The optimal number of options for multiple-choice questions on high-stakes tests: application of a revised index for detecting nonfunctional distractors

Adv Health Sci Educ Theory Pract. 2019 Mar;24(1):141-150. doi: 10.1007/s10459-018-9855-9. Epub 2018 Oct 25.


Research suggests that the three-option format is optimal for multiple choice questions (MCQs). This conclusion is supported by numerous studies showing that most distractors (i.e., incorrect answers) are selected by so few examinees that they are essentially nonfunctional. However, nearly all studies have defined a distractor as nonfunctional if it is selected by fewer than 5% of examinees. A limitation of this definition is that the proportion of examinees available to choose a distractor depends on overall item difficulty. This is especially problematic for mastery tests, which consist of items that most examinees are expected to answer correctly. Based on the traditional definition of nonfunctional, a five-option MCQ answered correctly by greater than 90% of examinees will be constrained to have only one functional distractor. The primary purpose of the present study was to evaluate an index of nonfunctional that is sensitive to item difficulty. A secondary purpose was to extend previous research by studying distractor functionality within the context of professionally-developed credentialing tests. Data were analyzed for 840 MCQs consisting of five options per item. Results based on the traditional definition of nonfunctional were consistent with previous research indicating that most MCQs had one or two functional distractors. In contrast, the newly proposed index indicated that nearly half (47.3%) of all items had three or four functional distractors. Implications for item and test development are discussed.

Keywords: Assessment; High-stakes testing; Item-writing guidelines; Multiple-choice questions; Test development.

MeSH terms

  • Choice Behavior
  • Education, Medical / methods*
  • Education, Medical / standards*
  • Educational Measurement / methods*
  • Educational Measurement / standards*
  • Humans
  • Models, Statistical
  • Psychometrics