Towards a Multidimensional Framework for Educational Data Literacy

Educational data literacy (EDL) has become a central concern for European schools as digitalization generates unprecedented volumes of sensitive data on minors, while the GDPR and AI Act impose constitutive constraints on data use. The conceptual landscape, however, remains fragmented: several traditions have proposed competency models, but each foregrounds one dimension while leaving others aside, and the boundary between EDL and adjacent constructs such as assessment literacy is still unresolved. This paper compares the four most influential traditions in the English-language literature: the Data Literacy for Teaching model, the Dutch Data-Based Decision Making tradition, the Learn2Analyze Educational Data Literacy Competence Profile, and the Critical Educational Data Literacy perspective. The comparison uses two axes: a dimensional axis of five facets (Technical, Pedagogical, Organizational, Ethical, Transversal) and a role axis distinguishing teachers from school leaders. The analytical method is a conceptual framework analysis rather than a systematic review, complementing recent empirical syntheses by asking whether the architectures organizing the field are adequate. The findings show that no tradition covers all five dimensions strongly, that role differentiation between teachers and school leaders is systematically lacking, that the organizational dimension is the most neglected, and that teachers’ actual data use remains narrower than definitions suggest, with assessment data still dominating practice. From these findings, four design requirements for an integrated framework follow: multidimensional coverage with explicit interdependencies; role differentiation within a unified architecture; contextual adaptability through modular proficiency levels; and governance as institutional infrastructure. The discussion grounds these requirements in the DIKW hierarchy, aligns them with European regulatory and data sovereignty requirements, and draws implications for teacher education, school leadership development, and European policy on professional data competence, translating analytical findings into actionable design parameters.