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  1. Programs
  2. Mathematics - BS

Mathematics - BS

Texas A & M University-College Station

Bachelor's DegreeAcademic

Become a contributor for free to openly demonstrate student outcomes, industry alignment & eligibility criteria.

The curriculum in the Bachelor of Science in Mathematics explores mathematical problems and their interplay with science and engineering. Students in this program investigate a broad array of techniques in pure mathematics and pursue electives in science and related fields that demonstrate the crucial underpinnings of mathematics in our understanding of information, science, and technology.

Credits

120 credits

Format

In-Person

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Program Pathways

Credentials this program stacks toward

No program pathways.

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Course Pathway

13 courses in this program

112 courses
PHYS 206
3 credits
OCNG 251
3 credits
MATH 415
3 credits
MATH 409
3 credits
MATH 323
3 credits
MATH 308
3 credits
MATH 300
3 credits
MATH 221
4 credits
MATH 172
4 credits
MATH 170
1 credits
MATH 150
4 credits
CHEM 119
4 credits
21 course
MATH 171
4 credits
Program Requirements

Courses required to complete this program

MATH 171Calculus I
4 cr
MATH 172Calculus II
4 cr
MATH 221Several Variable Calculus
4 cr
MATH 300Foundations of Mathematics
3 cr
MATH 308Differential Equations
3 cr
MATH 323Linear Algebra
3 cr
PHYS 206Newtonian Mechanics for Engineering and Science
3 cr
MATH 409Analysis on the Real Line
3 cr
MATH 415Modern Algebra I
3 cr
CHEM 119Fundamentals of Chemistry I
4 cr
OCNG 251The Blue Planet - Our Oceans
3 cr
MATH 170Freshman Mathematics Laboratory
1 cr
MATH 150Functions, Trigonometry and Linear Systems
4 cr
Program Details

Detailed information about this program

No detailed information available.

Requirements

What you need to earn this credential

No requirements listed.

Financial Aid

Eligible funding programs

No funding information available.

Scholarships

No scholarships listed.

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Locations

Where this program is offered

  • Texas

    Texas

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Related Programs

Programs related to this one

No related programs.

Skills & Competencies

Skills developed through this program

Auto-populated·from O*NET via SOC 25-1022.00

Skills

MathematicsSpeakingInstructingReading ComprehensionActive ListeningCritical ThinkingLearning StrategiesMonitoring

Knowledge

MathematicsEducation and TrainingEnglish LanguageComputers and Electronics

Abilities

Mathematical ReasoningOral ExpressionNumber FacilityOral ComprehensionWritten ComprehensionDeductive ReasoningWritten ExpressionInductive ReasoningSpeech ClarityNear Vision

Tasks

  • Compile, administer, and grade examinations, or assign this work to others.
  • Evaluate and grade students' class work, assignments, and papers.
  • Prepare and deliver lectures to undergraduate or graduate students on topics such as linear algebra,
  • Hire adjunct faculty.

Technology

Computer based training softwareData base user interface and query softwareCalendar and scheduling softwareWord processing softwareAnalytical or scientific software

Tools

Carousel slide projectorsCompact digital camerasCompact disk CD playersComputer data input scannersComputer laser printersConference telephonesDesktop computersDigital calculatorsDigital video camerasDigital video disk DVD playersHandheld microphonesInteractive whiteboard controllersInteractive whiteboardsLaptop computersLaser facsimile machines

Work Values

AchievementIndependenceRecognitionWorking ConditionsRelationshipsSupport
Career Pathways

Occupations this program prepares you for

Auto-populated·from O*NET + BLS
Occupations matched to this program, with median wage, top wage, growth, and openings
SOCOccupationMethodWageGrowthOpenings
Match confidence: medium25-1022.00Mathematical Science Teachers, Postsecondarytitle_inference———
What You'll Learn

Key competencies developed through this program

Auto-populated·from NSX Competency Framework

Mastery: proficient (Level 3)(based on Bachelor's Degree)

  • Graduate and upper-division undergraduate lectures — autonomously design and deliver advanced instruction on topics such as real analysis, abstract algebra, or topology, adapting content to diverse learner backgrounds in a doctoral-granting department.
  • Comprehensive assessment systems — independently develop, administer, and evaluate a full suite of examinations, projects, and written papers that measure both procedural fluency and mathematical reasoning in a postsecondary context.
  • Non-routine student work — assess and provide substantive written feedback on graduate-level proofs, theses chapters, and research expositions, applying expert judgment about mathematical validity and communication quality.
  • Curriculum design and revision — independently lead the planning, evaluation, and revision of course content and instructional methods for a mathematics program sequence, incorporating current disciplinary and pedagogical research.
  • Interdisciplinary course materials — develop innovative syllabi and handouts that integrate computational tools, real-world applications, and primary literature to enhance student engagement and disciplinary depth.
  • Student academic advising — provide sustained mentorship and guidance to undergraduate and graduate students during office hours and advising sessions, supporting degree planning and research development in a university mathematics department.
  • Classroom discourse management — facilitate high-level seminar discussions that require students to construct, critique, and refine mathematical arguments autonomously in graduate-level course environments.
  • Learning strategy differentiation — apply evidence-based instructional approaches to address varied levels of mathematical preparation and learning needs across a heterogeneous student population.
  • Analytical and scientific software integration — incorporate tools such as Mathematica, R, or Python seamlessly into course delivery and assessment to support computational mathematics pedagogy.
  • Systems evaluation — assess the effectiveness of instructional methods and course structures by analyzing student performance trends and implementing data-informed improvements across a full academic year.

Some details on this page are auto-populated from public workforce data sources: O*NET (opens in new tab), BLS (opens in new tab), College Scorecard (opens in new tab), DOL Training Provider Results (opens in new tab), NSX (opens in new tab). Provided in partnership with LER.me Career Intelligence.

Student Outcomes

Performance metrics for this program

Auto-populated·from Scorecard + DOL
Completion Rate
77%
Placement Rate
42%