provides meaningful implications for instructors preparing for Arduino lectures, researchers studying the subject, and policy makers who establish software education or coding education and related policies.

키워드

과제정보

이 논문은 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No. 2021R1F1A104755011).

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