The online Master of Science in Civil Engineering curriculum provides a rich grounding in theoretical concepts and practical skills. As an R1 research university, MSU offers students exceptional access to industry resources and real-world data, often drawn from the systems that serve the university’s own sprawling campus. Our faculty members teach the quantitative methods and industry-standard software tools that enable professionals to solve vital problems related to pavement and transportation systems.
You’ll work with an academic adviser to determine a customized program plan that fulfills graduation requirements while helping you build the expertise to take on complex engineering projects, qualify for state licensure and progress in your career.
- Master’s students must complete 30 total credit hours (10 courses) to graduate.
- Choose from courses in two specialization areas:
Students may take any selection of 24 credit hours (8 courses) in the areas of Transportation Engineering and Pavement Engineering. We currently offer 5 online courses in each specialization. You may choose to focus primarily on one of these areas or split your coursework between the two.
- In addition, all online civil engineering students are required to take two General Courses that cover the fundamentals in statistical theory and programming in R.
Master of Civil Engineering Course Descriptions
Note: Course availability varies by semester. Contact an admission counselor for details.
General Courses (Required)
Programming in R and use of associated open source tools. Addressing practical issues in documenting workflow, data management and scientific computing.
Transportation Engineering (Choose up to 5)
Driver and vehicle characteristics affecting traffic flow and safety. Speed, density and capacity relationships. Signal control in street networks. Freeway management systems. Risk management and liability.
Geometric design of highways. Operation, capacity, safety and geometric features. Alignment, drainage and pavement design. Use of CAD systems in preparing contract plans.
Application and interpretation of quantitative methods and design of experiments for transportation research. Analysis of variance (ANOVA), non-parametric, discriminant analysis, factor analysis, multivariate regression and SPSS statistical analysis software.
Analysis of highway geometric design alternatives and operational-control strategies with respect to accident probabilities. Statistical methods of pattern identification. Countermeasure selection and evaluation methodology. Risk management.
Advanced highway design policies and practices. Evaluation of operational and safety effects associated with highway design including analytical methods. Traffic control and signalization strategies for highways.
Pavement Engineering (Choose up to 5)
Engineering concepts and information needed to rehabilitate pavements. Network and project survey and evaluation: design of rigid and flexible overlays, other methods of rehabilitation and selection of rehabilitation alternatives. Initial and life cycle cost analysis of various rehabilitation alternatives.
Theoretical models for analysis of concrete pavement systems. Impact of concrete material on pavement response and performance. Formulation of improved mechanistic structural design procedures.
Mechanistic approach to asphalt pavement design. Analysis of asphalt pavement systems using theoretical models, asphalt material modeling, prediction and performance. Formulation of improved mechanistic structural and mix design procedures.
Theoretical and statistical analysis of pavement networks. Engineering monitoring. Determination of distress mechanisms and engineering solutions. Assignment of priorities to engineering actions.
Superpave asphalt mix design, binder tests, hot mix asphalt performance tests, viscoelasticity, continuum damage models and image analysis methods.
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