The Developing Organizational Capacity to Improve K-8 Mathematics Teaching and Learning is a 4-year Implementation and Improvement project. The project will develop and test a leadership model to improve K-8 mathematics teaching and learning by involving stakeholders across the K-8 spectrum. The project will support teachers, teacher leaders, and administrators in collectively identifying and addressing problems of practice in the teaching and learning of mathematics, and in turn develop plans to improve school and district organizational capacities to support stronger mathematics teaching. At the heart of the project is the Elementary Mathematics Leadership (EML) model, which is designed to improve stakeholder understandings of effective math teaching practices. The EML model involves collaboratively identifying classroom-based problems of practice with school and district personnel, designing and implementing professional development aligned with the problems of practice, and iterating those cycles of development, implementation, and revision to assess the model's effectiveness.
The EML model operates at the teacher, school, and district level using a design-based implementation research approach. At the district level, leadership teams in conjunction with researchers will identify problems of practice for which work on those problems will lead to a more coherent mathematics instruction in the district. Following this, professional development and coaching at the teacher level will be designed and implemented to target the problem of practice, with a focus on big ideas within the Common Core State Standards for Mathematics. This phase of the model also includes professional development aimed at school leaders and district administrators to strengthen organizational capacity to support and lead change related to the problem of practice. The final phase of the model calls on researchers, district, and school personnel to engage in an annual redesign of the intervention, making use of data gathered during the school year and evidence about what is happening in classrooms. This design acknowledges the broader policy context in which schools and districts operate as they work towards instructional change. To evaluate the effectiveness of the overall EML model, the project will collect a wide variety of data, including student achievement outcomes using standardized tests; assessments of teachers' mathematical knowledge, instructional practices, and efficacy measures; and measures of leader, administrator, and organizational capacities to support high-quality mathematics instruction. Four districts will be recruited to participate, enacting the model in pairs with a staggered start for one pair of districts to be able to measure treatment effects, using a variation of a switching replications design. Classroom practice and teacher outcomes will be assessed using a variety of MKT assessments, the Mathematical Quality of Instruction (MQI), and the Instructional Quality Assessment (IQA). School level outcomes will be collected via a leadership assessment and interview data, and district level outcomes will be assessed through the use of interview and documentary data. Analysis will include a statistical analysis of the EML model using hierarchical linear modeling, MANOVA/ANOVA, and regression as appropriate at the level of students and teachers, and qualitative analysis and descriptive statistics will be used at the school and district level due to small sample size.
The Discovery Research preK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
