Multiple Choice Question Corpus Analysis for Distractor Characterization

• Main Authors: Pho, Van-Minh, Andre, T., Ligozat, Anne-Laure, Grau, Brigitte, Illouz, Gabriel, François, Thomas
• Other Authors: Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur (LIMSI), Université Paris-Sud - Paris 11 (UP11)-Sorbonne Université - UFR d'Ingénierie (UFR 919), Sorbonne Université (SU)-Sorbonne Université (SU)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université Paris Saclay (COmUE)
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2014
• Subjects: MCQ; corpus analysis; syntactic and semantic homogeneity; [INFO]Computer Science [cs]; [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; Iceland
• Online Access: https://hal.science/hal-02282009; https://hal.science/hal-02282009/document; https://hal.science/hal-02282009/file/Sami-lrec2014.pdf

International audience In this paper, we present a study of MCQ aiming to define criteria in order to automatically select distractors. We are aiming to show that distractor editing follows rules like syntactic and semantic homogeneity according to associated answer, and the possibility to automatically identify this homogeneity. Manual analysis shows that homogeneity rule is respected to edit distractors and automatic analysis shows the possibility to reproduce these criteria. These ones can be used in future works to automatically select distractors, with the combination of other criteria.