Which approach focuses on using student data to guide teaching instructions?

The approach that focuses on using student data to guide teaching instructions is data-driven instruction. This method emphasizes the importance of collecting and analyzing various types of student data, such as assessments, assignments, and classroom observations, to inform and enhance teaching practices. By continuously assessing student performance, educators can identify areas where students may need additional support, adjust their instructional strategies accordingly, and ultimately improve student learning outcomes.

Data-driven instruction allows teachers to make informed decisions based on concrete evidence rather than assumptions or intuition. This process includes setting specific learning goals based on data, monitoring student progress towards those goals, and using the data to differentiate instruction to meet the varied needs of students in the classroom.

While other approaches like inquiry-based learning, project-based learning, and experiential learning engage students in active learning and real-world problem solving, they do not inherently rely on the systematic analysis of student data as a foundation for instructional decisions. Instead, these methods emphasize student-driven exploration and collaboration. In contrast, data-driven instruction directly connects the analysis of student learning metrics to teaching strategies, ensuring that instruction is tailored to student needs based on measurable outcomes.