Program Learning Outcomes

Learning Outcomes for Mathematics Majors

(Developed with reference to the MAA’s 2015 Curriculum Guide to Majors in the Mathematical Sciences.)

  1. Communication: Be able to read, interpret, write about, and talk about mathematics.
  2. Computation: Develop computational, algorithmic, and technological problem-solving fluency.
  3. Abstraction: Be able to work with abstract mathematical structures, and to generalize from the concrete to the abstract.
  4. Disciplinary Citizenship: Develop collaborative skills, independence, perseverance, and experience with open-ended inquiry.

Learning Outcomes for Applied Mathematics Majors

  1. Communication: Be able to read, interpret, write about, and talk about mathematics.
  2. Computation: Develop computational, algorithmic, and technological problem-solving fluency.
  3. Application: Be able to apply mathematical concepts to concrete situations.
  4. Disciplinary Citizenship: Develop collaborative skills, independence, perseverance; have experience with open-ended inquiry.

Additional Learning Outcomes for Mathematics Education BS Majors (ME)
(Adapted from Association of Mathematics Teacher Educators’ 2017 Standards for Preparing Teachers of Mathematics.)

  1. Demonstrate the belief that all people are capable of thinking mathematically and are able to solve sophisticated mathematical problems with effort.
  2. Demonstrate understanding that the social, historical, and institutional contexts of mathematics affect teaching and learning, and show commitment to their critical roles as advocates for each and every student.

Learning Outcomes for Mathematics Minor

Mathematics Major LO’s 1 and 2.

Learning Outcomes for Statistics Minor
(Adapted from the ASA’s 2014 Curriculum Guidelines for Undergraduate Programs in Statistical Science.)

  1. Develop novice-level statistical thinking, particularly with respect to linking appropriate inferences to study design (e.g., correlation does not imply causation).
  2. Demonstrate the ability to appropriately select and use statistical models (e.g., normal distribution, t-distribution, binomial distribution) and statistical methods (e.g., regression, resampling).
  3. Develop facility with one or more professional statistical software programs.
  4. Respond appropriately to issues that may arise when analyzing real data sets and communicating results.

Learning Outcomes for Actuarial Science Minor (AS)
(Developed with reference to the Society of Actuaries’ guidelines for actuarial preparation. Mastery of these learning objectives will prepare a student to begin taking actuarial certification examinations.)

  1. Demonstrate statistical thinking about the concepts of randomness, centrality and variability.
  2. Demonstrate the ability to work with the rules of probability and with basic probability models.
  3. Demonstrate proficiency with single variable calculus.
  4. Demonstrate the ability to apply mathematical concepts to applications in business or economics.

Updated December 2018