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Quantitative Reasoning Learning Progressions for Environmental Science: Developing a Framework
  • Robert L Mayes, Georgia Southern University
  • Franziska Peterson, University of Wyoming
  • Rachel Bonilla, Georgia Southern University
  • quantitative reasoning,
  • learning progression,
  • quantification,
  • quantitative literacy,
  • modeling

Quantitative reasoning is a complex concept with many definitions and a diverse account in the literature. The purpose of this article is to establish a working definition of quantitative reasoning within the context of science, construct a quantitative reasoning framework, and summarize research on key components in that framework. Context underlies all quantitative reasoning; for this review, environmental science serves as the context.In the framework, we identify four components of quantitative reasoning: the quantification act, quantitative literacy, quantitative interpretation of a model, and quantitative modeling. Within each of these components, the framework provides elements that comprise the four components. The quantification act includes the elements of variable identification, communication, context, and variation. Quantitative literacy includes the elements of numeracy, measurement, proportional reasoning, and basic probability/statistics. Quantitative interpretation includes the elements of representations, science diagrams, statistics and probability, and logarithmic scales. Quantitative modeling includes the elements of logic, problem solving, modeling, and inference. A brief comparison of the quantitative reasoning framework with the AAC&U Quantitative Literacy VALUE rubric is presented, demonstrating a mapping of the components and illustrating differences in structure. The framework serves as a precursor for a quantitative reasoning learning progression which is currently under development.

Creative Commons License
Creative Commons Attribution-Noncommercial 4.0
Citation Information
Robert L Mayes, Franziska Peterson and Rachel Bonilla. "Quantitative Reasoning Learning Progressions for Environmental Science: Developing a Framework"
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