Development of Data Literacy as a Component of Digital Competency in the Mathematics Curriculum

Data literacy has become an essential component of mathematics education and digital competence in increasingly data-driven societies. Although previous research has increasingly examined data literacy in mathematics education, relatively little attention has been given to how data literacy competencies are systematically integrated across national mathematics curricula, particularly beyond statistical literacy and within Eastern European contexts. This study examines the integration of data literacy competencies within the Latvian mathematics curriculum for basic education (Grades 1–9). Using Schüller’s data literacy framework, the research applies deductive qualitative content analysis to investigate curriculum progression across six dimensions of data literacy: establishing data culture, providing data, evaluating data, interpreting results, interpreting data, and deriving actions. Curriculum elements were coded using a three-point integration scale and transformed into quantitative indicators. The findings reveal a systematic progression of data literacy competencies from foundational representational skills in Grade 3 to advanced analytical and interpretative competencies in Grade 9. Data visualization achieved the highest cumulative integration score (6), whereas data protection and security received no explicit curriculum representation (0). Source evaluation and societal impact received comparatively less curriculum attention than data analysis, visualization, and interpretation. The study contributes to curriculum research by demonstrating that the Latvian mathematics curriculum predominantly develops statistical literacy while giving comparatively limited attention to critical data literacy. These findings provide a framework for evaluating curriculum-level data literacy integration and support the inclusion of ethical, critical, and socio-digital dimensions in mathematics education.