UC Berkeley

Coordinating modeling and real-world data is central to building scientific theories. This paper examines how a complementary focus on modeling and data contributed to 8th grade students' learning of mechanisms underlying wildfire smoke spread in MoDa, a web-based environment that integrates computational modeling side-by-side with real-world data for comparison and validation. Epistemic network analysis of student responses in pre-post tests revealed a shift from primarily macro-level explanations to explanations that integrated macro and micro-level explanations of the phenomenon. Video data analysis revealed three design elements that contributed to student learning: Naming of the blocks, match between data and model visualization, and collective reflections on models. We reflect on implications for the design of environments that integrate computational modeling with real-world data analysis.