[국내논문]앱인벤터를 활용한 PBL 기반 데이터 사이언스 교육 수업이 초등학생의 컴퓨팅 사고력과 창의성 향상에 미치는 효과 The Effects of PBL-based Data Science Education classes using App Inventor on elementary student Computational Thinking and Creativity improvement원문보기
본 연구는 앱인벤터를 활용한 PBL 기반 데이터 사이언스 교육 수업이 초등학생의 컴퓨팅 사고력과 창의성에 미치는 영향을 알아보기 위한 연구이다. Rossett의 요구분석 모형에 의한 사전 요구분석 결과를 바탕으로 ISD모형인 ADDIE 모형의 절차에 따라 PBL 기반의 데이터 사이언스 교육 수업을 설계하여 초등학생을 대상으로 42차시의 수업을 실시하였다. 대응표본 t검정 결과, 컴퓨팅 사고력은 컴퓨팅 사고력은 사후 검사에서 통계적으로 유의미하게 향상되었음이 입증되었다. 또한, 대응표본 t검정, Wilcoxon 부호 순위 검정 결과 창의성의 하위 요소인 '독창성', '정교성', '성급한 종결에 대한 저항'과 '창의성 평균', '창의성 지수'에서 통계적으로 유의미하게 향상된 것으로 나타났다. 따라서, 앱인벤터를 활용한 PBL 기반 데이터 사이언스 교육 수업이 초등학생의 컴퓨팅 사고력과 창의성 향상에 효과가 있음을 확인할 수 있었다.
본 연구는 앱인벤터를 활용한 PBL 기반 데이터 사이언스 교육 수업이 초등학생의 컴퓨팅 사고력과 창의성에 미치는 영향을 알아보기 위한 연구이다. Rossett의 요구분석 모형에 의한 사전 요구분석 결과를 바탕으로 ISD모형인 ADDIE 모형의 절차에 따라 PBL 기반의 데이터 사이언스 교육 수업을 설계하여 초등학생을 대상으로 42차시의 수업을 실시하였다. 대응표본 t검정 결과, 컴퓨팅 사고력은 컴퓨팅 사고력은 사후 검사에서 통계적으로 유의미하게 향상되었음이 입증되었다. 또한, 대응표본 t검정, Wilcoxon 부호 순위 검정 결과 창의성의 하위 요소인 '독창성', '정교성', '성급한 종결에 대한 저항'과 '창의성 평균', '창의성 지수'에서 통계적으로 유의미하게 향상된 것으로 나타났다. 따라서, 앱인벤터를 활용한 PBL 기반 데이터 사이언스 교육 수업이 초등학생의 컴퓨팅 사고력과 창의성 향상에 효과가 있음을 확인할 수 있었다.
The purpose of this study is to investigate the effects of Data Science Education classes using PBL-based App Inventor on elementary student Computational Thinking and Creativity. Based on the results of the pre-requisite analysis by Rossett's demand analysis model, PBL-based Data Science Education ...
The purpose of this study is to investigate the effects of Data Science Education classes using PBL-based App Inventor on elementary student Computational Thinking and Creativity. Based on the results of the pre-requisite analysis by Rossett's demand analysis model, PBL-based Data Science Education class was designed according to the procedure of ADDIE model which is 42 hours of classroom instruction for elementary student. As a result of the Paired t-test, it was proved that the Computational Thinking was statistically significantly improved in the post-test. In addition, as a result of the Paired t-test and Wilcoxon's signed rank test, it was found that the sub-factors of Creativity were 'Originality', 'Fluency', 'Closure', 'Average', and 'Index'. Therefore, it was confirmed that the PBL-based Data Science Education class using App Inventor is effective in improving Computational Thinking and Creativity of elementary student.
The purpose of this study is to investigate the effects of Data Science Education classes using PBL-based App Inventor on elementary student Computational Thinking and Creativity. Based on the results of the pre-requisite analysis by Rossett's demand analysis model, PBL-based Data Science Education class was designed according to the procedure of ADDIE model which is 42 hours of classroom instruction for elementary student. As a result of the Paired t-test, it was proved that the Computational Thinking was statistically significantly improved in the post-test. In addition, as a result of the Paired t-test and Wilcoxon's signed rank test, it was found that the sub-factors of Creativity were 'Originality', 'Fluency', 'Closure', 'Average', and 'Index'. Therefore, it was confirmed that the PBL-based Data Science Education class using App Inventor is effective in improving Computational Thinking and Creativity of elementary student.
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