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Structure-Aware Modeling of Multiple-Choice Questions Improves Automatic Difficulty Estimation
arXiv:2606.08988v1 Announce Type: new Abstract: Automatic Question Difficulty Estimation (AQDE) holds growing promise for educational assessment because it has the potential to yield difficulty estimates that are competitive with expert judgment, while helping reduce the time and financial burden associated with pilot administrations and scaling to digital testing contexts. Prior AQDE studies report mixed evidence on whether adding distractors as additional text to the question stem and the...