Quantitative Thinking Designation

Rationale and Requirement

For all courses offered FALL 2014 or later

Rationale

Many policy debates, scientific discussions, political issues, and personal and organizational
decisions involve judgments about claims based upon quantitative evidence. To critically evaluate these claims, the individual must have basic familiarity with such concepts as counting, measurement, estimation, and data analysis. Equally important is the capacity to ask and answer questions in a manner appropriate to these quantitative tools and to understand when the use of quantitative tools is or is not appropriate. The purpose of the QT requirement is to ensure that students have the opportunity to develop such skills. Students should learn approaches to collecting, interpreting, and presenting information about the world based on numerical, logical, and statistical skills. These topics arise in a wide range of areas, and we invite faculty from a range of disciplines to teach courses that contribute to QT.

Requirement

Students may take one or more courses with a Q3, Q2, or Q1 designation. A single Q3 course completely satisfies the requirement; alternatively, a Q2 course together with any other Q2 or Q1 course or three Q1 courses, can meet the requirement.

Q1 Fulfills the Quantitative Description goal, plus 1-2 other learning goals.

Q2 Fulfills the Quantitative Description goal, plus 3-4 other learning goals.

Q3 Fulfills the Quantitative Description goal, plus 5- 6 other learning goals.

Request for a Quantitative Thinking Designation for courses offered FALL 2014 or later

If you have questions, please contact Timothy Traffie, Registrar.

Section 1.



(e.g. 105 or 320)





Section 2.

All Quantitative Thinking designated courses must enable students to accomplish the two learning outcomes associated with the requirement’s Quantitative Description goal. The two Quantitative Description learning outcomes are:

  • Describe objects and/or events quantitatively in terms of their number, probability, proportion, frequency of occurrence, price volume, weight, etc.;
  • Use basic skills such as arithmetic, algebra, geometry, statistics and/or logic to examine the relationships between variables.

Provide a brief description of how your course will emphasize these two student learning outcomes. Refer to course content, pedagogy, materials, activities, etc., as needed.

In addition to the Quantitative Description goal, courses can also promote other Quantitative Thinking learning goals, including Visualization, Quality of Data, Association and Causation, Trade-Offs, Uncertainty, and Estimation and Scale.

Check the box of each Quantitative Thinking goal that will be addressed by your course. (NOTE: Both student learning outcomes under a learning goal must be addressed for GERC to consider the learning goal as advanced by the course.)

 A. Visualization:

1. Interpret common visual presentations of data (e.g., graphs, charts, maps) accurately and critically
2. Create clear and accurate visual depictions of data

Provide a brief description of how your course will emphasize these two student learning outcomes. Refer to course content, pedagogy, materials, activities, etc., as needed.

 B. Quality of data:

1. Locate or create data appropriate to the question being addressed
2. Describe potential limits to a research study’s validity based either on how well the sample represents the total population (i.e., recognizing potential sources of biases and/or error within a data collection process) or on the fit between the study’s variables and the phenomena it seeks to illuminate (i.e., construct validity)

Provide a brief description of how your course will emphasize these two student learning outcomes. Refer to course content, pedagogy, materials, activities, etc., as needed.

 C. Association and causation:

1. Know the different ways that factors identified in research findings can be linked (e.g., correlation, causation)
2. Critically assess the strengths and limitations of research findings involving linkages between factors (e.g., identify cases where correlations might not provide evidence of causality due to “lurking” or confounding variables)

Provide a brief description of how your course will emphasize these two student learning outcomes. Refer to course content, pedagogy, materials, activities, etc., as needed.

 D. Trade-offs:

1. Apply techniques to quantify the trade-offs associated with phenomena such as time life expectancy, money, risk, scientific measurement, or environmental quality
2. Demonstrate knowledge of the strengths and limitations of trade-off quantification as a tool for decision-making

Provide a brief description of how your course will emphasize these two student learning outcomes. Refer to course content, pedagogy, materials, activities, etc., as needed.

 E. Uncertainty:

1. Generate and apply probabilistic information to decision-making
2. Explain the limits of probabilistic information

Provide a brief description of how your course will emphasize these two student learning outcomes. Refer to course content, pedagogy, materials, activities, etc., as needed.

 F. Estimation and scale:

1. Use scale to place quantities in context
2. Generate reasonable rough estimates based on readily available data

Provide a brief description of how your course will emphasize these two student learning outcomes. Refer to course content, pedagogy, materials, activities, etc., as needed.

Submit Form

A copy of this proposal will be sent to your e-mail address when you click the “Submit” button.

You will be notified of the outcome of your application and the Q-level assigned, by either the Registrar or a member of the General Education Requirements Committee (GERC).