Car Coders is a hands-on data science activity that transforms an ordinary neighborhood walk into a real-world sustainability research project. Students observe and record the makes, models, and vehicle types of cars on their street, then use fuel economy data and color-coded classifications to investigate how much energy the local vehicle fleet consumes.

The activity introduces students to data collection, classification, analysis, and visualization while helping them connect climate concepts to the world around them. Participants learn to identify differences between sedans, SUVs, trucks, hybrids, and electric vehicles, and discover how vehicle choices influence fuel consumption and emissions. The resulting data can be displayed on classroom charts, maps, or community dashboards to reveal patterns that would otherwise remain invisible.

Car Coders applies behavioral science principles including disclosure, salience, and experiential learning. By making fuel efficiency visible in the local environment, the activity helps students develop a deeper understanding of transportation impacts while building critical thinking and data literacy skills. The project encourages learners to see everyday systems through the lens of observation and evidence, fostering curiosity about how communities can transition toward lower-carbon transportation.

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