Shumate Middle School and Carlson High School
Students at Shumate Middle School and Carlson High School pioneer the use of a WeatherSTEM package to collect atmosphere and pedosphere data, conduct research projects, and provide weather information to their local community. The package combines automated weather, leaf wetness, and soil moisture and temperature sensors with educational materials and curriculum content. The grant will also fund the addition of equipment required to conduct the GLOBE Automated Sensor Soil Moisture and Temperature Protocol. Students will be immersed in Citizen Science and learn about weather via the use of scientific instruments and technology. They will learn by making observations, collecting and analyzing real world data, and completing various online learning modules provided by WeatherSTEM. WeatherSTEM will also provide students with the opportunity to utilize technology to learn coding, and students will become familiar with various forms of code used to design and create weather apps. With this technology the schools will be able to provide the community with an up-to-the-minute weather website, weather social media pages (both Facebook and Twitter), and a weather app for all to utilize to make informed decisions. All data that correspond with GLOBE protocols will be reported to GLOBE.
The activities enabled by this grant will address the following Michigan Science
MS-ESS2-5 Collect data to provide evidence for how the motions and complex interactions of air masses results in changes in weather conditions.
MS-ESS2-6 Develop and use a model to describe how unequal heating and rotation of the Earth cause patterns of atmospheric and oceanic circulation that determine regional climates.
MS-ESS3-5 Ask questions to clarify evidence of the factors that have caused the rise in global temperatures over the past century.
HS-ESS2-4 Use a model to describe how variations in the flow of energy into and out of Earth’s systems result in changes in climate.
HS-ESS3-5 Analyze geoscience data and the results from global climate models to make an evidence-based forecast of the current rate of global or regional climate change and associated future impacts to Earth systems.
This grant demonstrates learning science by doing science.