Why a Data-Based Decision-Making Intervention Works in Some Schools and Not in Others

The use of data for adaptive, tailor-made education can be beneficial for students with learning difficulties. While evaluating the effects of a data-based decision-making (DBDM) intervention on student outcomes, considerable variation between intervention effects, ranging from high-intervention effects to small or even negative intervention effects, across schools was found. The main purpose of this study was to investigate whether educator and school organizational characteristics are related to the effects of a DBDM intervention on student achievement growth by comparing 10 primary schools with strong intervention effects with 10 primary schools with no intervention effects on student achievement. Supportive and hindering factors were studied by means of surveys and interviews with school management teams, and by examining school reports from the project trainers. Results indicate that schools with strong intervention effects differed from schools with no intervention effects with regard to their teachers' teaching quality, staff's attitude toward DBDM, and the school data culture