The Science of Better Podcast … or how to trick your students into learning about O.R.

By Theresa Roeder

My first O.R. class was old-school. In assignments and quizzes, we demonstrated our algorithmic and arithmetic prowess in classic techniques and heuristics such as the Hungarian Method or the Modified Simplex Algorithm. It was great. I went from “What is this operations research thing and why do I have to take it?” to my O.R. course being the only thing that kept me going through a bleary semester of business classes. I got to do the math I loved but with applications, rather than just flinging abstract theorems around. I took all the O.R. classes I could, and eventually found myself with a Ph.D. because I was just having too much fun to stop doing it. Seriously – where else do you have a field that tries to be as efficient as possible about being efficient?

Fast-forward a decade or so. The core business operations class we teach here is not so old-school anymore. We focus on the fundamental concepts (“What is inventory management and why should I care?”) and introduce basic models with a formula or two. Any solutions more complex than that involve a computer, which I think is appropriate. I can get myself pretty enthused about teaching most O.R. topics, especially without having to try to explain involved numeric manipulations.

My students, on the other hand, are less easily excitable about such things. In their defense, most of them, unlike me at their educational stage, have a lot on their plates. We are a commuter campus where almost half the students are the first in their families to attend college. They typically have at least one job to put themselves through school, and many of them are caring for children or other relatives. They often do not have the bandwidth to do much more than muddle through, and I must seem slightly deranged to some of them, excitedly chattering on about critical paths. Besides which, we use a suspiciously large amount of “math” and even Excel – scary stuff of limited value. I had one student write on a final exam that she thought the course material was pointless, and she would never use it in the future because she would “choose” not to on the job.

Nonetheless, the course is required, and students must earn at least a C-. Despite the general lack of enthusiasm on the part of students, I need to convey some of what I think is O.R.’s near-universal applicability. In addition, we would love to get our students more comfortable with quantitative reasoning and math.

Because practice makes perfect, but many students will not do anything that does not directly contribute to their final grade, I give them extra credit opportunities. Students receive extra credit for in-class exercises, for extra problems I may assign and for online quizzes after each lecture. This works to actively work on problems in class and to get students to practice more. They can also earn up to 20 points of extra credit for the final exam by listening to “The Science of Better” podcast episodes on the INFORMS website ( and writing a half-page summary (1 point per podcast). I curve their final grades both with and without extra credit, assigning the higher of the two grades, so students are not penalized for not doing what is “extra.”

I did an informal data analysis on the last two semesters’ worth of students. Excluding those who withdrew or otherwise dropped out, n = 204, with all four class averages around a C. Eighty-two distinct students submitted at least one podcast write up. In all, 807 were submitted. The average number of podcasts per person submitted was 9.8. Students receiving grades of A, B+, D and F all averaged in the double digits for submissions. Better students did more non-podcast extra credit (i.e., got more practice solving problems). Combining podcast and non-podcast extra credit, they also earn more points than poorer students, though the difference is not as dramatic as without. Twenty-one students passed the course by doing extra credit (i.e., earned less than a C- on the curve excluding extra credit), while 47 students did not.

The largest number of total extra credit points earned over the two semesters was 58.83, while the average was 26.89. (A midterm exam is worth 100 points.) By and large, students are engaging with the material, and a good number of podcasts have been listened to.

Anecdotally, the podcasts impacted how at least a few students viewed O.R. One student wrote, “As a marketing major with an interest in social marketing data mining, the mining for gold podcast was very insightful! Listening to these podcasts have transformed into [sic] a task to be done each day, to something I really look forward to. Thanks professor!” Another student (who did not pass the class) told me that she reluctantly started listening to the podcasts at first but ended up finding them very interesting.

I feel strongly that we need to try to engage our students, especially in required courses. The Science of Better podcast has given me a way to “trick” students into learning about O.R. (and even find it interesting, despite themselves!), while also giving them the opportunity to build a “buffer” of points for the final exam to relieve the pressure. I am extremely grateful to INFORMS for providing this resource!

Theresa Roeder ( is an assistant professor in the Department of Decision Sciences at San Francisco State University.