Using Automatic Item Generation to Improve the Quality of MCQ Distractors.

@article{Lai2016UsingAI,
  title={Using Automatic Item Generation to Improve the Quality of MCQ Distractors.},
  author={Hollis Lai and Mark Gierl and Claire Touchie and Debra Pugh and Andre-Philippe Boulais and Andre F De Champlain},
  journal={Teaching and learning in medicine},
  year={2016},
  volume={28 2},
  pages={166-73}
}
UNLABELLED CONSTRUCT: Automatic item generation (AIG) is an alternative method for producing large numbers of test items that integrate cognitive modeling with computer technology to systematically generate multiple-choice questions (MCQs). The purpose of our study is to describe and validate a method of generating plausible but incorrect distractors. Initial applications of AIG demonstrated its effectiveness in producing test items. However, expert review of the initial items identified a key… CONTINUE READING

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