InSTEP is developing an online personalized professional learning platform to support teachers' growth in providing students learning opportunities in statistics and data science using key practices and processes with data. We are creating a scalable, accessible, and flexible approach aligned with research-based principles of effective professional learning. We use design principles for online teacher learning, and our materials are based on research on students' and teachers' learning in statistics and data science education.
Co-PI(s): Gemma Mojica and ALex Dreier, North Carolina State University
Learn More: InSTEP overview