, Volume 69, Issue 2, pp 217-234

Analysis of distractor difficulty in multiple-choice items

Rent the article at a discount

Rent now

* Final gross prices may vary according to local VAT.

Get Access

Abstract

Two psychometric models are presented for evaluating the difficulty of the distractors in multiple-choice items. They are based on the criterion of rising distractor selection ratios, which facilitates interpretation of the subject and item parameters. Statistical inferential tools are developed in a Bayesian framework: modal a posteriori estimation by application of an EM algorithm and model evaluation by monitoring posterior predictive replications of the data matrix. An educational example with real data is included to exemplify the application of the models and compare them with the nominal categories model.

This research was supported by the DGI grant BSO2002-01485.
I would like to thank Eric Maris and Vicente Ponsoda for their advice, Juan Botella for providing the data for the empirical application, and three anonymous reviewers for their comments that were essential for improving the quality of the paper.