Linh Huynh
Author directory2026
Supporting Distractor Quality Review Through Interpretable Semantic and Lexical Diagnostics
Michelle Banawan | Shubham Chakraborty | Katerina Christhilf | Linh Huynh | Tracy Arner | Danielle McNamara
Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers
Michelle Banawan | Shubham Chakraborty | Katerina Christhilf | Linh Huynh | Tracy Arner | Danielle McNamara
Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers
MCQ-Diag is a diagnostic tool for reviewing distractor quality in multiple-choice assessments through three interpretable indicators: semantic plausibility, semantic uniqueness, and lexical distinctiveness. Rather than assigning automated judgments, it presents these as evidence within an interactive review environment. Semantic plausibility and lexical distinctiveness show modest, statistically significant validity against expert ratings.