Teachers tend to be lifelong learners, motivated to pursue professional learning that is meaningful to their particular needs. In 2013, Marrongelle et. al., noted “it is incumbent on the field to capitalize on emerging technologies in the design and delivery of effective professional development.” (p. 208). While the past decade has seen an increase in development of opportunities for personalized learning for mathematics teachers online (e.g., Silverman & Hoyos, 2018), more work is needed to provide additional research-based opportunities.
The InSTEP professional learning platform aims to support grades 6-12 teachers’ professional learning in teaching statistics and data science through a personalized online learning platform. While statistics and data analysis are included in standards for both mathematics and science, there are also many states across the country envisioning high school course pathways that include a heavier emphasis on statistics and even stand alone courses on data science. In this brief research report, we aim to share how we have designed supports for teachers to personalize their professional learning and results from a collective case study of 37 participants engaged in a field test of the platform in Fall 2022.