Program Outcomes and Objectives

Bachelor of Science or Bachelor of Arts in Mathematics

Including Actuarial Track

Program Outcomes   

Upon completion of the B.S./B.A. in Mathematics, students will be able to meet the following program objectives:

1. Find employment utilizing their mathematical knowledge.
2. Use mathematical knowledge to solve problems.
3. Undertake further studies related to mathematics. 

Student Learning Outcomes:

The student learning outcomes listed below will serve as a guide for the assessment of the mathematics major. Students in the major are expected to meet the following outcomes:

1. Conceptual Understanding - Demonstrate conceptual understanding by defining/describing underlying concepts for definitions and/or theorems including by using examples and non-examples.
2. Reasoning and Proof (Adaptive Reasoning) - Formulate and evaluate conjectures with proofs or refutations and critique the reasoning of others.
3. Algorithmic Thinking (Procedural Fluency) - Select appropriate algorithms and tools and apply them accurately to solve problems.
4. Applications (Strategic Competence) - Analyze real-world phenomena by identifying key elements and assumptions, proposing models and/or methods for solving, and correctly interpreting results.
5. Communication - Communicate the results of their work in oral and/or written form effectively.
6. Technology - Use technology appropriately in service of doing mathematics.

Bachelor of Science or Bachelor of Arts in Mathematics Teaching

Program Outcomes   

Upon completion of the B.S./B.A. in Mathematics Teaching, students will be able to meet the following program objectives:

1. Find employment utilizing their mathematical knowledge.
2. Use mathematical knowledge to solve problems.
3. Undertake further studies related to mathematics. 

Student Learning Outcomes:

The student learning outcomes listed below will serve as a guide for the assessment of the mathematics teaching major. Students in the major are expected to meet the following outcomes:

1. Conceptual Understanding - Demonstrate conceptual understanding by defining/describing underlying concepts for definitions and/or theorems including by using examples and non-examples.
2. Reasoning and Proof (Adaptive Reasoning) - Formulate and evaluate conjectures with proofs or refutations and critique the reasoning of others.
3. Algorithmic Thinking (Procedural Fluency) - Select appropriate algorithms and tools and apply them accurately to solve problems.
4. Applications (Strategic Competence) - Analyze real-world phenomena by identifying key elements and assumptions, proposing models and/or methods for solving, and correctly interpreting results.
5. Communication - Communicate the results of their work in oral and/or written form effectively.
6. Technology - Use technology appropriately in service of doing mathematics.

MATT:  Student Learning Outcome -  Students completing the Mathematics Teaching Major should also demonstrate their ability to understand the pedagogical knowledge specific to mathematics teaching and learning in the following areas:

       Use current research and theory in teaching and learning to plan for mathematics instruction and assessment aligned to appropriate learning goals.

Bachelor of Science or Bachelor of Arts in Statistics

Program Outcomes   

 Upon completion of the B.S./B.A. in Statistics, students will be able to meet the following program objectives:

1. Find employment utilizing their statistical knowledge.
2. Use statistical knowledge to identify and solve problems.
3. Undertake graduate studies related to statistics. 

Student Learning Outcomes:

The student learning outcomes listed below will serve as a guide for the assessment of the statistics major. Students in the major are expected to meet the following outcomes:

1. Be able to convert a problem description into testable research hypotheses.
2. Be able to select appropriate statistical tools to investigate a research hypothesis.
3. Be able to apply appropriate statistical methodology and interpret results in a variety of settings.
4. Be able to apply likelihood principles and calculus to derive fundamental results in probability, estimation and hypothesis testing.
5. Be able to select standard experiment designs, with consideration of selection process, data collection, issues of bias, causality and confounding, based on specifications of a scientific study.
6. Be able to write code to extract and reformat real data and to utilize statistical programming environments.
7. Be able to identify limitations to statistical results and avoid misleading quantitative analysis.
8. Be able to effectively present statistical findings to an audience lacking statistical expertise as well as work collaboratively.