Which kind of data analysis promotes informed decision-making in school improvement strategies?

Data-driven decision-making is a systematic approach that emphasizes the importance of using relevant and accurate data to guide decisions in educational settings. This method empowers school leaders and educators to assess student performance, track progress, and identify areas needing improvement. By relying on data, schools can make informed choices that are based on evidence rather than assumptions or anecdotal observations.

When schools engage in data-driven decision-making, they utilize various types of data, such as academic performance metrics, attendance records, and student feedback, to inform strategic planning and interventions. This process helps in setting measurable goals, evaluating program effectiveness, and allocating resources efficiently to enhance student outcomes. It encourages a culture of accountability and ongoing assessment, leading to continuous improvement in teaching and learning practices.

In contrast, the other options describe decision-making approaches that are less effective in fostering sustained school improvement. For instance, data-free decision-making ignores evidence, reactive decision-making often leads to hasty choices without thorough analysis, and short-term decision-making focuses on immediate results rather than long-term growth and sustainability. Thus, data-driven decision-making stands out as a robust framework for supporting meaningful and strategic school improvement initiatives.