In this activity students will compare different methods for observing the Sun’s corona and make predictions about what they will observe during the April 8, 2024 total solar eclipse.

Students are introduced to the Earthrise phenomenon by seeing the Earth as the Apollo 8 astronauts viewed our home planet for the first time from the Moon.  They will analyze a time series of mapped plots of Earth science variables that NASA monitors to better understand the Earth

Students will synthesize information from maps that show population, concentrations of PM_2.5, and PM_2.5-attributable mortality across the globe in order to draw conclusions about the relationship between particulate pollution and human health. 

In this activity, learners predict the likelihood of aurora on Earth by examining the Kp-index and using NOAA’s 30-minute aurora forecast.

The Earth System Satellite Images, help the learner visualize how different Earth system variables change over time, establish cause and effect relationships for a specific variable, identify patterns, and determine relationships among variables over one year.

Students will engage in a “Zoom In Inquiry” learning routine to understand the symbols on a world map that shows population-weighted concentrations of PM_2.5. They will reflect on how their perception of the image changed as they saw more of the image.

Learners use a compass to trace magnetic field lines of a bar magnet. They observe a CME hitting Earth’s magnetosphere and compare its shape to the magnet. They then apply their understanding of magnetic fields to those found on the Sun.

The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner visualize how different Earth system variables change over time, identify patterns, and determine relationships among two variables in three months.

Selected GLOBE protocols and learning activities which support some aspect of the investigation of scale, proportion and quantity are outlined.

Students will engage in a “Zoom In Inquiry” learning routine to understand a world map that shows changes in PM_2.5-attributable mortality per 100,000 population (Bondie, 2013).