Our newly published paper in Education Sciences explores how students develop “critical data literacy” — the ability to work with data not just technically, but ethically and thoughtfully — through a summer-long data science program.
The study compared what students learned in a traditional classroom setting with how they applied those skills in a real-world project focused on food justice. In class, students were introduced to basic data tools and abstract concepts. But it was in the hands-on project work where they really began to connect data science with broader social issues. By analyzing real data and thinking through the ethical implications of their work, students gained a deeper and more practical understanding of data science.
This work suggests that to truly teach data literacy, educators need to go beyond lectures and worksheets. Real-world projects—especially those grounded in issues students care about—can help bridge the gap between theory and practice, preparing students to tackle meaningful problems with data.
Citation: Sager, M. T., Wieselmann, J. R., & Petrosino, A. J. (2025). From Classroom to Community: Evaluating Data Science Practices in Education and Social Justice Projects. Education Sciences,15(7),878. https://doi.org/ 10.3390/educsci15070878
From Classroom to Community: Evaluating Data Science Practices in Education and Social Justice Projects by Tony Petrosino on Scribd
