Implementing Data Science Education in Schools: Opportunities and Challenges

Document Type : Research Paper

Authors

1 Department of Mathematics Education-Faculty of Mathematics and Computer-Shahid Bahonar University of Kerman Mahani Mathematical Research Center-Afzalipour Research Institute- Shahid Bahonar University of Kerman

2 Department of Mathematics Education-Faculty of Mathematics and Computer-Shahid Bahonar University of Kerman

Abstract

The vast volume and storage of data in today’s world have significantly increased public access to data. However, this trend poses challenges, such as the misinterpretation of data, which complicates decision-making in all fields that rely on data. On the other hand, the demand for skilled professionals in this field is exceedingly high. Data scientists and data analysts hold some of the highest-paying jobs globally. Furthermore, students are also part of this society, and their need to analyze data, both as citizens and as the future workforce, is a pressing issue. This need has drawn attention to integrating data science education into schools. The aim of this study is to explore the fundamental challenges of teaching data science in schools, focusing on curriculum design, data utilization, and technology. The definition of data science plays a crucial role in examining these challenges. A key aspect of data science is discovering patterns and generating knowledge using data, which requires proficiency in disciplines such as mathematics, statistics, and computer science. Considering this definition, curriculum changes could particularly target these three subjects: mathematics, statistics, and computer science. Among these, the most significant changes could be implemented in school mathematics.

Keywords

Main Subjects

References

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Mathematics and Society
Volume 10, Issue 3 - Serial Number 3
September 2025
Pages 99-117

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History

  • Receive Date: 16 October 2024
  • Revise Date: 30 December 2024
  • Accept Date: 05 January 2025
  • Publish Date: 09 July 2025

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