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Contextualising Data Literacy for the 21st-Century Science Education

Ngbarabara, Prince Boniface, Ph.D

Abstract

Data literacy has become a vital competence in contemporary Science Education, reflecting the growing dominance of data in scientific investigation, evidence-based decision-making, and civic engagements. This paper examined data literacy within the context of Science Education, presenting it not as a subsidiary of digital or statistical literacy but as a core scientific skill in its own right. Drawing from existing literature, the paper explored the core components of data literacy, which include: data exploration, management, usage, and reflective evaluation for continuous improvement and further positioned them within the framework of scientific inquiry processes. Furthermore, the paper examined the cognitive foundations of data literacy through the lens of the 5C framework: curiosity, critical thinking, communication, collaboration, and creativity. These competencies are presented as enabling conditions for deep, responsible, and contextually meaningful engagement with data. The educational benefits of data literacy for learners, teachers, and society are also established, including enhanced scientific reasoning, informed decision-making, STEM workforce preparedness, and responsible citizenship. In like manner, the paper cross-examined key challenges to the development of data literacy in Science Education, with particular attention to infrastructural, pedagogical, curricular, and contextual constraints in developing countries such as Nigeria. Finally, policy-oriented and pedagogical strategies were proposed to strengthen data literacy through curriculum reform, teacher professional development, innovative instructional practices, and context-sensitive implementation. It contributed practical direction for advancing data literacy as a transformative element of Science Education.

Keywords

Data LiteracyScience EducationScientific inquiryDevelopmentTeacher Professional Developmentand Curriculum Reform.

References

Bybee, R. W. (2015). The BSCS 5E instructional model: Creating teachable moments. National Science Teaching Association Press. Cultivating Visualization Literacy for Children Through Curiosity and Play. (2023). IEEE Transactions on Visualization and Computer Graphics, 29(1), 257–267. https://doi.org/10.1109/tvcg.2022.3209442 D’Ignazio, C. (2017). Creative data literacy: Bridging the gap between the data-haves and data- have nots. Information Design Journal, 23(1), 6–18. https://doi.org/10.1075/IDJ .23.1.03DIG Darling-Hammond, L., Hyler, M. E., & Gardner, M. (2017). Effective teacher professional development. Learning Policy Institute. https://learningpolicyinstitute.org/product/ effective-teacher-professional-development-report Gal, I. (2002). Adults’ statistical literacy: Meanings, components, responsibilities. International Statistical Review, 70(1), 1–25. https://doi.org/10.1111/j.1751-5823.2002.tb00336.x Mandinach, E. B., & Gummer, E. S. (2016). What does it mean for teachers to be data literate? Teachers College Record, 118(4), 1–42. Munasinghe, T., & Svirsky, A. (2021). Engaging Students in Data Literacy: Lessons Learned from Data Intensive Classrooms. Web Science, 40–43. https://doi.org/10.1145/3462 741.3466665 Ngbarabara, P. B. (2026). Data Literacy in Science Education. Science Education Handbook on SED 101. Department of Science Education, Federal University Otuoke, Bayelsa State, Nigeria. OECD. (2019). Future of education and skills 2030: OECD learning compass 2030. OECD Publishing. https://www.oecd.org/education/2030-project/ Ologbosere, O. A. (2025). Data literacy and higher education in the 21st century. IASSIST Quarterly. https://doi.org/10.29173/iq1082 Pedersen, A. Y., & Caviglia, F. (2018). Data Literacy as a Compound Competence (pp. 166–173). Springer, Cham. https://doi.org/10.1007/978-3-030-02351-5_21 Qiao, C., Chen, Y., Guo, Q., & Yu, Y. (2024). Understanding science data literacy: A conceptual framework and assessment tool for college students majoring in STEM. International Journal of STEM Education, 11(25). https://doi.org/10.1186/s40594-024-00484-5 Schumacher, C., & Ifenthaler, D. (Eds.). (2026). International perspectives on educational data literacy: Frameworks, contexts, and practices. Routledge. Smit, M., Ridsdale, C., & Colborne, A. (2018). Proficient Use of Open Data Requires These Core Information Skills: An Open Data Community Perspective. https://doi.org/10.29173/CAIS990 Texas Education Agency. (2024). Data literacy in STEM: Data as the foundation of scientific inquiry. TEA Data Literacy Toolkit. UNESCO. (2018). A global framework of reference on digital literacy skills for indicator 4.4.2. UNESCO Institute for Statistics. https://uis.unesco.org

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