Math Modeling taught by Mrs. Burns is a unique and exciting class where we focus on using math to solve real-world problems. Instead of just learning formulas and taking tests, we work on projects and challenges that require us to think critically and collaborate with others. The class focuses on learning how to create mathematical models to simulate situations we might face in everyday life. Throughout the year, we also participate in math competitions like NEML, HiMCM, and MTFC, where we can test our skills in a fun and competitive setting. The class is hands-on and focuses on problem-solving as well as collaboration, making it a beneficial experience that helps us grow as mathematicians.
The Modeling the Future Challenge (MTFC) is an exciting competition where teams create math models to solve real-world problems. It helps students learn about actuarial science, which involves using math and data to assess risks and come up with solutions. In this competition, teams focus on a risk that affects society, create a model to address it, and then work on ways to reduce or manage that risk. For our MTFC project, my team is focused on addressing wrongful convictions in the justice system. This is a serious issue because innocent people are sent to jail, disrupting their lives and families. I am working with Sophie, Lauren, Sharvi and Jasmin on team skib to model the risks involved with wrongful convictions.
For our first math modeling problem, we worked on the Epsilon School project, where we had to figure out the best way to hire new teachers for a school that was expecting more students. The school wanted to know how to distribute the new teachers into different departments based on the subjects the students would be studying. I worked with Lilian and Anika on this project. Our goal was to come up with a fair way to distribute the teachers, and we used math modeling to support our decisions. To do this, we had to start by looking at the current number of students, predict which courses the new students would take, and decide how many teachers were needed for each subject. It was a bit challenging at first because we had to make assumptions and start small, but as we worked through the data and built our solution, it became much more interesting. In the end, we created a presentation to share our findings and explain how we came up with our solution.