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Mathematics Teaching BS

College of Sciences / Mathematics and Statistics
Undergraduate major / Bachelor of Science

About The Program

Program accreditation

Metro State’s program to earn a mathematics degree to become a teacher is accredited by the Minnesota Professional Education and Licensing Standards Board (PELSB) to meet the content standards associated with teaching licensure in this subject area.

Mathematics teaching degree candidates gain a solid foundation in the areas of statistics, calculus, analysis, geometry, modeling, and abstract algebra. Several teaching methods courses give prospective teachers the tools to transmit that knowledge and serve the diverse needs of a classroom in an urban setting.

Student outcomes

Students seeking a degree to become a math teacher will acquire: 

  • The content knowledge in mathematics at a level suitable for teaching at grade 5–12 level. 
  • The ability to teach mathematics in grade 5–12 classrooms by using updated pedagogy and best practices. 
  • Appreciate the role of mathematics and statistics in the modern world, and will be role models of logical reasoning and data-based thinking in and outside the classroom. 

How to enroll

Current students: Declare this program

Once you’re admitted as an undergraduate student and have met any further admission requirements your chosen program may have, you may declare a major or declare an optional minor.

Future students: Apply now

Apply to Metropolitan State: Start the journey toward your Mathematics Teaching BS now. Learn about the steps to enroll or, if you have questions about what Metropolitan State can offer you, request information, visit campus or chat with an admissions counselor.

Get started on your Mathematics Teaching BS

Program eligibility requirements

Students interested in pursuing the Mathematics for Teaching BS should take the following steps:

(1) Speak with a faculty member in the Mathematics & Statistics Department or contact the Chair of the department ( to learn more about the Mathematics for Teaching, B.S. as well as other programs in the department to determine which program best aligns with your interests.

(2) Complete the following Premajor Requirements:

  • Take the following prerequisite courses: STAT 201 Statistics I, MATH 210 Calculus I, and MATH 211 Calculus II.
  • Earn grades of C- or higher and a cumulative GPA of 2.5 or higher in the above prerequisite courses.

(3) Declare the Mathematics for Teaching, B.S. using the online Undergraduate Program Change or Declaration eForm.

Transfer coursework equivalency is determined by the Mathematics and Statistics Department.

Courses and Requirements


In order to declare the Mathematics Teaching BS, grades C- or higher and a cumulative GPA of 2.5 or higher in MATH 210, MATH 211, and STAT 201 are required. Students must complete a minimum of 20 credits in the program at Metropolitan State University.

Student licensure

Completing the Mathematics Teaching major designed to meet state content standards for teachers is only part of the preparation for teaching this subject area effectively to middle school or high school youth. To earn a Tier 3 Mathematics license (grades 5-12) to teach in Minnesota, among other requirements you must also meet state pedagogy standards by completing additional coursework in urban secondary education and student teaching at either the undergraduate or graduate level through the university's Urban Teacher Program in the School of Urban Education.

Please note that the School of Urban Education has the responsibility for recommending students for licensure once they have met all state licensure requirements. For information about Urban Teacher Program admission requirements as well as urban secondary education coursework and student teaching required for licensure, please visit the Secondary Education Licensure page or contact the School of Urban Education at

Major Requirements

+ Premajor Foundation (12 credits)

This course covers the basic principles and methods of statistics. It emphasizes techniques and applications in real-world problem solving and decision making. Topics include frequency distributions, measures of location and variation, probability, sampling, design of experiments, sampling distributions, interval estimation, hypothesis testing, correlation and regression.

Full course description for Statistics I

Since its beginnings, calculus has demonstrated itself to be one of humankind's greatest intellectual achievements. This versatile subject has proven useful in solving problems ranging from physics and astronomy to biology and social science. Through a conceptual and theoretical framework this course covers topics in differential calculus including limits, derivatives, derivatives of transcendental functions, applications of differentiation, L'Hopital's rule, implicit differentiation, and related rates.

Full course description for Calculus I

This is a continuation of MATH 210 Calculus I and a working knowledge of that material is expected. Through a conceptual and theoretical framework this course covers the definite integral, the fundamental theorem of calculus, applications of integration, numerical methods for evaluating integrals, techniques of integration and series.

Full course description for Calculus II

+ Core (28 credits)

Mathematical modeling is the process of using mathematics and computational tools to gain insights into complex problems arising in the sciences, business, industry, and society. Mathematical modeling is an iterative process which involves a computational approach to the scientific method. Assumptions are established, a mathematical structure consistent with those assumptions is developed, hypotheses are produced and tested against empirical evidence, and then the model is refined accordingly. The quality of these models is examined as part of the verification process, and the entire cycle repeats as improvements and adjustments to the model are made. This course provides an introduction to both the mathematical modeling process as well as deterministic and stochastic methods that are commonly employed to investigate time-dependent phenomena.

Full course description for Introduction to Mathematical Modeling

This is an introductory course in real analysis. Starting with a rigorous look at the laws of logic and how these laws are used in structuring mathematical arguments, this course develops the topological structure of real numbers. Topics include limits, sequences, series and continuity. The main goal of the course is to teach students how to read and write mathematical proofs.

Full course description for Introduction to Analysis

Optimization covers a broad range of problems that share a common goal - determining the values for the decision variables in a problem that will maximize (or minimize) some objective function while satisfying various constraints. Using a mathematical modeling approach, this course introduces mathematical programming techniques and concepts such as linear programming, sensitivity analysis, network modeling, integer linear programming, goal programming, and multiple criteria optimization. Software is used to solve real-world problems with an emphasis on interpretability of results. Applications include determining product mix, routing and logistics, and financial planning.

Full course description for Optimization

This course goes beyond the Euclidean Geometry typically taught in high schools. This is a modern approach to geometry based on the systematic use of transformations. It includes a study of some advanced concepts from Euclidean Geometry and then proceeds to examine a wide variety of other geometries, including Non-Euclidean and Projective Geometry. A working knowledge of vectors, matrices, and multivariable calculus is assumed.

Full course description for Modern Geometry