Investigating the role of model-based reasoning while troubleshooting an electric circuit

Abstract

We explore the overlap of two nationally-recognized learning outcomes for physics lab courses, namely, the ability to model experimental systems and the ability to troubleshoot a malfunctioning apparatus. Modeling and troubleshooting are both nonlinear, recursive processes that involve using models to inform revisions to an apparatus. To probe the overlap of modeling and troubleshooting, we collected audiovisual data from think-aloud activities in which eight pairs of students from two institutions attempted to diagnose and repair a malfunctioning electrical circuit. We characterize the cognitive tasks and model-based reasoning that students employed during this activity. In doing so, we demonstrate that troubleshooting engages students in the core scientific practice of modeling.

arXiv comment20 pages, 6 figures, 4 tables; Submitted to Physical Review PER

References in corpus (3)

• Students' Understanding of Direct Current Resistive Electrical Circuits
• The Process of Transforming an Advanced Lab Course: Goals, Curriculum, and Assessments
• Model-Based Reasoning in the Upper-Division Physics Laboratory: Framework and Initial Results

Cited by in corpus (9)

• The Modeling Framework for Experimental Physics: Description, development, and applications
• Investigating the Role of Socially Mediated Metacognition During Collaborative Troubleshooting of Electric Circuits
• Not engaging with problems in the lab: Students' navigation of conflicting data and models
• Using think-aloud interviews to characterize model-based reasoning in electronics for a laboratory course assessment
• Characterizing lab instructors' self-reported learning goals to inform development of an experimental modeling skills assessment
• Implementation and goals of quantum optics experiments in undergraduate instructional labs
• The Boiling-Frog Problem of Physics Education
• Electronics lab instructors' approaches to troubleshooting instruction
• Using Computational Essays to Redistribute Epistemic Agency in Undergraduate Science