Relating two quantities to describe a physical system or process is at the heart of "doing physics" for novices and experts alike. In this paper, we explore the ways in which experts use covariational reasoning when solving introductory physics graphing problems. Here, graduate students are considered experts for the introductory level material, as they often take the role of instructor at large research universities. Drawing on work from Research in Undergraduate Mathematics Education (RUME), we replicated a study of mathematics experts' covariational reasoning done by Hobson and Moore with physics experts [N. L. F. Hobson and K. C. Moore, in RUME Conference Proceedings, pp. 664-672 (2017)]. We conducted think-aloud interviews with 10 physics graduate students using tasks minimally adapted from the mathematics study. Adaptations were made solely for the purpose of participant understanding of the question, and validated by preliminary interviews. Preliminary findings suggest physics experts approach covariational reasoning problems significantly differently than mathematics experts. In particular, two behaviors are identified in the reasoning of expert physicists that were not seen in the mathematics study. We introduce these two behaviors, which we call Using Compiled Relationships and Neighborhood Analysis, and articulate their differences from the behaviors articulated by Hobson and Moore. Finally, we share implications for instruction and questions for further research.
One desired outcome of introductory physics instruction is that students will be able to reason mathematically about physical phenomena. Little research has been done regarding how students develop the knowledge and skills needed to reason productively about physics quantities, which is different from either conceptual understanding or problem-solving abilities. We introduce the Physics Inventory of Quantitative Literacy (PIQL) as a tool for measuring quantitative literacy (i.e., mathematical reasoning) in the context of introductory physics. We present the development of the PIQL and results showing its validity for use in calculus-based introductory physics courses. As has been the case with many inventories in physics education, we expect large-scale use of the PIQL to catalyze the development of instructional materials and strategies-in this case, designed to meet the course objective that all students become quantitatively literate in introductory physics. Unlike concept inventories, the PIQL is a reasoning inventory, and can be used to assess reasoning over the span of students' instruction in introductory physics.
We present a set of modes of reasoning about ratio and proportion as a means of operationalizing expert practice in physics. These modes, or natures of proportional reasoning, stem from consideration of how physicists reason in context and are informed by prior work in physics and mathematics education. We frame the natures as the core of an emerging framework for proportional reasoning in introductory physics, that will categorize the uses of proportional reasoning in introductory physics contexts, and provide guidance for the development of reliable assessments. We share results from preliminary assessment items indicating that university physics students have difficulty interpreting and applying ratios in context.
We have developed the Physics Inventory of Quantitative Literacy (PIQL) as a tool to measure students' quantitative literacy in the context of introductory physics topics. We present the results from various quantitative analyses used to establish the validity of both the individual items and the PIQL as a whole. We show how examining the results from classical test theory analyses, factor analysis, and item response curves informed decisions regarding the inclusion, removal, or modification of items. We also discuss how the choice to include multiple-choice/multiple-response items has informed both our choices for analyses and the interpretations of their results. We are confident that the most recent version of the PIQL is a valid and reliable instrument for measuring students' physics quantitative literacy in calculus-based introductory physics courses at our primary research site. More data are needed to establish its validity for use at other institutions and in other courses.
We are developing the Physics Inventory of Quantitative Literacy (PIQL), a new research based assessment (RBA) focused on quantitative reasoning-rather than conceptual understanding-in physics contexts. We rapidly moved administration of the PIQL online in Spring 2020 due to the COVID-19 pandemic. We present our experiences with online, unproctored administration of an RBA in development to students enrolled in a large-enrollment, calculus-based, introductory physics course. We describe our attempts to adhere to best practices on a limited time frame, and present a preliminary analysis of the results, comparing results from the online administration to earlier results from in-person, proctored administration. We include discussion of online administration of multiple-choice/multiple-response (MCMR) items, which we use on the instrument as a way to probe multiple facets of student reasoning. Our initial comparison indicates little difference between online and paper administrations of the PIQL, except for performance MCMR items
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