Our math class mainly involves modeling real-world problems. We have tackled many major modeling problems, including participating in HiMCM and Modeling the Future Challenge (MTFC). For our HiMCM, we were given 50 hours to solve a modeling problem about one of two choices. While I am not allowed to release my solution right now, I plan to in the future. For MTFC, we initially participated in the first round, where we responded to questions about a hypothetical scenario and designed our modeling problem based on real-world data. Now that we have qualified as semi-finals, we will move forward on solving our own problem. To prepare for these competitions, we tackled many modeling problems in class, and one of my favorites was about modeling how an increased school population would increase the need for teachers. Below is the initial problem and how we tackled it with our solution. Additionally below is our group’s initial MTFC work.
Epsilon School was a hypothetical school scenario where the school was looking to expand its class sizes, and we had to determine where it was fit to hire teachers to deal with this incoming student population. We were limited to a certain number of teachers and had to work around this while determining where it was fair to hire teachers. We ended up using the fact that we could hire particular teachers for certain subjects. Through this, we found that we could also cut a teacher; however, we decided that that would be quite unfair.
Our MTFC Project focuses on understanding the correlation between mental health and aggressive attacks on schools, with the goal of mitigating these incidents. We have identified a dataset containing detailed information on school attacks and are currently integrating it with mental health data to uncover potential patterns and contributing factors. By analyzing this relationship, we aim to develop evidence-based strategies to reduce the risk and impact of violent attacks on schools, ultimately creating safer and more supportive school environments.