IPA를 이용한 스마트러닝 품질관리 요인분석

Analysis of the Factors Influencing Quality Assurance of Smart Learning using IPA

  • Lee, Jun-Hee (Chungbuk National University, Dept, of Management Information Systems)
  • 투고 : 2012.01.10
  • 심사 : 2012.02.26
  • 발행 : 2012.03.31

초록

스마트러닝 품질은 전통적인 교육보다 복잡하고 다양한 요인으로 구성된다. 본 논문에서는 스마트러닝 품질을 콘텐츠, 시스템, 서비스측면에서 살펴보고 문헌연구와 표적집단면접법(FGI)에 의해서 스마트러닝 품질요인을 분류하였다. 설문조사는 리커트식 5점 척도에 의하여 사용자들이 품질요인의 만족도와 중요도를 상대적으로 평가하도록 하였다. 설문지는 39문항으로 구성하였으며 불성실하게 응답한 설문지 8부를 제외하고 112부가 최종분석을 위하여 활용되었다. 수집된 데이터는 SPSS 18.0을 활용하여 통계적으로 분석되었으며, 실증적 검증을 위해서 중요도-만족도 분석이 활용되었다.

Quality in smart learning is composed of many factors, and it is more complicated than the traditional education. This study put emphasis on three aspects of the smart learning quality(contents, systems, services). This study depended mostly on literature review, supplemented by FGI(Focus Group Interview) for classification of the smart learning quality factors. On a 5 point Likert scale, the survey enables the users to rate the relative importance of factors, followed by another factor performance rating. The questionnaire were composed of 39 questions. 8 questionnaire sheets were excluded which were not properly filled in or unsuitable for the analysis, and therefore, a total of 112 questionnaires were used for the final analysis. Collected data was statistically analyzed using the SPSS 18.0 for Windows statistical package. Importance-performance analysis(IPA; gap between importance and performance) is used for the empirical test.

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