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Pedagogy Review: An International Journal of Educational Theories, Approaches and Strategies
Volume 6 | Issue 1 | 2025 | 1 – 20
1Doctor of Education major in Educational Administration, Greenville College, Manggahan, Pasig City, Philippines
2Research Adviser, Greenville College, Pasig Greenpark Village, Manggahan, Pasig City, Philippines
Article History:
Initial submission: 28 July 2025
First decision: 30 July 2025
Revision received: 30 August 2025
Accepted for publication: 15 September 2025
Online release: 19 September 2025
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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.
Keywords: data-driven decision making, curriculum optimization, mathematics education, educational leadership, professional development, public high schools, evidence-based practice
APA (7th edition)
Ortiz, O. E., Jr., & Sta. Ana, M. C. (2025). Data-driven decision making (DDDM) and the optimization of mathematics curriculum planning and development. Pedagogy Review: An International Journal of Educational Theories, Approaches and Strategies, 6(1), 1–20. https://doi.org/10.62718/vmca.pr-ijetas.6.1.SC-0825-007.
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This research received no external funding.
The authors declare no conflict of interest.
This study involved human respondents; however, formal ethical approval was not sought from the authors’ institution. The authors affirm that participation was voluntary, informed consent was obtained, and confidentiality of responses was strictly maintained. No procedures were undertaken that posed risk or harm to the participants.
All data supporting the findings of this study are included within the manuscript and its supplementary materials.
AI-assisted language editing was performed; authors reviewed and approved all content.
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The views expressed in this article are those of the authors and do not necessarily reflect the views of the publisher. The publisher disclaims any responsibility for errors or omissions.