This project seeks to apply explainable artificial intelligence to the challenge of personalizing training for adult citizen scientists. The approach will be developed in the context of the Native Bee Watch (NBW) biodiversity monitoring project that began in 2016 at Colorado State University.
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TEAM MEMBERS:
Sarath SreedharanNikhil KrishnaswamyJill ZarestkyNathaniel Blanchard
We present the assets that collaboration across a land grant university brought to the table, and the Winterberry Citizen Science program design elements we have developed to engage our 1080+ volunteer berry citizen scientists ages three through elder across urban and rural, Indigenous and non-Indigenous, and formal and informal learning settings.
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TEAM MEMBERS:
Katie SpellmanJasmine ShawChristine VillanoChrista MulderElena SparrowDouglas Cost
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
Plants with persistent fleshy fruits that last throughout fall and into winter and spring are an important source of nutrition for animals and people in boreal, subarctic, and arctic regions, but little information on fruit retention or loss is available for these regions. We evaluated fruit loss for four species across Alaska using data from our Winterberry community science network.
In this study, we examined how two different CCS models, a contributory design and a co-created design, influenced science self-efficacy and science interest among youth CCS participants.
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TEAM MEMBERS:
Sarah ClementKatie SpellmanLaura OxtobyKelly KealyKarin BodonyElena SparrowChristopher Arp
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