Students will investigate, “Where are the hottest and coolest places on our school campus, and how can data guide where shade trees should be planted?” Teams will collect temperature and humidity data, evaluate how precision, granularity, and metadata affect findings, and use computational tools to sort, filter, group, summarize, and visualize campus microclimates. Students will create reusable procedures with support from reference documentation, then present an interactive dashboard and evidence-based tree-planting recommendations to the principal and facilities team.

Students will collect temperature and humidity data across campus and evaluate how measurement precision and granularity affect accuracy, storage, and analysis. They will use metadata to interpret readings and answer where the hottest and coolest campus locations are. Students will use computational tools to sort, filter, group, summarize, and visualize microclimate data, creating reusable procedures with variables, lists, loops, and conditionals while consulting reference documentation. They will present an interactive dashboard and evidence-based shade-tree planting recommendations to the principal or facilities team.

Teams will create a campus sensor map, data-collection plan, and metadata guide documenting location, time, units, conditions, and measurement precision. They will maintain a structured temperature-and-humidity dataset and reusable, clearly named code procedures—developed with reference documentation—to sort, filter, group, summarize, and graph readings. Each team will produce a brief analysis showing how data granularity and precision affect accuracy, storage, and conclusions about campus microclimates. The final products will be an interactive dashboard identifying the hottest and coolest locations and a short, evidence-based shade-tree planting recommendation presented to the principal or facilities team.

Teams begin with a campus “temperature hunt,” using sensors to collect temperature and humidity readings at several sunny and shaded locations while recording metadata such as time, surface type, and shade level. They compare repeated readings taken at different intervals or precision levels and discuss how those choices affect accuracy, storage, and conclusions. Students place results on a shared campus map, identify early hot and cool spots, and generate questions about microclimates. Launch the challenge: “Where are the hottest and coolest places on our school campus, and how can data guide where shade trees should be planted?”

Host a Campus Microclimate Showcase for the principal, facilities team, families, and student leaders. Teams present interactive dashboards that sort, filter, group, and summarize three weeks of temperature and humidity data, including metadata about sensor location, time, and collection precision. Students demonstrate their reusable, documented code and explain how data granularity affected accuracy, storage, and analysis. Each team concludes with a map-based recommendation for shade-tree locations, then gathers audience feedback to support a final campus proposal.