The Journal of the Korea institute of electronic communication sciences (한국전자통신학회논문지)

Korea Institute of Electronic Communication Science (한국전자통신학회)
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Deriving AI-Based E-Learning and Personalized Education Methods to Improve Efficient Class Satisfaction in the Post-Covid-19 Environment Using Statistical Techniques

통계기법을 활용한 Covid-19 이후의 환경에서 효율적인 수업만족도 향상을 위한 AI 기반 e-러닝과 개인화 교육방법 도출방안

  • 이선경 (경동대학교 치기공학과) ;
  • 성정민 (강원대학교 치위생학과)
  • Received : 2022.09.30
  • Accepted : 2022.12.17
  • Published : 2022.12.31
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Abstract

This study was conducted to understand how to derive educational methods to efficiently improve class satisfaction for 130 college students who experienced non-face-to-face classes during the last Covid-19. The appropriateness of class time, improvement of learning effect, continuity of non-face-to-face classes, and use of educational media were set as items corresponding to class satisfaction. Research was attempted to derive an educational method for efficient class satisfaction improvement by grasping the difference and relationship between variables.

지난 Covid-19 시기의 비대면 수업을 겪었던 대학생 130명을 대상으로 효율적인 수업만족도 향상을 위한 교육방법의 도출방안에 대해 파악하고자 본 연구를 실시하였다. 수업시간의 적절성, 학습효과 향상, 비대면수업의 계속성, 교육매체의 이용을 수업만족도에 해당되는 항목으로 설정하고 변인간의 차이와 관계성에 대해 파악하여 효율적인 수업만족도 향상을 위한 교육방법의 도출하기 위해 연구를 시도하였다.

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References

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