This project began with a very simple question: “What if we could identify when a student might be struggling in math — before it's too late?”
As someone deeply interested in both data science and education, I built this tool to explore how machine learning can be used not just for predictions, but to help identify students who may benefit from early support.
The model uses details like a student's reading and writing scores— key indicators of reasoning and comprehension — along with their background and learning environment to predict their math score. But more importantly, it also tells you why the model made that prediction — through a personalized, human-readable explanation.
Whether you're an educator, a parent, or just someone curious about AI, this tool shows how data can help us make smarter, more empathetic decisions in the classroom.