Gemma Mojica

North Carolina State University (NCSU)
08/01/2019

This project seeks to strengthen statistics and data science instruction in grades 6–12 through the design and implementation of an online professional learning environment for teachers. In partnership with RTI International, the InSTEP project designed and launched instepwithdata.org, an online professional learning platform that supports in-service teachers in developing both deeper content knowledge in statistics and the pedagogical expertise needed to teach statistics and data science effectively in their classrooms.

InSTEP is intentionally designed as a flexible professional learning experience with no fixed sequence of completing activities and modules. Teachers can chart their own learning pathways, engaging with selected resources or the full collection of materials based on their interests and needs. This flexibility allows educators to work at their own pace while deepening their understanding of key aspects of classroom practice, including selecting meaningful data and statistics tasks, facilitating rich classroom discourse, and making thoughtful choices about technology tools. 

InSTEP provides two primary types of learning experiences:

Self-Paced Modules. These modules support focused exploration of 7 individual dimensions, helping teachers strengthen both their statistical content knowledge and instructional practice. Together the 7 interconnected dimensions characterize effective learning environments for teaching data science and statistics, as shown in the accompanying diagram. As of January 2026, the platform includes 15 modules spanning the seven dimensions.

A diagram of a diagram</p>
<p>AI-generated content may be incorrect.

Data Investigations. These inquiry-oriented experiences immerse teachers in working with real-world, multivariate datasets using data visualization tools. Each investigation is situated in an authentic context and engages teachers in core Data and Statistical Practices and Central Statistical Ideas. Investigations are organized around the Data Investigation Process (Lee et al., 2022), represented in the puzzle-piece figure. As of January 2026, there are six investigations available.

Hexagon shaped figure formed by interlocking puzzle pieces. Starting at the top we have a puzzle piece labeled Frame Problem, moving clockwise, next is a  puzzle piece labeled Consider & Gather data, next is a puzzle piece labeled Process data. At the bottom is a puzzle piece labeled Explore & Visualize Data, next is a puzzle piece labeled Consider Models, and, lastly, a puzzle piece labeled Communicate & Propose Action. These phases are represented with puzzle pieces that fit together to show phases rely on each where the process could be linear or nonlinear.