OpenSciEd Lesson 6.3, Lesson 2: Weather Data From Seven Hailstorm Sites Data Task
Task
Use this Data Task with the Grade 6 OpenSciEd curriculum during unit 6.3, Lesson 2. Tuva has digitized the paper maps and static data tables provided in Parts 4 and 5 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. Where This Investigation Fits into the Storyline In the last lesson, students observed three video clips of hail falling in different areas of the United States on different days, developed a model to try to explain what causes hail to occur, and generated ideas for data to collect before, during, and after a hailstorm. During this lesson, students analyze and interpret data from cases of hail events at different locations and times of year to notice patterns and identify relevant factors that might explain the formation of hail. When to Use Tuva Use this Tuva Data Task on Day One after completing Parts 1, 2, and 3 (Navigation, Observe Hailstones, and Analyze Hail Frequency Map Data) of the OpenSciEd lesson. During step 4 (Analyze and Example Hailstorm Case), project Tuva on your board, have students pull it up on their computers, and explore the Fort Scott data together. *Depending on your students' experience with data tables and graphs, you may want to provide students with a physical hard copy of the data table as well. Point out that the data on the table and the data in Tuva Table and Tuva Case Card are the same. Explain that graphing is a visual way of sharing the same information but that the position of a data point is what communicates the information. Suggested Steps for Group Exploration of Fort Scott Map: Give students time to annotate their maps in Tuva before sharing aloud. Show students how to save their data visualization by selecting :ti[screenshot]. Suggested Steps for Group Exploration of Fort Scott Dataset: Get acquainted with the dataset. Read the :ti[ti-about-dataset] section to find out who collected the data. Identify what information was collected at each site by looking at the list of attributes in the case card. Show students how to filter out only the Fort Scott data. Click the :ti[ti-edit-attribute] icon beside :ta["Location"]. Ask students which attribute they'd like to explore first (temperature, relative humidity, windspeed, or wind gusts). Start by showing some simple distributions of the attribute they have chosen data. Drag your chosen attribute onto the y-axis. Any of the following graph types can be used to show distributions: :ti[dot], :ti[histogram], or :ti[box-and-dot-plot]. Select one from the toolbar. Ask students what the placement of a specific dot means. Say, "What does it mean if a data point is positioned higher up?" Ask students what they notice about the range and spread of the data. Then, drag :ta["Time (s)"] onto the x-axis. Show students how they can change the data to a line graph by selecting :ti[line-graph]. Ask the students why the dots changed position. Listen for responses indicating students understand that each data point is lined up with a specific y-axis value and with a specific time. Demonstrate how to use the annotation tools in Tuva to add arrows (:ti[ti-arrow]), draw shapes (:ti[ti-circle]), or labels (:ti[ti-text]). Have them add a reference line (:ti[ref-line-on-x]) on the graph to mark when the hailstorm happened. Before further discussion, give them time to explore other attributes in partners. Have them pick one data visualization to annotate with an arrow and a WIS statement. During Part 5 (Analyze Hailstorm Cases in Partners), have students work side-by-side on their computers. They will be able to save annotated maps and data visualizations. What Happens Next On Day Two, during the building understanding discussion, students can use data visualizations they have created to communicate about patterns they noticed.
At the end of the last lesson, you came up with ideas for the data that you'd need to collect before, during, and after a hailstorm to get to the bottom of why hailstorms occur. Today, you will have a chance to explore that data from eight different storms. First, you will explore one dataset as a class. Then you will break off into smaller groups to explore one of the other seven datasets. Later, you'll share your insights about this dataset with the larger class and, together, look for patterns across all of the datasets.
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