Designing Data Science Learning in Initial Teacher Education: The EDUCATE Conceptual Framework

Data science has become central to contemporary social, civic, and professional life, yet its integration into initial teacher education remains fragmented and undertheorised. This paper addresses the need to support teacher educators in designing learning experiences that develop pre-service teachers, who are non-data science specialists, competence in data science. A systematic scoping review of the literature was conducted across major academic databases and complemented by an expert-informed literature identification strategy. The review examined how data science is described conceptually, how it is structured within school curricula and teacher education, and what knowledge and practices are emphasised for teachers. Findings indicate that while core processes and practices of data science, such as problem formulation, data preparation, exploratory analysis, modelling, visualisation, and ethical engagement, are widely recognised, their translation into teacher education is inconsistent and often lacks coherence. In response, the paper presents a conceptual framework designed to support pre-service teachers in engaging with the processes and practices of doing data science. The framework offers a flexible, practice-informed structure that is accessible to non-specialist teachers and aligned with pedagogical decision-making in educational settings. The paper concludes by discussing how the framework, alongside practical considerations for enactment, can support the preparation of data-literate teachers capable of fostering critical, ethical, and inquiry-based engagements with data in schools.