Participants will learn strategies for helping students: identify different types of data, 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.

Data is the heart of science practice, but many students are stymied by real-world datasets. In this workshop, learn how to guide students in identifying the structure and limits of the datasets they encounter and in framing investigable questions that unlock the potential of data. We’ll begin by “getting to know” a dataset- its cases, attributes, and source. Then, with student hats on, participants will engage in activities to determine what questions can—and can’t—be asked of the data. Next, using Tuva’s free data literacy handouts, teachers will learn six types of questions that can be used to unlock data insights (variability, comparisons, relationships, time, proportion, and geographic distribution). They will practice determining whether or not each type is appropriate for a given dataset and drafting questions. Finally, participants will pick a dataset and draft a brief lesson that scaffolds the process of framing investigable questions about data.