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Testing The “Art” Of Engineering Economic Decision Making

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Conference

2006 Annual Conference & Exposition

Location

Chicago, Illinois

Publication Date

June 18, 2006

Start Date

June 18, 2006

End Date

June 21, 2006

ISSN

2153-5965

Conference Session

Innovation in Teaching Engineering Economics

Tagged Division

Engineering Economy

Page Count

8

Page Numbers

11.1247.1 - 11.1247.8

Permanent URL

https://peer.asee.org/1097

Download Count

100

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Paper Authors

biography

Joseph Hartman Lehigh University

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JOSEPH C. HARTMAN is an Associate Professor in the Department of Industrial and Systems Engineering at Lehigh University, holds the George Kledaras Endowed Chair, and serves as Department Chair. He received his Ph.D. (1996) and M.S. (1994) in Industrial Engineering from the Georgia Institute of Technology and B.S. in General Engineering from the University of Illinois at Urbana-Champaign (1992). His research interests are in economic decisions analysis and dynamic programming. He is an active member of ASEE, IIE, and INFORMS and currently serves as Editor of The Engineering Economist.

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Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Testing the “Art” of Engineering Economic Decision-Making

Abstract

Making an economic decision involves both science and art. The “science” is comprised of the analyses applied in the process, such as discounted cash flow analysis, sensitivity analysis, or breakeven analysis. The “art” involves defining the problem, identifying relevant parameters, synthesizing information, trading off multi-attributes, and considering non-economic influences. While traditional quizzes can test whether students understand the science, testing the art is more difficult. We utilize a single question, open-ended final exam for this purpose. Students are given a problem scenario, data, and supplemental information and merely asked whether a capital investment should be pursued or not. It is expected that they will justify their decision, although there are no requirements as to how. We describe our experiences with this approach, which has been implemented for five years now.

Introduction

Problem-based learning attempts to engage students in the learning process by having students (1) work on problems that are perceived as relevant or meaningful and (2) fill in gaps when presented with a situation that is “incomplete.” Both of these traits are inherent in real problems – data is incomplete, problems are ill-defined, and results are requested without formal paths of inquiry. Establishing relevance with coursework has been shown to be a critical factor in engineering education [2].

As advocates of problem-based learning, we teach Engineering Economy in a decision-making context [3] such that students understand the entire process of making a capital investment decision from defining the problem; to generating solution alternatives; to estimating before and after-tax cash flows; to evaluating options under certainty, risk, time, multiple alternatives, constraints, and multi-attributes; to post-implementation and project tracking. Furthermore, we utilize numerous media sources to generate realistic problems such that students appreciate its application [4,5]. The goal upon completion of the course, as stated on the syllabus, is that a student is able to make, and justify, a capital investment decision.

While traditional mechanisms of evaluation (homework sets, quizzes, and exams) are good for testing a student’s knowledge and skill in the use of formal methodologies, such as discounted cash flow analysis, performing a breakeven analysis, or choosing the minimum cost solution between two mutually exclusive alternatives, they do not necessarily allow for examining other relevant steps in decision-making (problem-solving). In the problem-based learning context, the goal is not relegated to knowing how to apply a methodology (i.e. execute a breakeven analysis). Rather, the goal is that a student understands how to (1) formulate a problem from incomplete data; (2) determine what parameter(s) are critical; (3) identify and execute the correct analysis (i.e. breakeven, project balance, scenario analysis, etc.); and (4) interpret the output from the given analyses. We refer to these skills as being the “art” in engineering economic analysis.

Hartman, J. (2006, June), Testing The “Art” Of Engineering Economic Decision Making Paper presented at 2006 Annual Conference & Exposition, Chicago, Illinois. https://peer.asee.org/1097

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