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Implementation and Evaluation of Visual Algorithm to Teach Benefit-to-Cost Ratio Analysis

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2016 ASEE Annual Conference & Exposition


New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

June 29, 2016





Conference Session

Engineering Economy Division Technical Session 2

Tagged Division

Engineering Economy

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Paper Authors


Hector E. Medina Liberty University

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Dr. Medina is an Assistant Professor of Mechanical Engineering at Liberty University (Lynchburg, Va.), where also he leads the development of the Mechanical Engineering Program. He obtained a B.Sc. in Engineering from the Colorado School of Mines, and both M.Sc. and Ph.D. in Mechanical and Nuclear Engineering from the Virginia Commonwealth University. Prior to graduate school, he worked in industry and as a high school teacher for several years in his native Venezuela and Aruba. Since 2012, he has published more than a dozen articles in peer-review journals and conference proceedings. Journals include Applied Mechanics Reviews, Polymer, and International Journal of Solids and Structures. He has also presented at both national and international podiums and won presentation awards at ICONE20 and ICONE21.

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Benjamin T. Scoville Liberty University

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Benjamin Scoville is a third year student pursuing a degree in Electrical Engineering at Liberty University. His topics of intrigue are control systems, communication in automated systems, and cyber physical systems (CPS). Engineering education and CPS are his research interests. His other interests include piano, exploring the outdoors, baking, and marine aquaculture.

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In the recent past, we developed a novel, visual, simple algorithm to teach incremental benefit-to-cost ratio (BCR) analysis to first- and second-year engineering students. The impetus behind that endeavor was twofold: (a) BCR analysis is the most used technique for economic analysis and decision making in the public sector, and (b) to accommodate for the visual learning style that dominates in the engineering student demographics. In the present follow-up work, we: (1) carried out statistical analysis to assess the reception and performance of students from two different semesters. Comparison is made versus the traditional incremental technique. Two null hypotheses were tested, Ho1: There is no difference in the true average levels of performance between the visual method and the traditional method; Ho2: There is no difference in the true average degree of acceptance between the two methods. (2) A simple mathematical proof is carried out to show the soundness of the method. The results corroborate, to a high confidence level, that students find the visual algorithm easier to use. Additionally, the data showed that there is no strong evidence to conclude that the performance is different, once a student has voluntarily selected a method.

Medina, H. E., & Scoville, B. T. (2016, June), Implementation and Evaluation of Visual Algorithm to Teach Benefit-to-Cost Ratio Analysis Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.25564

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