• The Journal of Korean Association of Computer Education
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• v.19 no.5
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• pp.1-9
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• 2016

In this paper, We evaluated students' computational thinking in elementary school for SW education. Also, we analyzed on the difference of students' computational thinking according to the level of school's educational information. As a result, We confirmed that students' computational thinking were deferent according to the experience of schoolmaster's SW education and the ICT infra of school. In particular, students' computational thinking were meaningfully deferent according to the SW education experience of schoolmaster, the number of mobile devices for education and the speed of school network. Accordingly, we proposed the policy to heighten the effect of SW education. The policy were the extension of SW education for teacher, school network infra and mobile device for education.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.259-267
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• 2020

The purpose of this study is to analyze the effects of computational thinking class using ARCS model to increase students' learning motivation. Then, this study designed the detailed instruction strategy according to each motivation factor(Attention, Relevance, Confidence, Satisfaction) of ARCS through the previous study on computational thinking education and ARCS model. The results of the ARCS test were compared between the experimental group to which the ARCS model was applied and the control group to which the general class was conducted. As a result, students in the experimental group showed significantly higher motivation for learning about computational thinking. In particular, the learning motivation of computer-related majors was significantly higher than that of the control group. In addition, majors were found to have high relevance(R) and non-majors had high satisfaction(S). Therefore, based on these findings, this study suggests an improvement for effective computational thinking class in liberal arts education.

• Journal of The Korean Association of Information Education
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• v.24 no.6
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• pp.551-562
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• 2020

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.

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.367-375
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• 2021

This study developed and applied an artificial intelligence education program as an educational method for increasing computational thinking of elementary school students and verified its effectiveness. The educational program was designed based on the results of a demand analysis conducted using Google survey of 100 elementary school teachers in advance according to the ADDIE(Analysis-Design-Development-Implementation-Evaluation) model. Among Machine Learning for Kids, we use scratch for block-based programming and develop and apply textbooks to improve computational thinking in the programming process of learning the principles of artificial intelligence and solving problems directly by utilizing numerical data. The degree of change in computational thinking was analyzed through pre- and post-test results using beaver challenge, and the analysis showed that this study had a positive impact on improving computational thinking of elementary school students.

• Journal of Creative Information Culture
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• v.6 no.2
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• pp.77-88
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• 2020

The purpose of this study is to statistically analyze the correlation between CS Unplugged education and the computational thinking of gifted and talented students. In this study, qualitative research was conducted for 17 students in 5th grade gifted class at an elementary school in the city of Yongin. Students participated in 10 hours of CS unplugged classes. Student questionnaire, class journals, student activity sheets, and student interview records were collected and qualitatively analyzed. In order to supplement the qualitative data, computational thinking ability tests were also administered. The results of the study are as follows. First, CS unplugged education plays an effective role in improving CT of gifted and talented students. Second, it was not every sub-area of CT that CS unplugged education brought statistically significant improvements in. Third, CS unplugged education is suitable to be presented as the first step of the SW curriculum for gifted and talented students.

• Journal of The Korean Association of Information Education
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• v.19 no.4
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• pp.385-398
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• 2015

In this study, we presented a App Inventor utilization Software Education program in the process of education for Computational Thinking improvement of elementary school girls. In order to analyze the effects of education programs that have been developed, to elect the 3, 4, 5 grade girls of the sample of volunteers by volunteers form collection as an experimental population, was charged with the development programs, and It was analyzed educational effect using the results of the pre-post tests. The results of the analysis, App Inventor utilization Software Education program that was developed in this study it was found that help in Computational Thinking kidney of elementary school girls.

• Proceedings of The KACE
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• 2018.01a
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• pp.107-110
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• 2018

본 연구에서는 컴퓨팅 사고력 평가도구로써 비버 챌린지 문항을 활용하기 위하여 문항반응이론을 통해 비버 챌린지 문항을 분석하고, 비버 챌린지에서 기존에 제시하는 난이도와 문항반응이론을 통한 난이도 간의 상관관계를 분석하였다. 분석 결과 비버 챌린지는 쉽고 변별력이 높은 검사로 나타났으나, 비버 챌린지에서 제시하는 난이도와 문항반응이론을 통한 난이도 간의 상관관계는 없었다. 난이도에 따라 가점과 감점이 이루어지는 비버 챌린지 채점 기준을 고려할 때 정확한 컴퓨팅 사고력 측정을 위해서는 난이도에 대한 수정 및 보완이 필요하다.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.751-759
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• 2021

This study developed an artificial intelligence education program using localized public data as an educational method for improving computing thinking skills of elementary school students. According to the ADDIE model, the program design was carried out based on the results of pre-requisite analysis for elementary school students, and textbooks and education programs were developed. Based on localized public data, the training program was constructed to learn the principles of artificial intelligence using machine learning for kids and scratches and to solve problems and improve computational thinking through abstracting public data for purpose. It is necessary to put this training program into the field through further research and verify the change in students' computational thinking as a result.

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.327-335
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• 2021

This study verified the effectiveness of machine learning education programs focused on data labeling as an educational method for improving computational thinking of elementary school students. The education program was designed and developed based on the results of a preliminary demand analysis conducted on 100 elementary school teachers. In order to verify the effectiveness of the developed education program, 17 sixth-grade students attending K Elementary School were given 2 classes per day for a total of 6 weeks. In order to measure the effect of the training on improving computational thinking, the educational effects were analyzed by conducting pre-post-inspection using the "Beaver Challenge". According to the analysis, machine learning education focused on data labeling contributed to improving computational thinking of elementary school students.

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.337-346
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• 2021

Despite the increasing rate of use of data science in various fields of society, research on data science education programs is relatively inadequate. In this study, a data science education program for elementary school students was developed and its effectiveness was verified. We created a program that collects data using microbit, one of the physical computing tools, and developed an education program that performs the data science stage of analyzing the collected data to derive results. A study was conducted on 10 students enrolled in the Information Gifted Program at 00 University, and pre- and post-tests of computing thinking skills were conducted to verify the effectiveness. As a result, it was found that the data science education program developed through this study has a significant effect on improving the computational thinking of elementary school students.