OpenSciEd 6.4, Lesson 1: Considering Other Mountains Data Task
Task
Use this Tuva Investigation with the Grade 6 Open SciEd curriculum during Unit 6.4, Lesson 1 to replace the data table they create in their science notebooks during Part 8 and the Patterns of Change handout in Part 9. It 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 On Day 1 of this lesson, students were introduced to the anchoring phenomenon. They read about how Mt. Everest is changing based on data collected by Nepal and China. Then, they create a consensus model to represent what is happening at Mt. Everest and what is causing these changes. Today, students will be analyzing five different mountain cases in a jigsaw to look for similar data at other mountains about movement or growth. As a class, they consider how the patterns they found might explain how a mountain could move and/or grow. When to Use Tuva Use this Tuva Investigation on Day 2 after completing OpenSciEd the Navigation routine that kicks off the day. Before Part 8: Compare Different Mountain Peak Information Cards, have students pull up this Tuva Data Task on their computers. Students will use Tuva to organize a data table. Use page 19 of the Teacher Edition to help facilitate deciding what to include on the data table. During Step 2 of the Tuva Data Task, demonstrate how to collect and record the data from the Mount Everest Card together and pause to discuss how the data might help you all figure out what is going on with Mount Everest (pages 20-21 of the Teacher Edition). Then, have students do the same with their assigned mountain case card. They will work as a group to jigsaw their data, tidy their group's dataset, and create data visualizations to help them understand what their data shows. What Comes Next At the end of Day 2, students convene in a scientists' circle. Pages 23-26 of the Teacher Edition will help you facilitate. Encourage students to bring their data tables and visualizations to communicate about patterns they noticed. Teacher Tips In Step 10, students are given an opportunity to openly explore data. Here are some suggestions for making this portion flow more smoothly. If you have not used Tuva in prior units, consider pausing for direct instruction before this portion. Demonstrate the following: Clicking on attributes in the Case Card and dragging and dropping them onto the x or y-axes. Clicking once on any attribute in the Case Card to color-code the data and create a legend. Selecting different graph types from the tool bar. (Point out that if the types of data you are trying to use are not a good fit for that graph type, the graph will gray out.) Using the toolbar to add stats (like mean or percentage). Click :ti[stats], the stat you want to display, and then :ti[labels-on-statistics]. Support Vocabulary Students may not know the terms numerical and categorical. numerical: having to do with quantities or numbers categorical: having to do with categories Maintain Productive Struggle With These Prompts If students are struggling to figure out what question to explore, try these prompts: What questions could you ask about __________ [list an attribute] ? Try starting with a _____ [question type]. Let's reread the instructions to figure out whether we need numerical or categorical attributes. Which of the attributes in this dataset are [attribute type]? If students have a question, but they are not sure how to graph it, try these prompts: Let's back up. What is your question? Which of the variables/attributes are needed to answer your question? Now that you know which variables/attributes you need, how can you decide which one goes on the x-axis and which on the y-axis? You can't break Tuva. Try a graph type and if it grays out, you can try a different one. I notice part of the graph is grayed out. I wonder what went wrong. What other types of graphs could you try with the attributes you chose to investigate? If students are struggling to interpret the graph they created, try these prompts: What attribute is on your x-axis? The position of the data point from side-to-side tells you information about that attribute. What does it mean when a point/bar is further to the right on your graph? What attribute is on your y-axis? The position of the data point up-and-down tells you information about that attribute. What does it mean when a point/bar is further up on your graph? Some common patterns in graphs are increasing, decreasing, and staying about the same. Sometimes graphs don't have patterns at all. Does your graph fit any of these descriptions? Sometimes adding shapes or lines can help us see patterns in our data. Use the Tuva Tutorials to learn more about creating different graph types and using the Tuva Tools.
To figure out what is causing Mt. Everest to change, we need more information. Today, you will have a chance to explore some data from five other mountains around the world. First, you will work together to decide what data you want to record about each mountain. You'll set up a data table to keep your data organized. Your teacher will give you a card about one mountain. You'll carefully read the card and use it to fill in your row of the table. Afterward, you will share your data in a small group. Your group will create data visualizations that will help you identify similarities and differences between mountains. These similarities and differences may be clues to why Everest is changing.
Topics and standards: Earth Science, MS-ESS2-3, MS-ESS2-2, MS-ESS2-1, Grade 6, MS-ESS1-4, OpenSciEd, 3.3.6-8.D, 3.3.6-8.E, 3.3.6-8.F, 3.3.6-8.G