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Development and Application of Statistical Programs Based on Data and Artificial Intelligence Prediction Model to Improve Statistical Literacy of Elementary School Students

초등학생의 통계적 소양 신장을 위한 데이터와 인공지능 예측모델 기반의 통계프로그램 개발 및 적용

  • Received : 2023.11.16
  • Accepted : 2023.12.26
  • Published : 2023.12.31

Abstract

The purpose of this study is to develop a statistical program using data and artificial intelligence prediction models and apply it to one class in the sixth grade of elementary school to see if it is effective in improving students' statistical literacy. Based on the analysis of problems in today's elementary school statistical education, a total of 15 sessions of the program was developed to encourage elementary students to experience the entire process of statistical problem solving and to make correct predictions by incorporating data, the core in the era of the Fourth Industrial Revolution into AI education. The biggest features of this program are the recognition of the importance of data, which are the key elements of artificial intelligence education, and the collection and analysis activities that take into account context using real-life data provided by public data platforms. In addition, since it consists of activities to predict the future based on data by using engineering tools such as entry and easy statistics, and creating an artificial intelligence prediction model, it is composed of a program focused on the ability to develop communication skills, information processing capabilities, and critical thinking skills. As a result of applying this program, not only did the program positively affect the statistical literacy of elementary school students, but we also observed students' interest, critical inquiry, and mathematical communication in the entire process of statistical problem solving.

본 연구는 데이터와 인공지능 예측모델을 활용한 통계프로그램을 개발하여 초등학교 6학년 한 학급에 적용함으로써 학생들의 통계적 소양 신장에 효과가 있는지 확인하는 것을 목적으로 한다. 오늘날 초등학교 통계교육의 문제점을 분석하고, 4차 산업혁명 시대에서 중시되는 데이터와 인공지능 교육을 융합하여 통계적 문제해결의 전 과정을 경험하고 미래에 대한 올바른 예측을 경험해 볼 수 있는 총 15차시의 통계프로그램을 개발하였다. 본 프로그램의 가장 큰 특징은 인공지능 교육의 중점 요소인 데이터의 중요성 인식, 공공데이터플랫폼에서 제공하는 실생활 데이터를 사용하여 맥락을 고려한 자료 수집 및 분석 활동을 포함한다는 것이다. 또한 공학 도구인 엔트리와 이지통계를 활용하고, 인공지능 예측모델을 제작하여 데이터를 기반으로 미래를 예측해 보는 활동으로 구성된다는 점에서 의사소통역량, 정보처리역량, 비판적 사고 역량을 기를 수 있는 역량 중심의 프로그램으로 구성하였다. 본 프로그램의 적용 결과, 프로그램 적용은 초등학생의 통계적 소양에 긍정적 영향을 미쳤을 뿐만 아니라 학생들의 흥미, 주체적이고 비판적 탐구, 통계적 문제해결 전 과정에서의 수학적 의사소통을 관찰할 수 있었다.

