Human-in-the-Loop LLM Grading for Handwritten Mathematics Assessments
The study developed a scalable workflow to use GPT-5.1 for grading short, handwritten mathematics assessments by combining automated scanning, multi-pass LLM scoring, and mandatory human verification. This method reduced grading time by about 23% while maintaining accuracy comparable to manual grading, proving LLMs can stabilize assessment decisions.