ISSUES IN EDUCATION

By Mike Racer

As a relative newcomer to the “Business School” (after 15 years in the “Engineering School”) the resistance to OR/MS has been a bit of a surprise to me. Now, six years after the move, I’ve got a little better idea.

First a little background: there are two quantitative courses in our business core – statistics and quantitative methods. Students look forward to getting them “out of the way” and faculty tend to focus on little more than regression analyses.

After a lot of frustration, and a little reflection, it occurred to me that it’s not so much a lack of mathematical skills; the hard task is identification. The students have the capability to do the required math – the question they struggle with is – “Out of all the tools in the toolkit, which one is suitable?”

In our statistics course, we have created a platform that includes the development of a notebook, each section focusing on a particular tool (e.g., binomial, Poisson, normal). The students are required to identify problems related to the semester’s theme that require the specified tool. (Past themes have been: health care, the economic environment, climate change and education.)

This framework has served much more than I’d expected. Students learned about current events. Students discovered the prevalence of numbers in the news. And the students learned how to connect a problem to a tool. Along the way, they griped about having to find a relevant problem. They begged for intervention. They procrastinated. But in the end, they were able to associate the “basic idea” of a tool with a real-world problem.

I’m fairly sure this is not a real surprise to anybody, but it seems to be something to consider as we wrestle with how to make OR/MS relevant in the business school. The real challenges to students involved in problem solving are these:

• Which tool?
• How?
• So what?

Which tool? When presented with, say, a binomial, the student looks for n, p and x and simply solves the problem. When the student doesn’t know it’s a binomial, he struggles. We need to help them recognize the character of the problem. And this is a great learning opportunity for all. One student might perceive a problem as binomial, with successes; another student looks at the same problem and sees events – and selects the Poisson. This is a chance for the student to learn some critical thinking – and accept some of life’s ambiguity.

How? Choosing a tool is a big step for the student, but it’s not over yet. Once the tool has been selected, the student needs to determine the necessary parameters. Where do some of those numbers come from? The quick answer – historical data – leaves the student unsatisfied. Our solution? Hit the pavement. Twice a semester, we have our students out collecting data and formulating problems. Whether it’s Chick-fil-A or a street corner, it’s a real eye-opener to see how that probability of success is calculated for the binomial. (“Aha, 16 out of 20 bought fries; I’ll estimate p=.8!”)

So what? The final step. The student has calculated a solution. They’ve determined the likelihood of a certain number of successes. Now what? What does that tell the student? How can that value be used in decision-making? Here, we have learned to be most relaxed. Our focus is not so much on “getting the right answer” as it is on getting the student to consider the possibilities. “If the solution is small, how will my action differ from if the solution is large?”

One concern I still had was going in the other direction. In the notebook problems, the student had to identify a problem that might require a particular tool. What if the challenge were instead to determine the right tool for a given problem?

In this case, our final has served as the testbed. And our experience has been that the students develop a good sense for this as well.

What Do We Bring to the Table?

I believe that as we move forward we need to realize what OR/MS brings to the table. It’s that fundamental ability to break down a problem into its base definition. I know it shocks many to find out that an OR/MS professional can be as comfortable working on a transportation problem just as much as a ground water modeling problem or a climate change model. This is one of our strengths! We need to share that.

And it’s the process. What are the steps involved in the problem solving? What information is needed? What information is extraneous? How do we proceed to collect the information? We can spell that out.

And, finally, it’s a knack for critical thinking. What are the possible outcomes? What are the possible choices we can make? What if …?
This is what we have to offer, and it is so much in demand.

Aside: One of my big concerns in deciding to do so many projects outside of class was a loss of quantity covered. I was very pleased to learn that many of my students had developed a problem-solving sense that went beyond the material. When I offer extra credit for addressing a tool not covered in class (e.g. comparison of two means), the students tend to do very well in approaching the new problem.

Mike Racer (mracer@memphis.edu) is an associate professor in the Fogelman College of Business & Economics at the University of Memphis.