Cynthia Fadem, Earlham College, InTeGrate; SERC
Activity takes about a 30 minute class session.Learn more about Teaching Climate Literacy and Energy Awareness»
See how this Activity supports the Next Generation Science Standards»
High School: 1 Disciplinary Core Idea, 2 Cross Cutting Concepts, 2 Science and Engineering Practices
About Teaching Climate Literacy
Other materials addressing 4f
Other materials addressing 5b
Other materials addressing 5c
2.1 Changes in energy flow over time.
2.6 Greenhouse gases affect energy flow.
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Teaching Tips | Science | Pedagogy |
- Educators have to request access to instructor materials by filling out a form but will need to do only once. When they are accepted into the system as an instructor, they will have all access to all such designated materials.
- This is a quantitative exercise and uses a spreadsheet program, both of which can be problematic for students. The activity provides several suggestions for helping students through the quantitative and graphing parts of the activity.
- This is the second of two case studies that examine the climate system. These case studies can be used independently or together, and there is an overarching teacher's guide that has lecture notes, assessment questions, and background information. https://serc.carleton.edu/integrate/teaching_materials/climate_change/unit5.html
- Student materials do not refer to the source of the data; however, the instructor materials do. Educators should let the students know where the data comes from and suggest that they enter this information in their spreadsheet with the data. The information is also in the slides.
About the Science
- This activity focuses on interpreting geoscientific data (atmospheric methane recorded in ice cores) and examining relative changes in climate.
- Passed initial science review - expert science review pending.
About the Pedagogy
- Students graph and analyze atmospheric methane data from ice core records, and compare the relative forcing power of methane and CO2. Using the methane data and current rate of change, students are asked to predict what is likely to happen to methane concentrations and associated atmospheric temperature changes and what humans would need to do to either mitigate or adapt to predicted changes.
- The activity also helps students connect their quantitative results with the implications for climate and for humans. This shows how numerical findings are useful.
- Activity includes Student Instructions, Student data sheet, Instructor Guidelines, and PowerPoint presentation.
- This resource engages students in using scientific data.
See other data-rich activities
Technical Details/Ease of Use
- This activity is well thought out and carefully described. All of the materials are included, and each step of the process is thoroughly documented. Supplemental resources are also provided.
- The student and instructor document files have different and somewhat generic names, unlike how the name for the link appears in the instructions. Instructors should be aware and make sure they have the downloaded files identified appropriately.
Next Generation Science Standards See how this Activity supports:
Disciplinary Core Ideas: 1
HS-ESS2.D4:Current models predict that, although future regional climate changes will be complex and varied, average global temperatures will continue to rise. The outcomes predicted by global climate models strongly depend on the amounts of human-generated greenhouse gases added to the atmosphere each year and by the ways in which these gases are absorbed by the ocean and biosphere.
Cross Cutting Concepts: 2
HS-C4.4:Models can be used to predict the behavior of a system, but these predictions have limited precision and reliability due to the assumptions and approximations inherent in models.
HS-C7.2:Change and rates of change can be quantified and modeled over very short or very long periods of time. Some system changes are irreversible.
Science and Engineering Practices: 2
HS-P2.6:Develop and/or use a model (including mathematical and computational) to generate data to support explanations, predict phenomena, analyze systems, and/or solve problems.
HS-P4.1:Analyze data using tools, technologies, and/or models (e.g., computational, mathematical) in order to make valid and reliable scientific claims or determine an optimal design solution.