Teaching BU275 was a valuable experience for me, especially because the course combines quantitative methods with real-world decision making. One of my main goals was to make the mathematical parts of the course less intimidating and help students understand why we use a model before learning how to solve it.

I usually started each class with a short mini-skit or activity connected to the topic of the day. These were often inspired by a story, a song, a humorous situation, or a problem from everyday life. The idea was simple: instead of starting a class with formulas and definitions, I wanted students to first become curious about the problem. Once they understood the story and the question we were trying to answer, we moved to the mathematical model.

Throughout the course, I tried to follow the same approach: start with the big picture, then move to the details. For topics such as decision analysis, simulation, queueing, linear programming, and network models, we first discussed what the problem meant in simple language. Then we identified the decisions, objectives, and limitations before introducing the mathematical formulation.

I also tried to make the classroom interactive. I used questions, discussions, simple examples, and real-life situations to encourage students to think like decision makers rather than simply memorize formulas. One important lesson I learned from teaching this course is that a student may know how to use a formula without fully understanding what it means. For this reason, I increasingly emphasized interpretation: Why is this constraint needed? Why is it an equality rather than an inequality? What does the Solver result actually tell a manager?

Overall, teaching BU275 reinforced an important principle in my teaching: students learn quantitative concepts more effectively when they first understand the story and logic behind the problem. My goal is to let students encounter the problem before they encounter the mathematics, and then use mathematics as a tool to find a better decision.