This lesson, "Awenasa Goes to Camp!," is a data analysis activity that presents maps of NASA Earth satellite data for a variety of locations across the United States for four unidentified months throughout the year.  Each location represents a real science camp th

Students observe monthly images of changing vegetation patterns, looking for seasonal changes occurring throughout 2017. These data can be used by students to develop their own models of change.

In this mini lesson, students explore the relationship of chlorophyll and solar radiation by analyzing line graphs from the North Atlantic during 2016-2018.

The extreme temperatures during July 2022 prompt students to investigate a model that displays historical heat wave frequency data to discover the importance of defining terms when interpreting data.

Students watch a short video to gather information about sources of methane emissions and then extend their understanding of these sources to evaluate monthly trends in the Alaska region, ultimately making connections to Earth’s energy budget.

For over 20 years, satellite instruments have measured the sea surface height of our ever-changing oceans.  This video of images shows the complicated patterns of rising and falling ocean levels across the globe from 1993 to 2015.

Students will use coloring sheets to create a color coded model of El Niño, then make comparisons using the actual model by answering questions. If the Data Literacy Map Cube is used with this, students will color their models first.

This lesson plan provides some generic maps, graphs, and data tables for use with the Data Literacy Cube. Because it is a differentiated resource, this lesson plan is appropriate for multiple grade bands. 

Students will make a claim about whether changing albedo contributes to changes in Arctic habitats.

By matching pie charts with dates between 2002 and 2020, students will predict how air quality has changed over the past two decades. They will then use color-coded Air Quality Index signatures to assess the accuracy of their predictions.