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Online Course Evaluation Method by Using Automatic Classification Technology

자동 분류 기술을 활용한 온라인 강의 평가 방법

  • Lee, Yong-Bae (Dept. of Computer Education, Jeonju National University of Education)
  • 이용배 (전주교육대학교 컴퓨터교육과)
  • Received : 2020.06.19
  • Accepted : 2020.07.13
  • Published : 2020.08.31

Abstract

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.

국내외 온라인 강의에 대한 학습자와 프로그램 수요는 증가하고 있지만 이에 대한 평가 방법은 설문지에 의한 정량적인 수치에 의존하고 있으며 객관적인 학습 만족도에 대한 평가 방법은 마련돼 있지 않다는 것이 문제점으로 드러나고 있다. 본 연구에서는 온라인 학습 시스템의 게시판에 있는 빅 데이터 메시지를 분석하여 온라인 강의를 평가하는 방법을 제안하려고 한다. 실제로 빅 데이터 분석기법 중 중요한 기술로 인식되는 자동분류 기법을 적용하여 온라인 강의 평가에 시범 적용해 보았으며 델파이 분석 결과에서도 평가 항목과 분류 결과 등이 온라인 강의 평가에 적합하고 학교나 기관에서 적용해볼 만하다는 결론을 얻었다. 본 연구는 빠르게 축적되고 있는 빅 데이터 분석기술을 가장 변화가 늦은 교육 분야에 적용해 보고 확장 가능성을 진단해보는데 의의가 있다.

Keywords

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