Many factors influence how teachers access, manage, interpret and act on data.  This paper examines strategies that two U.S. school districts and their schools used to facilitate data-driven decision-making and to support the use of interim assessments in elementary mathematics.  It draws on interviews with district staff, instructional coaches, and school principals in one large urban and one small suburban school district in one state in the United States and is part of a larger CPRE study of the use of interim assessments in these two sites. 

We identified several conditions that were critical to creating and supporting a culture of data use.  First, both districts established and communicated expectations for the use of assessment results.  The districts viewed interim assessments as “teaching tools” that would support and guide teachers’ instruction by providing them with timely and relevant information about their students’ mastery of concepts and skills covered in the districts’ core mathematics curriculum and the state’s standards during a specified instructional period.  Teachers were expected to use assessment results to reflect on their instruction, and to provide remediation for students in areas of weakness and enrichment in areas of strength during a dedicated period of time following the assessments.  Second, the districts designed “user-friendly” electronic data systems that gave teachers easy ways to analyze student performance on individual items (urban district only), the entire test and associated learning standards.  The urban district developed data analysis protocols to assist teachers in evaluating data from the interim assessment and their teaching strategies, to plan instruction for the re-teaching time, and to identify professional development needs.  Third, both districts provided professional support in curriculum, the use of the data management systems, analysis of assessment data, and, to differing extent, instructional approaches.  Both districts designated school-based mathematics coaches for instructional and content support—a full-time specialist in the suburban district, but only limited release time for a grade level teacher in the urban schools. The suburban teachers also had access to a district-level math coach and instructional aides to work with their students.  Fourth, the districts scheduled dedicated time for teachers to discuss assessment results and instructional techniques, to re-teach content and skills to students and to participate in professional development. Finally, school leadership and a culture of data use were the most critical factors.  School leaders reinforced expectations for data use by modeling (conducting their own analyses) and monitoring (reviewing and providing feedback) teachers’ use of data, creating time for teacher collaboration, and providing direct support to teachers through modeling instruction.