# Combining model tracing and constraint-based modeling for multistep strategy diagnoses

arXiv: https://arxiv.org/abs/2507.13652 · HTML: https://mlsanity.com/paper/2507.13652/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 23 references that are in the map.
- First posted on arXiv 18 Jul 2025.

## Builds on (most cited first, 1 of 1)

- [Automated Feedback in Math Education: A Comparative Analysis of LLMs for Open-Ended Responses](https://mlsanity.com/paper/2411.08910/) (2024)

## Abstract (arXiv)

Model tracing and constraint-based modeling are two approaches to diagnose student input in stepwise tasks. Model tracing supports identifying consecutive problem-solving steps taken by a student, whereas constraint-based modeling supports student input diagnosis even when several steps are combined into one step. We propose an approach that merges both paradigms. By defining constraints as properties that a student input has in common with a step of a strategy, it is possible to provide a diagnosis when a student deviates from a strategy even when the student combines several steps. In this study we explore the design of a system for multistep strategy diagnoses, and evaluate these diagnoses. As a proof of concept, we generate diagnoses for an existing dataset containing steps students take when solving quadratic equations (n=2136). To compare with human diagnoses, two teachers coded a random sample of deviations (n=70) and applications of the strategy (n=70). Results show that that the system diagnosis aligned with the teacher coding in all of the 140 student steps.