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Main Authors: Zimmerman, Charlotte, Olsho, Alexis, Loverude, Michael, Brahmia, Suzanne White
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2306.00921
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author Zimmerman, Charlotte
Olsho, Alexis
Loverude, Michael
Brahmia, Suzanne White
author_facet Zimmerman, Charlotte
Olsho, Alexis
Loverude, Michael
Brahmia, Suzanne White
contents Developing and making sense of quantitative models is a core practice of physics. Covariational reasoning -- considering how the changes in one quantity affect changes in another, related quantity -- is an essential part of modeling quantitatively. Covariational reasoning has been studied widely in mathematics education research, but has only begun to be used in physics education research. We present evidence from three studies of 25 individual interviews with physics experts, in which the experts were asked to reason out loud while generating graphical models. We analyze the studies through the lens of covariational reasoning frameworks from mathematics education research, and determine that the frameworks are useful but do not completely describe the covariational reasoning of the physics experts we interviewed. From our data, we identified reasoning patterns that are not described in the mathematics education research that, together with the mathematics covariational reasoning frameworks, begin to characterize physics covariational reasoning.
format Preprint
id arxiv_https___arxiv_org_abs_2306_00921
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Expert covariational reasoning resources in physics graphing tasks
Zimmerman, Charlotte
Olsho, Alexis
Loverude, Michael
Brahmia, Suzanne White
Physics Education
Developing and making sense of quantitative models is a core practice of physics. Covariational reasoning -- considering how the changes in one quantity affect changes in another, related quantity -- is an essential part of modeling quantitatively. Covariational reasoning has been studied widely in mathematics education research, but has only begun to be used in physics education research. We present evidence from three studies of 25 individual interviews with physics experts, in which the experts were asked to reason out loud while generating graphical models. We analyze the studies through the lens of covariational reasoning frameworks from mathematics education research, and determine that the frameworks are useful but do not completely describe the covariational reasoning of the physics experts we interviewed. From our data, we identified reasoning patterns that are not described in the mathematics education research that, together with the mathematics covariational reasoning frameworks, begin to characterize physics covariational reasoning.
title Expert covariational reasoning resources in physics graphing tasks
topic Physics Education
url https://arxiv.org/abs/2306.00921