Deep Structure Modeling

The Deep Structure Modeling (DSM) project, National Science Foundation Award #DRL 2010223, addresses the pressing need to more effectively organize science teaching and learning around “big ideas” that run through disciplines. Big ideas are important tools for learning because they enable students to organize and link information within a consistent knowledge framework. However, finding ways to teach big ideas effectively is a significant challenge. In DSM we strive to meet this challenge through modeling. Specifically, students synthesize big ideas by abstracting them as deep structures within sets of examples that contain them. As learners apprehend a deep structure within the examples, they use the tools and procedures of explanatory modeling to express and develop it. The result is a big idea that is flexible, meaningful, and easy to express, providing a strong framework for making sense of new information. DSM is a collaboration between The University of Alabama and the University of Georgia.

Abstraction in Modeling through Synthesis

Abstraction in Modeling through Synthesis (AiMS), National Science Foundation Award #DRL 1720996, built knowledge about the value that abstraction can bring to modeling instruction. Models are abstractions because they represent select information, or structure, that has been pulled away from their referents. AiMS involved studies of what students should know about abstraction, how readily they could learn about abstraction and the ways in which modeling processes that emphasize abstraction can benefit learning. As part of these studies, researchers collaborated with classroom teachers to design an abstracting approach to explanatory modeling, called synthesis, that is featured in project publications. AiMS, which has transitioned to the Deep Structure Modeling project (DSM), was a collaboration between the University of Georgia and The University of Alabama.