Keywords

References

  1. Ministry of Education (2022a). General curriculum, Book 1. Ministry of Education. 
  2. Ministry of Education (2022b). Mathematics curriculum, Book 8. Ministry of Education. 
  3. Ministry of Education, Kofac (2021). Artificial intelligence classes at school. Gyeongseong Munhwasa. 
  4. Kim, K. (2017). A study on collaborative learning methods for the cultivation of statistical thinking in elementary mathematics [Master's thesis, Korea National University of Education]. 
  5. Kim, D., Hong, J., Kim, S., Shin B., Kim Y., Park J., Tak, B., Hwang, J., Wang, H., Song, C. (2020) Analysis of the field conditions of the 2015 revised mathematics curriculum. Research report BD21010009. KOFAC. 
  6. Kim, S., & Cho, M. (2022). AI-based educational platform analysis supporting personalized mathematics learning. Communications of Mathematical Education, 36(3). 417-438.  https://doi.org/10.7468/JKSMEE.2022.36.3.417
  7. Kim, S., Jeon, Y., Lee, H., Kim, Y., Kim, T. (2021). A proposal of data set analysis and application for AI education in primary and secondary school. The Journal of Korean Association of Computer Education, Communication of Academic Presentation Competition, 25(1), 55-58. 
  8. Kim, H. (2023). An instructional model for data-driven problem solving in elementary school mathematics [Master's thesis, Seoul National University of Education]. 
  9. Noh, J. (2022) Analysis on statistical literacy of elementary mathematics gifted students by development and application of gifted education program based on statistical problem solving process [Master's thesis, Seoul National University of Education]. 
  10. Park, M., & Jeon, I. (2020). Comparative analysis of information processing competency in elementary mathematics textbooks according to the 2009 and 2015 revised curriculum: Focused on statistics. Journal of Elementary Mathematics Education in Korea, 24(4), 343-369 
  11. Bae, H., & Lee, D. (2016). An analysis on statistical units of elementary school mathematics textbook. Journal of Elementary Mathematics Education in Korea., 20(1), 55-69 
  12. Oh, Y., & Lee, Y. (2022). Analysis of data-related error perception cases of elementary school students for data-driven statistical education. Korean Journal of Elementary Education, 33(4), 91-108 
  13. Lee, D. (2021). Elementary school students' mathematical thinking types and mathematics learning styles Study of relationships between levels of statistical thinking [Doctoral dissertation, Seoul National University of Education]. 
  14. Lee, K. H. et al. (2022). A study on the development of the 2022 revised mathematics curriculum. Ministry of Education. 
  15. Lee, K., Yoo, Y., & Tak, B. (2021). Towards data-driven statistics education: An exploration of restructuring the mathematics curriculum. Journal of Korea Society Educational Studies in Mathematics, 23(3), 361-386 
  16. Lee, H. (2019) The effects of multidisciplinary statistics education on statistical thinking and mathematics learning attitude - Focused on practical arts curriculum in 5th grade. [Master's thesis, Seoul National University of Education]. 
  17. Im, D., & Park, Y. (2017). A Study on School Statistics and Statistical Literacy of 6th Graders in the Elementary School. Journal of Elementary Mathematics Education in Korea, 21(2), 391-414. 
  18. Song, H. (2023). An analysis of the statistical inquiry tasks in elementary school mathematics textbooks: Focused on the context of the task and the statistical problem solving process [Master's thesis, Seoul National University of Education]. 
  19. Jung, S., & Cho, M. (2019). An analysis on statistical literacy of mathematically gifted students using real-life tasks Journal of Learner-Centered Curriculum and Instruction, 19(23), 921-943. 
  20. Choi, S., & Lee, D. (2012). Acomparion analysis of the statistical sections between in the Korean elementary mathematics textbooks and the MiC textbooks. Education of Primary School Mathematics, 15(1), 41-52.  https://doi.org/10.7468/JKSMEC.2012.15.1.041
  21. Choi, I. (2022). Exploring teaching and learning methods using artificial intelligence (AI) in the mathematics classroom : Focusing on the development of middle school statistic scenarios. Journal of the Korean School Mathematics Society, 25(2), 149-174  https://doi.org/10.30807/ksms.2022.25.2.003
  22. Tak, B., & Lee, K. (2016). Current status of statistics education research in Korea Trend Analysis. Proceedings of the 2016 International Conference of the Korean Society of Mathematics Education (pp. 119).
  23. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. The Center for Curriculum Redesign.
  24. Franklin, C. A., Kader, G. D., Mewborn, D., Moreno, J., Peck, R., Perry, M., & Scheaffer, R. (2007). Guidelines for assessment and instruction in statistics education report. American Statistical Association.
  25. Gal, I. (2002). Adults' statistical literacy: meanings, components, responsibilities. International Statistical Review, 70(1), 1-51.
  26. Rumsey. D. J. (2002). Statistical literacy as a goal for introductory statistics courses. Journal of Statistics Education. 10(3), jse.amstat.org/v10n3/rumsey2.html.
  27. Wallman, K. K. (1993). Enhancing statistical literacy: Enriching our society. Journal of the American Statistical Association, 88, 1-8. https://doi.org/10.1080/01621459.1993.10594283
  28. Watson, J. M. (1997). Assessing statistical thinking using the media. In I. Gal & J. Garfield (Eds.). The assessment challenge in statistics education. (pp. 107-121). IOS Press.
  29. Watson, J. M. (2006). Statistical literacy at school: Growth and goals. London: Routledge. 박영희 역(2013). 학교에서 어떤 통계를 배워야 하지? 통계적 소양의 성장과 목표. 경문사.