Invigorating Statistics Teacher Education Through Professional Online Learning (InSTEP)

Implementing meaningful statistics education in middle and high schools has been a persistent challenge in the United States. Statistics and data science are critical domains for STEM careers and the general data literacy of the citizenry. This project seeks to strengthen the teaching of statistics and data science in grades 6-12 through the design and implementation of an online professional learning environment for teachers. The professional learning environment aims to support in-service teachers in developing stronger content knowledge related to statistics, and knowledge of how to effectively teach statistics in their classrooms. The project will also evaluate a model of professional development that integrates personalized online learning and microcredentialing (earning small-scale certifications) to better understand its effectiveness in supporting teacher learning. The project will draw from previous work to assemble online modules that engage teachers in doing high-quality statistics and data science tasks, the analysis of video of teachers' and students' work with those tasks, learning a pedagogical framework for teachers to implement the tasks, and exploring guidelines for identifying and developing high-quality statistics and data science tasks. The project will study teacher learning through the use of these modules, and the pathways that teachers choose through them to understand the effectiveness of the model.

The project builds on previous work by the investigators to develop research-based teacher professional development modules that support learning about statistics and statistics education in grades 6-12. Materials currently developed include a series of microcredentials with design features consistent with research on effective teacher professional development. They include opportunities for teachers to engage with statistics content appropriate to the target grade levels they teach, active learning opportunities that engage them with teachers in similar contexts, and a coherent focus that builds on the knowledge and experience teachers bring to the table. The project will take place in iterative phases, beginning with focus groups of middle and high school teachers and district leaders based on first drafts of the materials. This will be followed by cognitive interviews with teachers who engage in the microcredential ecosystem which will inform modifications to the system. Following this phase, cohorts of teachers (25 in the first cohort, 75 in the second) will participate in scaffolded professional development engagement with the materials, and will be assessed with respect to changes in their knowledge and practice. The project will assess changes in teacher knowledge using reliable and valid measures of statistics knowledge and practice. Data will be collected from the online platform regarding teacher engagement and usage to better understand usage and pathways through the materials. The professional learning platform will be made available as a free and open online source at the close of the project.

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.