Model-Based Reasoning in the Upper-Division Physics Laboratory: Framework and Initial Results

TL;DR

This paper develops a new framework for understanding model-based reasoning in upper-division physics labs, emphasizing the role of measurement tools and providing initial qualitative insights from student interviews.

Contribution

It introduces an extended modeling framework that includes measurement tools and demonstrates its utility through think-aloud interviews with students.

Findings

Students apply modeling facets to both physical systems and measurement tools.

Students struggle to articulate assumptions in model construction.

Insufficient prior understanding hampers effective model development.

Abstract

We review and extend existing frameworks on modeling to develop a new framework that describes model-based reasoning in upper-division physics labs. Constructing and using models are core scientific practices that have gained significant attention within K-12 and higher education. Although modeling is a broadly applicable process, within physics education, it has been preferentially applied to the iterative development of broadly applicable principles (e.g., Newton's laws of motion in introductory mechanics). A significant feature of the new framework is that measurement tools (in addition to the physical system being studied) are subjected to the process of modeling. Think-aloud interviews were used to refine the framework and demonstrate its utility by documenting examples of model-based reasoning in the laboratory. When applied to the think-aloud interviews, the framework captures and differentiates students' model-based reasoning and helps identify areas of future research. The interviews showed how students productively applied similar facets of modeling to the physical system and measurement tools: construction, prediction, interpretation of data, identification of model limitations, and revision. Finally, we document students' challenges in explicitly articulating assumptions when constructing models of experimental systems and further challenges in model construction due to students' insufficient prior conceptual understanding. A modeling perspective reframes many of the seemingly arbitrary technical details of measurement tools and apparatus as an opportunity for authentic and engaging scientific sense-making.