About the Session Join Tuva and the NSTA Professional Learning Team for a deep dive into how data can be authentically integrated into the eight science and engineering practices. In this interactive 2nd-12th session, attendees will explore strategies and tools that position students as the drivers of sensemaking and deepen their use of data.

Through grade-band breakout groups (2-5 and 6-12), educators will engage with data-rich tasks and instructional routines tailored to the unique needs of students at different grade levels, leaving with practical approaches to bring back to their classrooms.

Key Takeaways

• Develop a deeper understanding of the role of data across all eight science and engineering practices.
• Experience and analyze data-rich tasks that engage students in multiple science and engineering practices.
• Identify instructional moves that position students as the drivers of sensemaking through the use of data.

About the Session: Data plays a central role in how students make sense of scientific phenomena. In this hands-on session, co-facilitated by the NSTA Professional Learning Team and Tuva, participants will build confidence with foundational data skills while exploring how graphing, statistical reasoning, and data interpretation support students in analyzing evidence, identifying patterns, and constructing explanations. Using real-world datasets and interactive tools in Tuva, participants will examine graph choice, variability, distributions, and common data visualizations through the lens of science instruction.

Takeaways: Participants will deepen their understanding of core data literacy concepts and learn practical strategies for helping students use data to analyze evidence, identify patterns, and engage in science sensemaking aligned to the NGSS Science and Engineering Practices.

Presenters: Jocelyn Foran (Tuva Science Education Specialist) and Brianna Reilly Oliveira (NSTA Director of Professional Learning)

About the Session: The process of science is driven by questions. While it’s easy to ask a general question, crafting an investigable question requires deeper thinking and intentionality. Doing so within the constraints of an existing dataset creates an additional challenge. This session, co-facilitated by the NSTA professional learning team and Tuva, will highlight strategies for helping students clarify what data they have to work with, determine the types of questions that can and cannot be answered with a given dataset, and frame six different types of questions about data.

Takeaway: The types of questions you can ask depend on the data you have. Participants will learn how to guide students in identifying the structure and limits of the local datasets they encounter and in framing investigable questions that unlock the potential of data.

Presenters: Jocelyn Foran (Tuva Science Education Specialist) and Brianna Reilly Oliveira (NSTA Director of Professional Learning)

About This Session: Science data analysis relies on mathematical and statistical reasoning that develops across grade levels. Co-facilitated by the NSTA Professional Learning Team and Tuva, this workshop explores how NGSS Science and Engineering Practices connect with grade-level math standards to support student data analysis and interpretation. Participants will analyze authentic science datasets to identify grade-level mathematical, statistical, and data skills. They will examine how these math standards and science practices align and discover how to leverage math learning to strengthen science sensemaking.

Takeaways: Participants will identify grade-level data and statistical reasoning skills and examine how they support student use of the Science and Engineering Practices. Teachers will leave with strategies for connecting mathematics learning to data-rich science instruction.

Presenters: Jocelyn Foran (Tuva Science Education Specialist) and Brianna Reilly Oliveira (NSTA Director of Professional Learning)

About This Session: This workshop builds data literacy for science instruction through mathematical modeling with data. In this session, co-facilitated by the NSTA Professional Learning Team and Tuva, participants will work in a student role, using data to make sense of phenomena as they explore how distributions describe variability using dot plots, box plots, and histograms, and when to use mean, median, or mode. They will also model relationships between variables using scatterplots, lines of best fit, and concepts such as correlation, association, and linear vs. nonlinear patterns. Participants will reflect on how these skills can be incorporated into their own classrooms.

Takeaways: Participants will strengthen their understanding of distributions, variability, and relationships through mathematical modeling and will consider how to bring these ideas into their own classrooms to support student sensemaking with authentic science data.

Presenters: Jocelyn Foran (Tuva Science Education Specialist) and Brianna Reilly Oliveira (NSTA Director of Professional Learning)

About the Session: Do your students struggle to construct explanations and engage in argument from evidence using data? During this session, co-facilitated by Tuva and the NSTA Professional Learning Team, participants will analyze datasets to explore how explanations and arguments can be scaffolded with the CER structure. Data is central to the process of constructing a claim and selecting the strongest evidence. Participants will surface common student challenges, and identify instructional moves and prompts that strengthen claims, evidence selection, and reasoning in science instruction.

Takeaways: Participants will learn strategies to help students construct explanations and argue from evidence using data to support clearer claims, stronger evidence selection, and more effective reasoning in NGSS-aligned science sensemaking.

Presenters: Jocelyn Foran (Tuva Science Education Specialist) and Brianna Reilly Oliveira (NSTA Director of Professional Learning)