Empowering Educators: Supporting Equitable Teaching of Statistics & Data Science Across Grades K-16

The MODULE(S2) project (www.modules2.com) created curriculum materials to support preservice teachers in gaining knowledge, pedagogical skills, confidence, and motivation to teach statistics & data science equitably with authentic data about societal issues. We will discuss the design of these materials, including how they incorporate technology (CODAP and StatKey), data investigation activities, and representations of the practice of teaching statistics to meet these goals. Key components include reading modern multivariate visualizations, interpreting data on educational outcomes through an equity lens, and studying project-based learning approaches to investigate issues of equity in local communities. We will also present the results of a study on preservice teachers' development of equity literacy and critical statistical literacy through use of these materials. 

The introduction of statistics and data science content in high school (HS) Algebra I, Algebra II, and Geometry courses continues to grow rapidly in the United States. HS teachers, however, do not have sufficient access to resources or support to effectively integrate statistics and data science in these classes. As a result, many HS students do not appreciate the relevance and importance of statistics in our data-driven world. To help address these gaps, the NSF-funded ESTARS project focuses on teacher professional development: to empower teachers with statistics knowledge and pedagogical practices that will serve them and others beyond the life of this project. In this project, approximately 25 HS math teachers are recruited yearly to collaborate with our team of experienced statistics educators and curriculum developers, and with each other in developing audience-specific GAISE-focused curricular materials that use recommended teaching practices with documented impact on student learning. To promote sustainability, upon "graduation," teachers are invited back to serve as mentors. This presentation will share findings from this project, on both teacher and student experiences. 

Statistics graduate teaching assistants (GTAs) play key roles in undergraduate statistics education, especially at the introductory level. In large university settings, introductory statistics courses and recitation sessions are often taught by GTAs. Supporting GTAs in implementing instructional recommendations (e.g., GAISE College Report) is an important issue. One of the initial steps toward this effort is identifying key areas of support for GTAs. To do so, we conducted a study on problems of practice perceived by statistics GTAs during professional development that was embedded in GTAs' instructor and mentoring meetings. The professional development included modules with the goal of teaching equitably with authentic data. Based on the data gathered from interviews and recordings from the professional development meetings in two GTA communities, we discuss thematic categories of problems of practice experienced by GTAs. These categories could inform the field in guiding what efforts are needed to better support GTAs to teach equitably with authentic data. 

The ESTEEM Project started in 2016 with a focus on preparing individuals to teach statistics and data science. Through curriculum creation and professional development for teacher educators (e.g., webinars and live workshops), we have supported and trained a diverse set of mathematics teacher educators (MTEs) using a multifaceted approach. Our unique curriculum design embeds content directly into learning management systems that are shareable and editable by MTEs. In our current work, we seek to build on the practices of improvement science to create fundamental changes in the practice of statistics teacher education. Our work is informed by 4 system studies that have revealed barriers facing MTEs, such as curriculum limitations, and characteristics and practices of early career teachers. Looking forward, we are developing a networked improvement community (NIC) that includes MTEs, professional organizations, research projects, and existing communities. Future opportunities for learning will allow NIC participants to exchange ideas and communicate within a Slack community and an online Statistics Teacher Education Hub.