The effects of pbl-based data science education program using app inventor on elementary students' computational thinking and creativity improvement

Abstract

This study is to investigate the effect of PBL-based Data Science Education Program using App Inventor on Computational Thinking and Creativity of elementary students. Based on the results of the pre-requisite analysis by Rossett’s demand analysis model, PBL-based Data Science Education program 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’, ‘Elavoration’, ‘Closure’, ‘Average’, and ‘Index’. Therefore, it was confirmed that the PBL-based Data
Science Education Program using App Inventor is effective in improving Computational Thinking and Creativity of elementary student.