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

TL;DR

This paper explores how K-12 teachers interpret and assess data literacy, highlighting challenges in assessment design and proposing opportunities for better support based on interdisciplinary insights.

Contribution

It identifies key challenges teachers face in assessing data literacy and offers insights to improve assessment practices through interdisciplinary approaches.

Findings

Four main challenges in assessing data literacy identified

Teachers struggle with conceptual ambiguity and resource limitations

Opportunities for supporting teachers in assessment design discussed

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.