• Title/Summary/Keyword: 파이선코딩

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A Study on Development of Integrating Mathematics and Coding Teaching & Learning Materials Using Python for Prime Factorization in 7th Grade (파이썬을 활용한 중학교 1학년 소인수분해의 수학과 코딩 융합 교수·학습 자료 개발 연구)

  • Kim, Ye Mi;Ko, Ho Kyoung;Huh, Nan
    • Communications of Mathematical Education
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    • v.34 no.4
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    • pp.563-585
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    • 2020
  • This study developed teaching-learning materials for mathematics and coding convergence classes using Python, focusing on 'Prime Factorization' of seventh graders. After applying the teaching methods and contents to the students, they analyzed whether the learners achieved their learning goals. The results were used to modify and supplement teaching and learning materials. Affective domain of learners were also analyzed. The results are that the teaching methods and contents of the developed teaching-learning materials were generally appropriate for learners. The learners understood most of the lessons according to the set teaching methods of all classes. And learners have mostly reached their learning goals. In addition, as a result of analyzing the definition characteristics of learners through follow-up interviews, the interest in mathematics and programming has improved. The developed teaching and learning materials of this study are well consisted mostly of the teaching methods and the contents of the classes, and are organized so that learners can reach most of the learning goals. It also brought positive changes to the affective domain of mathematics and coding, demonstrating the potential for useful use in school.

Welfare Policy Visualization Analysis using Big Data -Chungcheong- (빅데이터를 활용한 복지정책 시각화분석 -충청도 중심으로-)

  • Dae-Yu Kim;Won-Shik Na
    • Advanced Industrial SCIence
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    • v.2 no.1
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    • pp.15-20
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    • 2023
  • The purpose of this study is to analyze the changes and importance of welfare policies in Chungcheong Province using big data analysis technology in the era of the Fourth Industrial Revolution, and to propose stable welfare policies for all generations, including the socially underprivileged. Chungcheong-do policy-related big data is coded in Python, and stable government policies are proposed based on the results of visualization analysis. As a result of the study, the keywords of Chungcheong-do government policy were confirmed in the order of region, society, government and support, education, and women, and welfare policy should be strengthened with a focus on improving local health policy and social welfare. For future research direction, it will be necessary to compare overseas cases and make policy proposals on the stable impact of national welfare policies.