Computational Thinking is the process of dissecting complex problems in a manner to generate solutions that are expressed as a series of computational steps in which a computer can perform (Aho, 2012). Typically, this process is separated into four elements: (1) decomposition (the method of dissecting a problem into smaller more manageable tasks), (2) pattern recognition (the method of searching for similarities within problems or solutions), (3) abstraction (the method of synthesizing important information and filtering out irrelevant data while generating a solution), and (4) algorithm design (the method of creating a step-by-step solution to be carried out by a computer program) (BBC, 2018). Computational Thinking also includes knowledge related to (a) the formation of algorithms (including flowcharting), (b) the translation of algorithms using appropriate programming languages, and (c) software design, implementation, and testing. Computational Thinking is important to the practice of Quantitative Analysis as engineering professionals systematically analyze and develop algorithms and programs to develop or optimize solutions to design problems. Furthermore, computational thinking is necessary to develop efficient and automated physical systems as well as visualizations of design concepts and computational scientific models (NRC, 2011).