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Grade Level: 3-5, 6-8, 9-12

Our Data Literacy Cube Page (and supporting resources) have been updated!  The new resources include only 1 cube for all three (maps, graphs, and data) Question Sets, Lexile levels, and addresses WIDA standards for multilingual learners!


Grade Level: 6-8, 9-12

Students analyze two North Pole orthographic data visualizations produced from soil moisture data. After describing trends in the seasonal thaw of land surfaces, students demonstrate their understanding of Earth’s energy budget by explaining relationships and make predictions about the dataset.


Grade Level: 6-8, 9-12

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.


Grade Level: 6-8, 9-12

By investigating the data presented in a model that displays extreme summer air temperatures, students explain energy transfer in the Earth system and consider the impact of excessive heat on local communities.


Grade Level: 3-5, 6-8, 9-12

The My NASA Data Literacy Cubes guide students’ exploration of graphs, data tables, and mapped images of NASA Earth science data (or other sources of Earth data). Leveled question sheets provide opportunities for students to connect with data, regardless of language proficiency or academic skill. 



Grade Level: 3-5, 6-8, 9-12

In this activity, students will use sea-level rise data to create models and compare short-term trends to long-term trends. They will then determine whether sea-level rise is occurring based on the data.



Grade Level: 3-5, 6-8, 9-12

This series of videos highlights how NASA Climate Scientists use mathematics to solve everyday problems.  These educational videos to illustrate how math is used in satellite data analysis. 


Grade Level: 9-12

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.


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