DataScEd4CiEn: Integrating data science into STEAM education for civic engagement and social justice – A case from Greece
DOI:
https://doi.org/10.52041/iase25.132Abstract
This paper explores the implementation of a data science activity within a STEAM scenario on food waste and sustainability, carried out in a Greek lower secondary school as part of the Erasmus+ project DataScEd4CiEn. The Greek case offers a unique lens due to the traditionally formal and discipline- bound structure of the national curriculum, where data literacy and interdisciplinary approaches are still emerging and not yet systematically embedded. Through an iterative design process, students engaged with real-world datasets to explore social issues and propose civic actions. The findings reveal both the emergence of key data science practices as well as the challenges involved in supporting open- ended inquiry and integrating data insights into civic messaging. The paper also highlights broader pedagogical tensions in teaching data science in schools and emphasizes the strong potential of STEAM scenarios to promote social engagement through data-driven inquiry.References
Bargagliotti, A., Franklin, C., Arnold, P., Gould, R., Johnson, S., Perez, L., & Spangler, D. (2020). Pre-K-12 Guidelines for Assessment and Instruction in Statistics Education (GAISE) report II. American Statistical Association and National Council of Teachers of Mathematics.
Burrill, G., & Pfannkuch, M. (2023). Emerging trends in statistics education. ZDM – Mathematics Education, 56, 19–29. https://doi.org/10.1007/s11858-023-01501-7.
Cobb, P., Confrey, J., Lehrer, R., & Schauble, L. (2003). Design experiments in educational research. Educational Researcher, 32(1), 9–13. https://doi.org/10.3102/0013189X032001009.
Engel J. (2017). Statistical literacy for active citizenship: A call for data science education. Statistics Education Research Journal, 16(1), 44–49. https://doi.org/10.52041/serj.v16i1.213.
Friedrich, A., Schreiter, S., Vogel, M., Becker-Genschow, S., Brünken, R., Kuhn, J., Lehmann, J., & Malone, S. (2024). What shapes statistical and data literacy research in K-12 STEM education? A systematic review of metrics and instructional strategies. International Journal of STEM Education,11(1). https://doi.org/10.1186/s40594-024-00517-z.
Gould, R. (2017). Data literacy is statistical literacy. Statistics Education Research Journal, 16(1), 22- 25. https://doi.org/10.52041/serj.v16i1.209.
Kahne, J., & Bowyer, B. (2017). Educating for Democracy in a Partisan Age: Confronting the Challenges of Motivated Reasoning and Misinformation. American Educational Research Journal, 54(1), 3-34. https://doi.org/10.3102/0002831216679817.
Kazak, S., Leavy, A., & Podworny, S. (2025). Framework for developing data science education modules for teacher education in STEAM subjects [Poster presentation]. Presented at the 14th Congress of the European Society for Research in Mathematics Education (CERME14), Bolzano, Italy.
Liston, M., Morrin, A. M., Furlong, T., & Griffin, L. (2022). Integrating data science and the internet of things into science, technology, engineering, arts, and mathematics education through the use of new and emerging technologies. In Frontiers in Education, 7(757866). https://doi.org/10.3389/feduc.2022.757866.
Makar, K., Fry, K., & English, L. (2023). Primary students’ learning about citizenship through data science. ZDM – Mathematics Education, 55, 967–979. https://doi.org/10.1007/s11858-022-01450- 7.
Meletiou-Mavrotheris, M., Serradó Bayés, A., Leavy, A., Frischemeier, D., Bakogianni, D., & Paparistodemou, E. (2025). Navigating subjectivities and perspectives in data science education: A Toulminian analysis of two STEAM scenarios from the European project DataScEd4CiEn. To be presented at the 14th International Forum for Statistical Reasoning, Thinking and Literacy (SRTL-14), Penn State University, USA.
Noll, J., Schnell, S., Gould, R., & Makar, K. (2022). New ways of interacting with data, context, and chance in statistical modeling processes. Mathematical Thinking and Learning, 24(4), 331-335. https://doi.org/10.1080/10986065.2021.1922855.
Ridgway, J. (Ed.). (2022). Statistics for empowerment and social engagement: Teaching Civic Statistics to develop informed citizens. Springer. https://doi.org/10.1007/978-3-031-20748-8.
Schreiter, S., Friedrich, A., Fuhr, H., Malone, S., Brünken, R., Kuhn, J., & Vogel, M. (2024).Teaching for statistical and data literacy in K-12 STEM education: a systematic review on teacher variables, teacher education, and impacts on classroom practice. ZDM – Mathematics Education, 56(1), 31- 45. https://doi.org/10.1007/s11858-023-01531-1.
Yin, R. K. (2009). Case study research: Design and methods (4th ed.). Sage Pu
Zieffler, A., Garfield, J., delMas, R., & Reading, C. (2008). A framework to support research on informal inferential reasoning. Statistics Education Research Journal, 7(2), 40–58. https://doi.org/10.52041/serj.v7i2.469.
Zucker, A., Noyce, P., & McCullough, A. (2020). JUST SAY NO! Teaching students to resist scientific misinformation. The Science Teacher, 87(5), 24-29. https://doi.org/10.2505/4/tst20_087_05_24.
