A Case-Based Reasoning Approach to Automating the Construction of Multiple Choice Questions

  • David McSherry
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6176)

Abstract

Automating the construction of multiple-choice questions (MCQs) is a challenge that has attracted the interest of artificial intelligence researchers for many years. We present a case-based reasoning (CBR) approach to this problem in which MCQs are automatically generated from cases describing events or experiences of interest (e.g., historical events, movie releases, sports events) in a given domain. Measures of interestingness and similarity are used in our approach to guide the retrieval of cases and case features from which questions, distractors, and hints for the user are generated in natural language. We also highlight a potential problem that may occur when similarity is used to select distractors for the correct answer in certain types of MCQ. Finally, we demonstrate and evaluate our approach in an intelligent system for automating the design of MCQ quizzes called AutoMCQ.

Keywords

case-based reasoning retrieval similarity multiple-choice questions natural language generation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • David McSherry
    • 1
  1. 1.School of Computing and Information EngineeringUniversity of UlsterColeraineNorthern Ireland

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