OpenSciEd 6.3, Lesson 20: Precipitation in Coastal Cities Data Task
Task
Use this Data Task during OpenSciEd Unit 6.3, Lesson 20. Tuva has digitized the static data tables in Part 7 to provide opportunities for students to deepen their ability to process and analyze data. This Data Task is not a standalone lesson. Use it in tandem with the OpenSciEd Teacher Edition to guide overall instruction and collaborative sensemaking. How it Fits into the Storyline This Data Task is just a small part of the larger lesson. It will come into play on Day 2. Students will begin the day by returning to the article they were reading on Day 1, "How the Ocean Changes Our Weather." They will summarize the key ideas of the article. When you are ready to begin Part 7, Analyze the Precipitation Data for Coastal Cities, project slide J and have students open the Data Task on their computers. Students will use the Tuva Tools to dynamically explore the data about coastal precipitation. They will create graphs showing patterns they notice in the data, share these graphs with their partners, and discuss how the data connects to the map and the content of the reading. Right after this Data Task, students will gather in a scientist circle. Encourage them to bring their computers so they can share the graphs they made as part of their consensus building discussion. Tips Depending on your students' experience with data tables and graphs, you may want to provide students with a physical hard copy of their data table as well. Encourage them to look for patterns in their data, make a data display using the variables that they noticed the pattern in, and observe how the pattern is communicated visually. This dataset provides aggregate data, or summary data, about city. For example, it provides the average annual rainfall rather than providing a list of how much rainfall a city received each year for 20 years. Because it is aggregate data, the types of data visualizations that will be useful are a bit more limited. Here are a few useful graph types: Bar Chart of Values: Drag either :ta["City"] or :ta["Coast"] on the x-axis. Drag :ta["Days With Precipitation"], :ta["Yearly Rain (in)"], or :ta["Yearly Snow (in)"] onto the y-axis. Students may choose to color-code the data by any third attribute. Click once on the attribute in the Case Card. Bar Chart of Means Drag :ta["Coast"] onto the x-axis. Drag :ta["Days With Precipitation"], :ta["Yearly Rain (in)"], or :ta["Yearly Snow (in)"] onto the y-axis. Scatter Plot (to look for relationships) Drag any numerical attribute onto the x-axis. Drag a second numerical attribute onto the y-axis. Color-code by :ta["Coast"]. Map Drag longitude onto the x-axis. Drag latitude onto the y-axis. Color-code by any of the numerical attributes to create a legend with a gradual scale.
You just completed summarizing the article "How the Ocean Changes Our Weather." Now you will see if the conclusions you drew from the reading play out in the real world. You will explore actual precipitation data from eight coastal cities to see if it matches your expectations. Click Next to get started.
Topics and standards: Earth Science, MS-ESS2-5, MS-ESS2-6, MS-ESS2-4, MS-PS1-4, Grade 6, OpenSciEd, 3.2.6-8.B, 3.3.6-8.H, 3.3.6-8.I, 3.3.6-8.J