Assessing Data Literacy in K--12 Education: Challenges and Opportunities

March 22, 2026 ยท Grace Period ยท ๐Ÿ› the CHI 2026 Workshop on Data Literacy

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Authors Annabel Goldman, Yuan Cui, Matthew Kay arXiv ID 2603.21382 Category cs.HC: Human-Computer Interaction Citations 0 Venue the CHI 2026 Workshop on Data Literacy
Abstract
Data literacy has become a key learning objective in K--12 education, but it remains an ambiguous concept as teachers interpret it differently. When creating assessments, teachers turn broad ideas about "working with data" into concrete decisions about what materials to include. Since working with data visualizations is a core component of data literacy, teachers' decisions about how to include them on assessments offer insight into how they interpret data literacy more broadly. Drawing on interviews with 13 teachers, we identify four challenges in enacting data literacy in assessments: (1) conceptual ambiguity between data visualization and data literacy, (2) tradeoffs between using real-world or synthetic data, (3) difficulty finding and adapting domain-appropriate visual representations and data visualizations, and (4) balancing assessing data literacy and domain-specific learning goals. Drawing on lessons from data visualization, human-computer interaction, and the learning sciences, we discuss opportunities to better support teachers in assessing data literacy.
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