This review highlights how data-driven decision making improves curriculum design, suggesting tools like learning analytics and frameworks such as Outcome-Based Education.
This paper reviews the growing role of data-driven decision making (DDDM) inmodern curriculum design. It explores how educational data—such as academic performance,attendance records, engagement metrics, and feedback—can be effectively used to improveteaching and learning outcomes. The study discusses various tools and techniques, includingmachine learning models, data visualization platforms, and learning analytics, that helpeducators make informed curricular decisions. It also highlights key frameworks such asOutcome-Based Education (OBE) and Bloom's Taxonomy, emphasizing the importance of ethicaldata use, privacy, and institutional readiness. The paper concludes by identifying future researchopportunities in AI-assisted curriculum co-design and adaptive learning systems.
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Kirange et al. (2025) studied this question.
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