Quantitative Literacy

@ StanState

Our charge
Students entering college broadly show poor preparedness in quantitative knowledge, skills, and reasoning (Grawe, 2012; Nilson, 2010). On our campus, typically around half of incoming freshmen are deemed "not proficient in mathematics".

 We began the development of a Quantitative Reasoning Faculty Learning Community (QR-FLC) in Fall, 2013. This Faculty Learning Community was designed to explore broad issues related to the development of campus-wide approaches to assessing student quantitative reasoning capabilities, and, more importantly, to developing curricular approaches aimed at helping students improve their quantitative reasoning capabilities throughout their undergraduate experiences.

 By combining attention to definitions, curriculum development and assessment into one comprehensive learning community project, and engaging in this work alongside other campus projects aimed at reforming General Education and developing baccalaureate learning outcomes, we believe we have an opportunity to significantly transform our academic program as it relates to quantitative reasoning.

Critical Areas
Move the cursor over an icon to see the definition of each of these critical areas
Approximation / estimation
Mathematical models
 Tables and graphs
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Pedagogical Materials
Rain - Quantitative Reasoning in a Literature Class (Link) Is it viable to have students engage in quantitative reasoning in a foreign language literature class?  Besides the mathematical practice gained, can this activity also open the door for students to consider that bridging disciplines can broaden the  possibilities offered by a text while helping us avoid falling into cultural one-sidedness?
Estimation (Link) This exercise was meant to develop a class estimate of the amount of radioactive material which was given to Alexander Litvinenko, a Russian dissident living in exile in London. All the required physics has been covered already in class, after which there are two remaining problems
Sources of Energy (Link) From an accompanying diagram which shows the different means by which electricity in the US is generated, students are asked to evaluate the consequences of eliminating either nuclear or coal power stations from the nation's energy generation. Given as an in class assignment, August 24 2017
Double radioactive decay (Link) From a diagram containing two decay curves corresponding to two different isotopes students determine relative populations at different times. Assignment does not require algebra, but instead uses graphical representation of data
Astronauts and solar radiation (Link) Students analyze an excerpt from an article in a local newspaper, and judge its veracity.
Understanding functions (Link) Some examples of questions where students have to answer questions based on the algebraic relationships between variables without being able to substitute numbers
The Power of Community (Link) How Cuba Survived Peak Oil †By tracking their food consumption students were asked to estimate the gallons of water needed to produce the food they consumed in a typical day.
Quantitative Literacy (QL) (also known as Quantitative Reasoning (QR) is a "quantitative habit of mind", proficiency, and comfort in dealing with and rationally processing numerical data. Individuals with strong QL skills possess the ability to analyze quantitative problems in everyday life situations using logical reasoning steps. They are able to read and understand numerical data. They can create valid arguments based on quantitative evidence and know how to interpret their conclusions. They are capable of clearly communicating their analyses and arguments in a variety of formats (including words, tables, graphs, mathematical equations and models, as appropriate).
Expanded definition
The formal definition of Quantitative Literacy implies competency in different fields of basic mathematics, and their application to diverse problems in the sciences, business and administration, politics, economics, and in everyday life. Most importantly, QL requires an understanding of the mathematics that is deeper than mere memorization of, and facility with, calculation procedures. Possession of strong QL skills requires competency in critical areas:
  • Approximation / estimation
  • Mathematical models
  • Tables and graphs
  • Algebra
  • Geometry
  • Statistics
Grading Rubrics
Grading rubrics have been developed for the overall goal of Quantitative Literacy and four each of the critical areas
Overall Quantitative Literacy
Logical Quantitative Reasoning and Analysis
Validity, applicability, and limitations of quantitative arguments
Critical Areas
Approximation / estimation
Mathematical models
 Tables and graphs

Note: links open in a new tab

"Quantitative Reasoning and / or Quantitative Literacy", CSU Stanislaus Quantitative Reasoning Working Group San Jose Meeting, April 22, 2016 (Longer version)

About us

The Quantitative Literacy Group at Stan State is open to all faculty members, staff and students. The current members include:
  • Dr. Tom Carter, Computer Science
  • Dr. Koni Stone, Chemistry
  • Dr. JungHa An, Mathematics
  • Dr. Melanie Martin, Computer Science and Mathematics
  • Dr. Sandra Garcia Sanborn, Philosophy and Modern Languages
  • Dr. Ian Littlewood, Physics
  • Dr. Chris Nagel, Philosophy and Modern Languages
  • Dr. Augustine Avwunudiogba, Geography