Stats (Jun 2023)

Guess for Success? Application of a Mixture Model to Test-Wiseness on Multiple-Choice Exams

  • Steven B. Caudill,
  • Franklin G. Mixon

DOI
https://doi.org/10.3390/stats6030046
Journal volume & issue
Vol. 6, no. 3
pp. 734 – 739

Abstract

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The use of large lecture halls in business and economic education often dictates the use of multiple-choice exams to measure student learning. This study asserts that student performance on these types of exams can be viewed as the result of the process of elimination of incorrect answers, rather than the selection of the correct answer. More specifically, how students respond on a multiple-choice test can be broken down into the fractions of questions where no wrong answers can be eliminated (i.e., random guessing), one wrong answer can be eliminated, two wrong answers can be eliminated, and all wrong answers can be eliminated. The results from an empirical model, representing a mixture of binomials in which the probability of a correct choice depends on the number of incorrect choices eliminated, we find, using student performance data from a final exam in principles of microeconomics consisting of 100 multiple choice questions, that the responses to all of the questions on the exam can be characterized by some form of guessing, with more than 26 percent of questions being completed using purely random guessing.

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