Improving Conceptual Learning in
Engineering Economy using
Model-Eliciting Activities (MEAs)
KAREN M. BURSIC, LARRY SHUMAN,
MARY BESTERFIELD-SACRE, TUBA PINAR YILDIRIM
UNIVERSITY OF PITTSBURGH
DEPARTMENT OF INDUSTRIAL ENGINEERING
SCHOOL OF EDUCATION
INDUSTRIAL ENGINEERING RESEARCH CONFERENCE
JUNE 7, 2010
What are MEAs?
Model-Eliciting Activities (MEAs) – method for presenting
complex, realistic, open-ended client driven problems.
Originally developed by mathematics education
researchers and now increasingly used in engineering.
Based on six principles: model construction, reality, self-
assessment, model documentation, generalizability, and
E-MEAs – introduce an ethical component into the
problem that students must recognize and address.
Experiment in Engineering Economy
Two sections of the core engineering economy course
taught at Pitt by the same instructor, Fall 2009.
In one section the instructor assigned 3 E-MEAs; the
other section was taught the same material with the
same assignments but no MEAs were introduced.
Does the use of the E-MEAs increase learning of specific
concepts? (Time value of money, cost estimation,
comparing alternative investments, benefit-cost ratios,
consideration of all relevant criteria, economic analysis of
contemporary problems, and dealing with uncertainty)
Secondary goal – improving student attainment of
specific ABET outcomes:
f – “an understanding of professional and ethical
h – “the broad education necessary to understand the impact
of engineering solutions in a global, economic, environmental,
and societal context”
j – “ a knowledge of contemporary issues”
To measure conceptual knowledge, we developed an
“engineering economics concept inventory”.
9 questions, 5 points each
mix of multiple choice and short answer aimed at the specific
engineering economic analysis concepts.
Given to both sections of students at the beginning (pre)
and end (post) of the semester.
Graded by the same graduate student researcher using
the solution key developed by the instructor.
E-MEAs used in Engineering Economy
Title Developed Decision Situation Ethical Dilemma
Which lighting proposal
E-MEA 1: for a college campus is Cost Estimation;
Campus Purdue the least costly and Campus safety concerns vs. Time Value of Money;
Lighting University addresses the campus cost of new lighting Comparing Alternative
Economics community’s safety Investments
Cost Estimation; Time
Value of Money;
E-MEA 2: University Should old trees in parks Destruction of old trees Benefit/Cost Ratios;
Trees and Road of be removed to provide (environmental concerns) Consideration of all
Safety Pittsburgh greater road safety? vs. driver/passenger safety relevant criteria;
Provision of water, job Time Value of Money;
How should a major dam creation , economic stability Benefit/Cost Ratios;
project in Turkey be vs. risks of construction in Uncertainty;
completed given required earthquake prone regions, Consideration of all
and Budget Pittsburgh
budget cuts? environmental concerns, relevant criteria;
and international relations Contemporary
Concept Inventory Scores (45 possible)
Group (E-MEA) Group
Pre Mean 20.38 17.49
Std. Dev. 6.45 5.49
Sample Size 69 47
Post Mean 32.04 30.20
Std. Dev. 5.77 5.26
Sample Size 69 45
Effect Size 1.90 2.36
Teaching evaluation contains questions related to
ABET outcomes (standard across the school).
“…indicate how much has this course improved your
knowledge or skill …”
Scale of 1 to 5 (“not at all” to “a great deal”).
Outcome Comparison group Experimental group
Average (standard average score (standard
deviation); sample size deviation); sample size
f (p<.05) 3.1 (1.11); 59 3.5 (1.13); 40
h (p <.01) 3.39 (1.00); 57 3.97 (.96); 39
j 3.76 (.96); 58 3.95 (1.04); 40
Analysis of student work
Performed well with respect to the direct application
of engineering economic analysis tools.
General models were not always created.
Did not sufficiently determine the economic impacts
of the ethical and other societal issues.
Overall, students recognized that “least-cost” is not
always the best solution!
Use of E-MEAs requires substantial effort on the part of the
To be truly effective, the instructor must provide feedback
and engage the students in a useful discussion.
E-MEAs can be very effective in reinforcing and integrating
E-MEAs are ideally suited as measures of ABET outcomes.
Our experiment demonstrated that E-MEAs are effective for
increasing conceptual learning in an engineering economy
Must be able to further students understanding of
“generalizability” of models.
We are introducing MEAs in probability and statistics 1 and
2, and engineering ethics as well as courses in other
departments in the school, including bio-engineering.
Student “reflective” data is also being collected to measure
life long learning and other benefits of MEAs.
Additional research is focused on the modeling aspects of
This research is supported in part by the National Science Foundation
through DUE 071780: “Collaborative Research: Improving Engineering
Students’ Learning Strategies through Models and Modeling.”
More information at: http://modelsandmodeling.net