Click here for the Data Driven curriculum adapted for remote learning.
In this data science lesson, students practice analyzing and interpreting data in order to answer an investigative question about air pollution in Washington. Student groups first collaborate to graph air pollution data from a city in Washington State. They then compile data as a class in order to observe trends and patterns across cities to make a claim about whether the time of year affects the amount of air pollution in Washington. Through this lesson, students will develop an understanding of foundational data science principles and recognize techniques for manipulating and analyzing data. Students will also gain skills in interpreting trends and patterns in data and writing evidence-based claims. In addition, students will gain an understanding of how air pollution affects human health and the global epidemiology of outcomes attributed to air pollution.
Lesson Plans and Supporting Documents