Effects of a data-based decision making intervention on student achievement

Data-based decision making (DBDM) is becoming important for teachers due to increasing amounts of digital feedback on student performance. In the quasi-experimental study reported here, teachers, principals, and academic coaches from 42 schools were trained for two years in using the results of half-year interim assessments for providing students with tailor-made instruction. Our results did not show any main effects of this DBDM training trajectory on student achievement but did indicate interaction effects with students’ low prior achievement levels and socioeconomic status. Teachers experience difficulties in translating student progress data into adaptive instruction in the classroom. Implications of our findings for teacher professionalization are discussed.