3 papers
cs.CL2026
AI-Enabled Quality Assurance for Multiple-Choice Assessment Items
Steven Moore, Nicholas Diana
Generating multiple-choice questions is increasingly scalable, but establishing their assessment quality remains difficult. We present a focused narrative review of automated item-…
cs.CL2026
BenchMarker: An Education-Inspired Toolkit for Highlighting Flaws in Multiple-Choice Benchmarks
Nishant Balepur, Bhavya Rajasekaran, Jane Oh +7
Multiple-choice question answering (MCQA) is standard in NLP, but benchmarks lack rigorous quality control. We present BenchMarker, an education-inspired toolkit using LLM judges t…
cs.CL2025
The Impact of Item-Writing Flaws on Difficulty and Discrimination in Item Response Theory
Robin Schmucker, Steven Moore
High-quality test items are essential for educational assessments, particularly within Item Response Theory (IRT). Traditional validation methods rely on resource-intensive pilot t…