Can LLMs Estimate Student Struggles? Human-AI Difficulty Alignment with Proficiency Simulation for Item Difficulty Prediction

This article explores the potential of Large Language Models (LLMs) in predicting the difficulty of educational items by aligning AI assessments with human understanding of student struggles. The research likely investigates how well LLMs can simulate student proficiency and predict item difficulty based on this simulation. The focus on human-AI alignment suggests a concern for the reliability and validity of LLM-based assessments in educational contexts.