"Wrong" isn't a diagnosis.
When a student answers 32 − 9 = 37, they didn't randomly guess. They subtracted in the wrong direction in the ones column — a specific, named error called a borrow-skip. A tutor that just marks it incorrect and moves on has wasted the most informative signal in the attempt: why the student got it wrong.
NumPath's Phase 2 mistake classifier turns wrong answers into structured MistakeEvent records. Here's how we built it, what we got wrong the first time, and why rule-based classifiers beat a neural network for this job at this stage.
What We Built
Eight rule-based classifiers covering all three of NumPath's Phase 1 skill areas:
