# Quantitative Reasoning Research

**Quantitative Reasoning Strand Overview**

The capacity to reason quantitatively within real-world contexts which impact one’s life has many names, including numeracy, number sense, deductive reasoning, mathematical literacy, quantitative literacy, problem solving, contextualized mathematics, mathematical modeling, and quantitative reasoning. The definition of QR used in this project is:

Quantitative reasoning is mathematics and statistics applied in real-life, authentic situations that impact an individual’s life as a constructive, concerned, and reflective citizen. QR problems are context dependent, interdisciplinary, open-ended tasks that require critical thinking and the capacity to communicate a course of action.

We propose that QR has four fundamental components:

- Quantification act (QA): mathematical process of conceptualizing an object and an attribute of it so that the attribute has a unit measure, and the attribute’s measure entails a proportional relationship (linear, bi-linear, or multi-linear) with its unit.
- Quantitative literacy (QL): use of fundamental mathematical concepts in sophisticated ways
- Quantitative interpretation (QI): ability to use models to make predictions and discover trends, which is central to a person being a citizen scientist.
- Quantitative modeling (QM): ability to create representations to explain a phenomena.

You can find a copy of the quantitative reasoning learning progression here.

**Publications**

2013

- R.L. Mayes, J. Harris Forrester, J. Schuttlefield Christus, F.I Peterson, R. Bonilla, and N. Yestness. 2013. Quantitative Reasoning in Environmental Science: A learning progression. International Journal of Science Education. http://dx.doi.org/10.1080/09500693.2013.819534 (download)
- R.L. Mayes, F. Peterson, and R. Bonilla. 2013. Quantitative Reasoning Learning Progressions for Environmental Science: Developing a Framework. Numeracy 6(1): http://scholarcommons.usf.edu/numeracy/vol6/iss1/art4 (download)