Students identify patterns in chlorophyll concentration data to formulate their explanations of phytoplankton distribution.
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Students will identify and describe the relationship between watersheds and phytoplankton distribution.
This Lesson Plan provides some generic maps, graphs, and data tables for use with the Data Literacy Cubes. Because it is a differentiated resource, this Lesson Plan is appropriate for multiple grade bands.
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
Learners follow adventurous camper, Awenasa, as she travels the United States and attends various camp locations throughout the year. Learners analyze data to find her location among the various campsites using monthly averaged NASA satellite data (Cloud Coverage, Surface (S
The Hurricane Dynamics Implementation Sequence provides a series of lessons and activities for students to learn how hurricanes affect the different spheres within the Earth System by using maps and other geographic representations, tools, and technologies to acquire, process, and report informat
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.
In this NASA-JPL lesson, students create a model of a volcano, produce and record lava flows, and interpret geologic history through volcano formation and excavation.
In this lesson, Observing Earth’s Seasonal Changes, students observe patterns of average snow and ice amounts as they change from one month to another, as well as connect the concepts of the tilt and orbit of the Earth (causing the changing of seasons) with monthly snow/ice data from January 2008
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.