Skip to Main Content Skip to Footer
Home
Toggle Navigation Menu menu

Quantitative Reasoning Evaluation Rubric

Courses with QR designation address all of the learning outcomes.

Learning Outcome Unsatisfactory Satisfactory Exemplary
Frame contextual questions using mathematical representation. Example fails to provide a contextual question, or fails to use recognized mathematical representations to translate the relevant question. Example uses recognized mathematical representations to translate contextual questions. Example uses recognized mathematical representations to pose questions (student generated) that are relevant and unambiguous.
Apply models to deduce consequences or make predictions. Model is unclear or absent, or no clear conclusions or predictions are articulated. Example indicates a model, and the model is applied to make conclusions, however some of the terms or supporting work are absent. All of the terms are clearly defined, the supporting work is evident, and the model is applied appropriately to make conclusions.
Communicate quantitative arguments using clear prose. Example fails to coherently convey a complete argument. Example adequately conveys a verbal interpretation of a mathematical argument. The example suffers from minor omissions or errors. Example completely and clearly conveys a verbal interpretation of a mathematical argument.
Critique quantitative arguments with respect to assumptions, constraints, and logical coherence. Example acknowledges neither the appropriate assumptions and constraints of the model, nor the strengths and weaknesses of the argument. Example considers the appropriate assumptions and constraints of the model, or the strengths and weaknesses of the argument, but not both. Exemplar considers the appropriate assumptions and constraints of the model, and the strengths and weaknesses of the argument.