https://www.per-central.org/ The latest PER-Central features, resource additions, and announcements. en-US Copyright 2026, ComPADRE.org editor@per-central.org (Managing Editor) Mon, 09 Mar 2026 18:08:16 EST http://blogs.law.harvard.edu/tech/rss https://www.per-central.org/services/images/LogoSmallPER.gif https://www.per-central.org/ 125 35 Quantitative literacy---the use of mathematics to describe and understand the world---is an essential skill. One facet of quantitative literacy in physics is covariational reasoning: how changes in one quantity affect changes in another, related quantity. Research has demonstrated that reasoning mathematically in physics contexts is distinct from reasoning mathematically in a context-free way. Early indications suggest that, similarly, covariational reasoning is likely different in physics contexts than in mathematics. Moreover, research has shown that quantitative literacy is unlikely to improve in physics classrooms without direct instruction. There is a need to characterize and understand physics covariational reasoning towards developing instructional activities that can be used in physics classrooms to help students develop quantitative literacy. We characterize and operationalize physics covariational reasoning through a series of studies that examine how physics experts reasoned while generating graphical models. Our results, together with prior research in the field, are organized into a framework of covariational reasoning: the Covariational Reasoning in Physics (CoRP) framework. We present this framework and describe how it can be used towards identifying learning outcomes for introductory physics courses and beyond, identifying proto-expert resources that students may already have when entering physics courses, and developing instructional interventions that attend to improving students' quantitative literacy. We present two assessment tools, the Physics Inventory of Quantitative Literacy (PIQL) and the Generalized Equation-based Reasoning inventory of Quantity and Negativity (GERQN), designed to measure physics quantitative literacy across a range of student populations. We conclude with how these pieces can be used to guide development of instructional materials to improve students' physics quantitative literacy. https://www.per-central.org/items/detail.cfm?ID=17241 https://www.compadre.org/Repository/document/ServeFile.cfm?ID=17241&DocID=6131 https://www.per-central.org/bulletinboard/Thread.cfm?ID=17241 Education Practices/Instructional Material Design Wed, 25 Feb 2026 01:24:34 EST Meta-Representational Competence (MRC) is a theoretical framework that is used to analyze how people create and interact with external representations. Within Quantum Mechanics, problems may be approached or perceived differently based on the notation used (either Dirac, Matrix, or Spinor notation) in the problem statement or by the person working on the problem. Semi-structured interviews were conducted to present physics students with change of basis content problems in the context of Quantum Mechanics. These content questions were paired with MRC-focused follow-up questions for the explicit purpose of asking students about MRC concepts directly. Student statements were coded to confirm previously identified MRC concepts and to identify MRC concepts that are novel to this data. Our analysis of three student interviews demonstrates an array of MRC concepts, the usefulness of asking direct questions about MRC concepts as part of an interview, and solidifies MRC as a useful lens for investigating student thinking.<br /><br />The attached codebook is authored by Idris Malik and Warren Christensen. It includes every "Meta-representational Competence statement" made by the students in the interview study. The authors coded each statement, either with a code informed by prior literature, or one defined based on the dataset analysis. https://www.per-central.org/items/detail.cfm?ID=17228 https://www.compadre.org/Repository/document/ServeFile.cfm?ID=17228 https://www.per-central.org/bulletinboard/Thread.cfm?ID=17228 Education Foundations/Research Design & Methodology/Evaluation Tue, 20 Jan 2026 20:07:50 EST