Integrating Data Science Foundations into the US Algebra II Curriculum: A Review of Pedagogical Frameworks

As the need for data-rich industries continues to grow and the nation has more citizens who require quantitative literacy, the demand for secondary mathematics to go beyond procedural learning has been increasing in the United States. Algebra II is an important gateway course that connects basic algebra with precalculus, is an under-used opportunity to integrate data science skills into the architecture of algebra and is a place of significant opportunity within the K–12 continuum. This narrative review aims to consolidate recent peer-reviewed scholarship (2020–present) to explore the potential for sensibly embedding data science foundations including statistical reasoning, data visualization, exploratory data analysis and computational thinking in the US Algebra II curriculum using evidence-informed pedagogical approaches. This review first maps the pedagogical landscape by interpreting the existing literature on mathematics education, educational technology, equity research, and instructional design through an expert-driven interpretive synthesis and then identifies pedagogical actionable insights. The review brings to light five interrelated themes: transition to a data-focused approach to algebra instruction, using computational thinking to expand access to data literacy, embedded systemic inequities as a result of unequal technology distribution, assessment reform as a leverage point for challenges, and the importance of teacher readiness as a support for fidelity in implementing. There is a conflict between breadth demands of a compressed curriculum and depth needed for authentic data inquiries. Research also suggests that if no effort is made to achieve this equitable scaffolding, integration can widen inequities. Data science can have great promise for improving mathematical literacy in the 21st century when integrated into Algebra II. It is, however, necessary to align policies, provide in-depth professional development for teachers, make digital infrastructure accessible and redesign assessment systems to make them successful. More research is needed to understand how specific pedagogies relate to measurable student learning, especially among historically marginalized student groups.