The Lawrence Hall of Science
This activity takes about one to two 45-minute lesson periods.Learn more about Teaching Climate Literacy and Energy Awareness»
See how this Activity supports the Next Generation Science Standards»
Middle School: 2 Cross Cutting Concepts, 3 Science and Engineering Practices
High School: 1 Cross Cutting Concept, 2 Science and Engineering Practices
About Teaching Climate Literacy
Other materials addressing 5b
2.6 Greenhouse gases affect energy flow.
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Teaching Tips | Science | Pedagogy |
- Educator may want to use the text that accompanies this activity http://www.globalsystemsscience.org/studentbooks/cc/ch6 to establish context.
- While part of curricula designed for high school, the activity could be appropriate for upper middle school students, with appropriate supports and modifications.
- Graphing programs could be used or graphs made in advance for students to interpret if an educator wanted to focus on analysis and not making graphs.
- Instructions and link are provided at the end of the activity to access current 30+-year data and graphs on carbon cycle gases from NOAA ESRL, which keeps the resource from becoming outdated: http://www.esrl.noaa.gov/gmd/.
- This activity is from the Climate Change guide, which is part of the Global System Sciences curriculum education theme Key Global Problems.
About the Science
- The activity uses real data to analyze and compare atmospheric carbon dioxide levels recorded at monitoring stations in Mauna Loa and Antarctica for a 2-year period (2006-2007).
- The 30-year average (1975-2005) of monthly average carbon dioxide levels at Mauna Loa is observed and the change in concentration over time is calculated.
- The effects of seasonal variations and differences in land cover on carbon dioxide levels are introduced but not explained in detail.
- Comments from expert scientist:
- Graphing real world data
- comparing graphs
- interpreting results to understand the ecological significance
- Also would be a great extension for students to try using Excel to plot their graphs
- Update the data to reflect more current years
About the Pedagogy
- This activity is very straight-forward; students plot CO2 concentration data provided from the two locations, compare variations/patterns from month to month and over 2 years, and answer several questions about why the patterns might be different in the two locations. Then they compare data from both sites over 30 years and consider what longer-term data indicates about overall trends common to both locations.
- Questions posed to students require them to examine the data and explain what they find.
- Prerequisite background information is available at: http://www.globalsystemsscience.org/studentbooks/cc/ch6
- This resource engages students in using scientific data.
See other data-rich activities
Technical Details/Ease of Use
- This is a straightforward activity involving interpretation of data tables and corresponding graphs. Very low tech and easy to follow.
- Free teacher guide with downloadable files and additional activities is available upon request at: http://www.globalsystemsscience.org/teacherguides.
Next Generation Science Standards See how this Activity supports:
Cross Cutting Concepts: 2
MS-C1.4:Graphs, charts, and images can be used to identify patterns in data.
MS-C2.1:Relationships can be classified as causal or correlational, and correlation does not necessarily imply causation.
Science and Engineering Practices: 3
MS-P4.1:Construct, analyze, and/or interpret graphical displays of data and/or large data sets to identify linear and nonlinear relationships.
MS-P4.4:Analyze and interpret data to provide evidence for phenomena.
MS-P4.7:Analyze and interpret data to determine similarities and differences in findings.
Cross Cutting Concepts: 1
HS-C2.1:Empirical evidence is required to differentiate between cause and correlation and make claims about specific causes and effects.
Science and Engineering Practices: 2
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.
HS-P4.4:Compare and contrast various types of data sets (e.g., self-generated, archival) to examine consistency of measurements and observations.