Modeling Data Use for Effective Instruction

The logic behind the rise of concerted efforts to strategically use data to inform instructional decisions appears to be relatively straightforward. If a teacher has high-quality data about a student, she should be able to adapt her instruction to meet each student in his zone of proximal development (ZPD: Vygotsky 1978), or that place where an appropriate amount of challenge with scaffolding is present to help the student grow and advance. This logic almost seems self-evident. If a teacher knows what a learner knows, understands, and can do, the teacher can adjust to provide developmentally appropriate instruction. Some recent large-scale evaluations bolster this position, providing evidence that data-driven reform can significantly impact student achievement levels in language and mathematics. Not surprisingly, policy across various educational levels has increasingly insisted that high-quality teachers be adept at using data effectively to guide their instructional decisions. The...