SMRC: Aligning Large Language Models with Student Reasoning for Mathematical Error Correction
This work formulates student reasoning as a multi-step sequential decision problem and introduces Monte Carlo Tree Search (MCTS) to explore optimal correction paths and proposes a dual evaluation protocol centered on solution accuracy and correct-step retention, offering a comprehensive measure of educational applicability.