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!

Are you searching for resources to use with your students related to Science and Engineering Practices?  Review these graphics that will help to hone students' attention to the specific practices in science and how they relate to investigating, sense-making, and critiquing of data.

This video explains what a Scientifically-Interesting Story is.

Using hourly graphs of PM 2.5 data and HYSPLIT model trajectories, students will collect evidence for the effects of fireworks on air quality.

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.

These resources are intended to be used with teachers and students to help model how to apply data literacy skills to analyzing patterns as they relate to stability and change in COVID-19 (and related human geographic) and nitrogen dioxide data.

Students watch a visualization video and answer questions on the potential of increasing megadroughts in the southwest and central United States from 1950-2095 using models created by soil moisture data.

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.

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.

The Earth System Satellite Images help students observe and analyze global Earth and environmental data, understand the relationship among different environmental variables, and explore how the data change seasonally and over longer timescales.