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Measuring and enhancing quantitative reasoning in physics instruction

Suzanne White Brahmia (UW Physics)
Wednesday, September 30, 2020 - 4:00pm to 5:00pm
An individual’s capacity to identify and understand quantitative situations is an expected outcome of taking a physics course. In the current crises in which we are mired, it is also essential to be an informed global citizen. 
Although quantitative procedural competency is a prerequisite for most introductory physics courses, spontaneous and productive mathematical reasoning across physics contexts is a desirable learning outcome of these courses for all students, regardless of major, and ideally it develops there. Physics Quantitative Literacy (PQL) is a set of interconnected skills and habits of mind that support quantitative reasoning about the physical world. In spite of being an important objective of physics instruction, there does not yet exist a validated instrument for assessing to what extent physics courses actually develop PQL. In this talk I will present the PIQL, Physics Inventory of Quantitative Literacy, which is in its final stages of instrument validation at the UW in a multi-institution collaboration. PIQL targets introductory physics - where the “math world” and “physical world” meet - assessing students’ proportional reasoning, covariational reasoning, and reasoning with signed quantities as they are used in physics. Unlike multiple-choice concept inventories, which assess conceptual mastery of specific physics topics, PIQL is a multiple-choice reasoning inventory that can provide snapshots of student reasoning that is continuously developing. Answer choices are constructed based on research-validated natures of expert mathematical reasoning in physics contexts. I will describe how this work is helping lead both to improved instruction that better meets the objective of developing physics quantitative literacy, and, through analytical methods of student responses, can help researchers better understand the novice state and the novice-expert transition. This work is support by the National Science Foundation DUE-IUSE # 1832836, # 1832880, and # 1833050. Preprint of paper is posted here:

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