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Quantitative Reasoning

This page is intended to support faculty in undertaking annual PLO assessment with a focus on the Quantitative Reasoning Core Competency. Faculty should freely use and adapt the definitions, criteria, and rubrics as they see fit to meet their program's priorities.

Overview:  What is Quantitative Reasoning, and how does it differ from Mathematics?

The Mathematical Association of America defines Quantitative Literacy (also known as Quantitative Reasoning or Numeracy) as the ability to adequately use elementary mathematical tools to interpret and manipulate quantitative data and ideas that arise in an individual's private, civic, and work life.  

While quantitative reasoning primarily involves interacting with quantitative information, the skill includes more than simple mathematical ability.  For instance, 

  • Wolfe (1993) notes that quantitative reasoning includes skills in measurement and estimation, a sense of scale, basic understanding of probability and statistics, and ease in reasoning with numbers.  
  • Grawe (2011) defines quantitative reasoning as the ability to consider the power and limitations of quantitative evidence in the evaluation, construction, and communication of arguments. 

Elrod (2014) charts the relationship between traditional mathematics and quantitative reasoning, together with example quantitative reasoning outcomes and assessment strategies. 


Faculty may wish to consider how quantitative reasoning applies to the undergraduate majors in which they teach, what specific knowledge and abilities the program expects of its graduates, and how these skills are developed through the curriculum.

There are many approaches to facilitating student development of and assessing quantitative reasoning in a program's curriculum.  Example assignments include student writing, open-ended mathematical problems, computational modeling, article critiques, complex data analysis, mapping, and estimation. Carleton College's Pedagogy in Action site offers an extensive list of assignment examples, sortable by discipline, which illustrate the wide range of possibilities. 

Direct evidence should be assessed in a way that is consistent with the program's expectations for quantitative reasoning. The sample rubrics below may provide a useful starting point. 

Sample Rubrics 


Mathmatical Association of America (MAA) goals

MAA's committee on undergraduate programs in mathematics report "What should students know"


MAA Quantitative Literacy Special Interest Group's extensive list of resources

MAA's report on quantitative literacy in college students

Carleton College's QUIRK initiative site

Elrod, S., (2014). Quantitative Reasoning: The Next "Across the Curriuculum" MovementPeer Review, Summer 2014, 16 (3).


Elrod, S., (2014). Quantitative Reasoning: The Next "Across the Curriuculum" Movement, Peer Review, Summer 2014, 16 (3).  

Wolfe, C. R., (1993). Quantitative Reasoning Across a College Curriculum, College Teaching, 41(1), 3-9.  

Grawe, N. D., (2011). Beyond math skills: Measuring quantitative reasoning in contextNew Directions in Institutional Research (2011)149, 41-52.