This project will design, develop, and test a sequence of lessons for high school aged youth from east Tennessee that will teach them artificial intelligence concepts by using images from planetary exploration and emerging Generative AI tools to create visually appealing generative artworks and digital stories.
We used a youth focused wild berry monitoring program that spanned urban and rural Alaska to test this method across diverse age levels and learning settings.
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TEAM MEMBERS:
Katie SpellmanDouglas CostChristine Villano
The Arctic Harvest-Public Participation in Scientific Research (which encompasses the Winterberry Citizen Science program), a four-year citizen science project looking at the effect of climate change on berry availability to consumers has made measurable progress advancing our understanding of key performance indicators of highly effective citizen science programs.
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TEAM MEMBERS:
Angela LarsonKelly KealyMakaela Dickerson
Informal STEM learning experiences (ISLEs), such as participating in science, computing, and engineering clubs and camps, have been associated with the development of youth’s science, technology, engineering, and mathematics interests and career aspirations. However, research on ISLEs predominantly focuses on institutional settings such as museums and science centers, which are often discursively inaccessible to youth who identify with minoritized demographic groups. Using latent class analysis, we identify five general profiles (i.e., classes) of childhood participation in ISLEs from data
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TEAM MEMBERS:
Remy DouHeidi CianZahra HazariPhilip SadlerGerhard Sonnert