The term data-based decision-making can refer to a wide range of practices from formative classroom use of monitoring in order to improve instruction to system-wide use of “big” data to guide educational policy. Within the context of special education, a primary focus has been on the formative classroom use of data to guide teachers in improving instruction for individual students. For teachers, this typically involves the capacity to (1) determine what data need to be collected to appropriately monitor the skill being taught, (2) collect that data, (3) interpret the data and make appropriate decisions, and (4) implement changes as needed. A number of approaches to such data-based decision-making have evolved, including precision teaching, curriculum-based assessment, and curriculum-based measurement. Evidence from systematic reviews and meta-analyses indicates instruction incorporating data-based decision-making has positive effects on outcomes for students with special education needs although the size of these effects has been variable. While the extent of the research base is modest, there are indications that some specific factors may be related to this variability. For example, the use of decision-making rules and graphic display of data appears to improve student outcomes and the frequency of data collection may differentially affect improvement. The presence and frequency of support offered to teachers may also be important to student outcomes. There is a need to increase our research base examining data-based decision-making and, more specifically, a need to more clearly define and characterize moderators that contribute to its effectiveness. In addition, there is a case for research on the wider use of data on student outcomes to inform broader policy and practice.
Using Evidence-Based Practice and Data-Based Decision Making in Inclusive Education
