This activity introduces students to different forms of energy, energy transformations, energy storage, and the flow of energy through systems. Students learn that most energy can be traced back to nuclear fusion on the sun.
This activity from NOAA Ocean Service is about using aerial photographs to assess the impact of extreme weather events such as Hurricane Katrina. The activity features aerial views of Biloxi, MS post-Katrina and enables students to see evidence of the power of extreme weather on the environment.
Student teams design and build solar water heating devices that mimic those used in residences to capture energy in the form of solar radiation and convert it to thermal energy. In this activity, students gain a better understanding of the three different types of heat transfer, each of which plays a role in the solar water heater design. Once the model devices are constructed, students perform efficiency calculations and compare designs.
In this activity for undergraduates, students explore the CLIMAP (Climate: Long-Range Investigation, Mapping and Prediction) model results for differences between the modern and the Last Glacial Maximum (LGM) and discover the how climate and vegetation may have changed in different regions of the Earth based on scientific data.
In this activity, students are guided through the process of locating and graphing web-based environmental data that has been collected by GLOBE Program participants using actual data collected by students in Pennsylvania and comparing them to their local climatic boundary conditions. This activity highlights the opportunities for using GLOBE data to introduce basic concepts of Earth system science.
In this lesson, students complete a Myers-Briggs Type Inventory of their personality type as an introductory step to understanding what green jobs might suit their personal styles. From the information on this online tool, they look at different Green Jobs to explore possible careers.
In this activity, students review techniques used by scientists, as they analyze a 50-year temperature time series dataset. The exercise helps students understand that data typically has considerable variability from year to year and to predict trends or forecast the future, there is value in long-term data collection.