In this session, co-facilitated by NSTA and Tuva, 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.

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. This session is part of a larger conference course, a four-part series of sessions around using local data as evidence in making sense of complex phenomena. Participants may attend a single session, or string all four together for deep, lasting learning.