AI RESEARCH
Can MLLMs Read Students' Minds? Unpacking Multimodal Error Analysis in Handwritten Math
arXiv CS.AI
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ArXi:2603.24961v1 Announce Type: new Assessing student handwritten scratchwork is crucial for personalized educational feedback but presents unique challenges due to diverse handwriting, complex layouts, and varied problem-solving approaches. Existing educational NLP primarily focuses on textual responses and neglects the complexity and multimodality inherent in authentic handwritten scratchwork.