Teaching and Teacher Educating Data Literacy in K-12 STEM Education: Looking Back, Moving Forward

The growing centrality of data in contemporary society has intensified calls to expand data literacy across K–12 education, positioning teachers as key agents in this effort. This article traces the emergence of data literacy as a domain of educational research and reports findings from a systematic review of empirical studies on K–12 STEM teacher data literacy published between 2015 and 2025. Guided by the PRISMA framework, searches of Academic Search Complete, APA PsycINFO, and supplementary sources yielded a final sample of 26 studies. The review examines (1) what has been prioritized in research on teaching data literacy and (2) the conceptual models used to study data literacy in educational contexts. Findings indicate that existing research primarily emphasizes teachers’ knowledge, beliefs, and use of technological tools, with comparatively limited attention to classroom enactment and student learning. Conceptually, the field is characterized by the use of diverse and often disconnected frameworks, including competency-based, statistical reasoning, and pedagogical models, resulting in a fragmented knowledge base. We argue that this fragmentation stems from underlying epistemological, methodological, and contextual tensions that have yet to be theoretically reconciled. In response, we propose an integrative perspective that conceptualizes data literacy as a situated, practice-based, and socio-epistemic phenomenon. This framing highlights the dynamic interplay among interpretive reasoning, instructional design, mediational tools, and contextual conditions. Advancing the field requires moving beyond isolated lines of inquiry toward theoretically coherent approaches that connect teacher cognition, instructional practice, and student learning in order to support meaningful and equitable participation in a data-driven world.