Data-Driven Decision Making (DDDM) and the Optimization of Mathematics Curriculum Planning and Development

This study examined the relationship between data-driven decision making (DDDM) and the optimization of mathematics curriculum planning and development among school leaders and teachers in selected public high schools in the District of Naic, Cavite, Philippines. Using a descriptive correlational research design, the study measured the extent of DDDM through five dimensions – educator data literacy, availability and quality of educational data, decision-making culture, collaborative practices, and alignment with curriculum standards – while assessing curriculum optimization across seven criteria, including curriculum objectives alignment, content coherence, instructional strategies integration, assessment alignment, stakeholder involvement, contextualization, and iterative review. The participants consisted of mathematics teachers and school leaders from five public secondary schools, providing complementary perspectives on administrative and instructional practices. Findings revealed strong integration of data use and collaborative practices in decision making, as well as high levels of curriculum optimization; however, gaps remained in directly linking data analysis to instructional improvement, enhancing data accessibility, engaging stakeholders more meaningfully, and formalizing structured review processes. The study also identified a significant positive relationship between DDDM and mathematics curriculum optimization, suggesting that evidence-based decision making contributes to more effective, responsive, and contextually relevant curriculum practices. Based on these results, professional development initiatives focusing on data literacy were proposed to further enhance the effectiveness of data-informed curriculum planning.