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2022 개정 교육과정 성취기준에 포함된 데이터 리터러시 요소 분석

Analysis of Elements Related to Data Literacy Presented in Achievement Standards of 2022Revised National Curriculum

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초록

With the drastic increase in the amount and types of data due to advancements in information and communication technology, the significance of data literacy has become more prominent. This study examined the elements of data literacy included in the achievement standards of the revised 2022 national curriculum, investigating how data literacy elements are reflected across various subjects such as Korean literature, mathematics, social studies, science, and practical arts. Analyzing 600 achievement standards related to data literacy, the study found that data interpretation and data-based inquiry were the main elements identified, with the application of data varying across subjects. The Korean literature focused on data communication, while mathematics stressed statistical problem-solving. An increasing trend in the ratio of data interpretation and databased inquiry was observed with higher grade levels, although it was challenging to clearly discern the learning hierarchy of data literacy elements. Through this analysis, the study suggests the necessity of systematic guidance on data literacy education in the curriculum and a deeper understanding of how data literacy elements vary by subject. This research provides foundational data on integrating data literacy into the curriculum and offers insights into how students can be supported in developing the ability to extract information from data and utilize it to solve problems.

Abstract

With the drastic increase in the amount and types of data due to advancements in information and communication technology, the significance of data literacy has become more prominent. This study examined the elements of data literacy included in the achievement standards of the revised 2022 national curriculum, investigating how data literacy elements are reflected across various subjects such as Korean literature, mathematics, social studies, science, and practical arts. Analyzing 600 achievement standards related to data literacy, the study found that data interpretation and data-based inquiry were the main elements identified, with the application of data varying across subjects. The Korean literature focused on data communication, while mathematics stressed statistical problem-solving. An increasing trend in the ratio of data interpretation and databased inquiry was observed with higher grade levels, although it was challenging to clearly discern the learning hierarchy of data literacy elements. Through this analysis, the study suggests the necessity of systematic guidance on data literacy education in the curriculum and a deeper understanding of how data literacy elements vary by subject. This research provides foundational data on integrating data literacy into the curriculum and offers insights into how students can be supported in developing the ability to extract information from data and utilize it to solve problems.

참고문헌 (31)

  1. Bae, H., "Educational implications of data literacy in social studies", Theory and Research in Citizenship Education, 51, pp.95~120 (2019)
  2. Pre-K-12Guidelines for Assessment and Instruction in Statistics Education II (GAISE II) Report, "Bargagliotti, A.", American Statistical Association and National Council of Teachers of Mathematics, ~ (2020)
  3. "Beyond Data Literacy: Reinventing Community Engagement and Empowerment in the Age of Data" (2015)[URL]
  4. Bybee, R. W., "NGSS and the next generation of science teachers", Journal of Science Teacher Education, 25, pp.211~221 (2014)
  5. Condon, P., "Data literacy in the social sciences : Findings from a local study on teaching with quantitative data in undergraduate courses", Evidence Based Library and Information Practice, 18, pp.61~75 (2023)
  6. Do, J. M., "Comparative analysis on the elementary mathematics curriculum standards and textbook problems from the perspective of data literacy and ill-structured : Focusing on Korea, the United States, Japan, and India", Korean Association For Learner-Centered Curriculum And Instruction, 23, pp.209~229 (2023)
  7. Erwin, R., "Data literacy : Real-world learning through problem-solving with data sets", American Secondary Education, 43, pp.18~26 (2015)
  8. "A conceptual framework for data-driven decision making" (2014)[URL]
  9. Grossman, J., "Political science and big data : structured data, unstructured data, and how to use them", Political Science Quarterly, 135, pp.225~257 (2020)
  10. Hong, J., "Development of AI data science education program to foster data literacy of elementary school students", Journal of The Korean Association of Information Education, 24, pp.633~641 (2020)
  11. "Big Data Revolution and Media Policy Issue. KISDI Premium Report, 26" (2012)[URL]
  12. Kim, D., "Data science for smart manufacturing : Techniques, applications, and issues", Industrial Engineering Magazine, 23, pp.20~30 (2016)
  13. Kim, S., "A study of the definition and components of data literacy for K-12 AI education", Journal of The Korean Association of Information Education, 25, pp.691~704 (2021)
  14. Kjelvik, M. K., "Getting messy with authentic data: Exploring the potential of using data from scientific research to support student data literacy", CBE—Life Sciences Education, 18, pp.es2~ (2019)
  15. Lee, J., "A study for cultivating data literacy in the social studies education-Focusing on the analysis of the data visualization contents of the social studies textbook in the 2015 curriculum", Teacher Education Research, 58, pp.501~512 (2019)
  16. Lee, J., "Re-approach to the concept of data literacy and its application to library information services", Korean Society for Library and Information Science, 53, pp.159~179 (2019)
  17. Mandinach, E. B., "A Theoretical Framework for Data-Driven Decision Making", Annual Meeting of the American Educational Research Association (2006)
  18. Ministry of Education, "2022 Revised Elementary School National Curriculum. The Notification of MOE 2022-33: The Separate Volume No.1", Ministry of Education, ~ (2022)
  19. Ministry of Education, "Moral Education Curriculum. The Notification of MOE 2022-33: The Separate Volume No.6", Ministry of Education, ~ (2022)
  20. Ministry of Education, "Social Studies Curriculum. The Notification of MOE 2022-34: The Separate Volume No.7", Ministry of Education, ~ (2022)
  21. Ministry of Education, "Science Curriculum. The Notification of MOE 2022-36: The Separate Volume No.9", Ministry of Education, ~ (2022)
  22. NGSS Lead States, "Next Generation Science Standards: For States, by States" (2013), The National Academy Press
  23. "OECD Learning Compass 2030: A Series of Concept Notes" (2023)[URL]
  24. Strategies and Best Practices for Data Literacy Education: Knowledge Synthesis Report, "Ridsdale, C.", Dalhousie University, ~ (2015)
  25. Seo, J., "A case study on the teaching and learning method of sw education for data analysis problem solving", Journal of Digital Contents Society, 20, pp.1953~1960 (2019)
  26. Song, Y., "A developmental study of an instructional model and strategies for data-driven debate(DDD)to improve data literacy", Journal of Educational Technology, 37, pp.943~982 (2021)
  27. Stephenson, E., "Incorporating data literacy into undergraduate information literacy programs in the social sciences : A pilot project", Reference Services Review, 35, pp.525~540 (2007)
  28. Swan, K., "Challenges to Cross-Disciplinary Curricula: Data Literacy and Divergent Disciplinary Perspectives", Annual Conference of the American Educational Research Association (2009)
  29. Van Borkulo, S. P., "Spreadsheets in secondary school statistics education : Using authentic data for computational thinking", Digital Experiences in Mathematics Education, 9, pp.420~443 (2023)
  30. Wolff, A., "Creating an understanding of data literacy for a data-driven society", The Journal of Community Informatics, 12, pp.9~26 (2016)
  31. Wollschleger, J., "Making it count : Using real-world projects for course assignments", Teaching Sociology, 47, pp.314~324 (2019)

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