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“Data-driven instruction” is a category of books that helps educators use evidence to inform teaching and improve student outcomes. These titles explain how to collect and interpret multiple data sources—formative and summative assessments, student work, observations, attendance/behavior, and demographic or SEL indicators—and translate findings into actionable plans for differentiation, intervention, and curriculum alignment. Books often present frameworks such as assessment cycles, PLC data teams, RTI/MTSS, and continuous improvement, alongside tools for data literacy, progress monitoring, goal setting, and data visualization or dashboards. Spanning practical guides, research, and case studies for classroom, school, and district contexts (K–12 and higher education), the category also addresses validity, bias, equity, and student privacy to ensure ethical, effective use of data.

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