Virtual Conference
July 26, 2021
July 26, 2021
July 19, 2022
Engineering Economy
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10.18260/1-2--36853
https://peer.asee.org/36853
307
Associate Professor and Undergraduate Program Director for Industrial Engineering at the University of Pittsburgh. She received her B.S., M.S., and Ph.D. degrees in Industrial Engineering from the University of Pittsburgh. Prior to joining the department she worked as a Senior Consultant for Ernst and Young and as an Industrial Engineer for General Motors Corporation. She teaches undergraduate courses in engineering economics, engineering management, and probability and statistics in Industrial Engineering as well as engineering computing in the freshman engineering program. Dr. Bursic’s recent research has focused on improving Engineering Education and she has 20 years’ experience and over 20 publications in this area. She has also done research and published work in the areas of Engineering and Project Management. She is a senior member of the Institute of Industrial Engineers and the American Society for Engineering Education (where she has served as the Chair of the Engineering Economy Division) and a registered Professional Engineer in the state of Pennsylvania.
Instructional Environment: The course is offered by an Industrial Engineering department at a large public university. It is required for all Industrial (IE) as well as Civil Engineering (CE) students and is generally taken in the sophomore year though not always. It is also taken as an elective by the other engineering disciplines in the school in either the sophomore, junior, or senior year. Each section typically has 70-80 students enrolled. 3 sections are offered per academic year.
Delivery Method: The course is delivered in a computer classroom and meets for two 1 hour and 15 minute sessions per week (a traditional 3 credit course). During COVID restrictions, the course delivery was forced to change to remote delivery then a hybrid approach.
Approach to Instruction and Technology: The instructor uses a mix of short lectures, in class group problem solving, as well as Tophat (“clicker”) quizzes and participation questions. Students are taught 3 methods for solving basic time value of money problems – hand/formula calculations, hand/table calculations, and using the Excel functions. More advanced problem solving is done on Excel.
Topics Covered: Making Economic Decisions; Cost Estimating and Basics of Accounting; The Time Value of Money; Evaluating & Comparing Projects using Equivalent Worth and Using Rate of Return; Benefit Cost Ratio Method & Analysis of Public Projects; Dealing with Uncertainty (Breakeven, Sensitivity Analysis); Depreciation & Income Taxes; and Replacement Analysis.
Assessment: 2 exams with formulas and tables provided; quizzes via Tophat with formulas provided as needed; homework and in class problems. Homework assignments have been a mix of paper and pencil as well as algorithmic problems provided by the book publisher and done on line. The instructor is currently experimenting with open book and notes exams.
Rationale for the approach: The course has always been taught to provide students with practical applications (as opposed to a theoretical background) of concepts so that they can answer business driven questions regarding their engineering projects. That is, which alternative is the least costly? Which alternative is the most profitable? Does the investment have a high ROI? And so forth. Since IEs generally do not take the FE exam, FE style questions are not emphasized although the types of problems students might encounter on the exam are briefly discussed for the benefit of the CE students.
Lessons Learned: It’s more effective to teach the basic concepts well and with a degree of depth rather than surface cover too many concepts in this course. In the “real world” students will use spreadsheets for the bulk of the economic analysis they’ll do. So while a fundamental understanding of the mathematics behind an economic analysis is critical, teaching spreadsheets is necessary and the computer classroom aids in this. However, the use of lectures, computers in the classroom, active learning, Tophat, algorithmic problems solving with the textbook (which is driven by Canvas), the occasional video lesson, Blackboard, and more…is too much! A more streamlined repetitive approach to each topic should be adopted.
Bursic, K. M. (2021, July), Course Strategy: A Little Bit of Everything is Probably Too Much Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--36853
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