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메타버스 플랫폼 게더타운 기반 비대면수업의 학습만족도와 지속이용의도에 미치는 요인 연구

A Study on Factors Affecting Learning Satisfaction and Continuous Use Intention in Non-face-to-face Classes based on Metaverse Platform Gather.Town

  • 김나랑 (동아대학교 경영정보학과) ;
  • 김연국 (동아대학교 경영정보학과)
  • 투고 : 2023.02.21
  • 심사 : 2023.03.14
  • 발행 : 2023.04.30

초록

본 연구의 목적은 메타버스 기반 비대면 수업에서 학습만족도와 지속이용의도에 영향을 미치는 요인을 찾아내는데 있다. 이를 위해 기술수용모형과 정보시스템 성공모형을 토대로 가설을 세우고, 메타버스 플랫폼 중 게더타운을 이용한 수업 경험이 있는 학생을 대상으로 2021년 11월 22일에서 2022년 1월 3일까지 온라인과 오프라인을 기반으로 설문조사를 실시하여 불성실한 응답을 한 설문지를 제외하고 122부를 대상으로 PLS 구조방정식을 이용하여 분석 하였다. 분석결과 플랫폼 품질요인 모두 용이성에 영향을 미치지만, 유용성에서는 콘텐츠 품질만 영향을 가지고 있었다. 용이성은 유용성에 영향을 미치고, 유용성과 용이성이 학습만족도에, 유용성과 학습만족도가 지속이 용의도에 정(+)의 영향을 가지고 있었다. 본 연구의 의의는 메타버스 기반 비대면 수업에서 학습만족도와 지속이용의도에 영향을 미치는 변수를 실증적으로 분석하였다는 점에 있다. 후속 연구에서는 게더타운을 비롯한 다양한 메타버스 기반 플랫폼을 대상으로 학습만족도와 지속이용의도에 영향을 미치는 변수들에 대한 추가 연구가 필요하다.

This study aims to determine the factors that affect learning satisfaction and continuous use intention in metaverse-based non-face-to-face classes. Therefore, a hypothesis was established based on the technology acceptance model and information system success model, and a survey was conducted from November 22, 2021 to January 03, 2022 for students who had class experience using Gather.town-a metaverse platform. PLS Structural Equation was conducted on 122 copies, excluding the questionnaires with insincere responses. The results reveal that "all platform quality" factors influenced "easiness," "content quality" influenced "usefulness," "easiness" influenced "usefulness," "easiness" and "usefulness" influenced "learning satisfaction," "usefulness" and "learning satisfaction" had a positive effect on "continuous use intention." This study is significant because it empirically analyzes the variables that affect learning satisfaction and continuous use intention in metaverse-based non-face-to-face classes. In follow-up studies, additional research is required on the variables that affect learning satisfaction and continuous use intention targeting various metaverse-based platforms, including Gather.town.

키워드

과제정보

이 논문은 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No.2022R1F1A1063537)

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