A Signal Detection Model for Multiple-Choice Exams.

ABSTRACT: A model for multiple-choice exams is developed from a signal-detection perspective. A correct alternative in a multiple-choice exam can be viewed as being a signal embedded in noise (incorrect alternatives). Examinees are assumed to have perceptions of the plausibility of each alternative, and the decision process is to choose the most plausible alternative. It is also assumed that each examinee either knows or does not know each item. These assumptions together lead to a signal detection choice model for multiple-choice exams. The model can be viewed, statistically, as a mixture extension, with random mixing, of the traditional choice model, or similarly, as a grade-of-membership extension. A version of the model with extreme value distributions is developed, in which case the mode

SUBMITTER: DeCarlo LT 

PROVIDER: S-EPMC8381693 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature