Computational tools hold promise for science education, but each tool models information in a different way. This paper explores ways to connect what students know to the language and structures of different modeling tools.

Agent-based modeling can encourage students to think about scientific mechanisms. But to refine students’ understandings toward accurate explanations, comparing their models with data is just as important.