Optimal Correction for Guessing in Multiple-Choice Tests
Building on Item Response Theory we introduce students٠optimal behavior in multiple-choice tests. Our simulations indicate that the optimal penalty is relatively high, because although correction for guessing discriminates against risk-averse subjects, this effect is small compared with the measurement error that the penalty prevents. This result obtains when knowledge is binary or partial, under different normalizations of the score, when risk aversion is related to knowledge and when there is a pass-fail break point. We also find that the mean degree of difficulty should be close to the mean level of knowledge and that the variance of difficulty should be high.
|Date of creation:||Dec 2007|
|Contact details of provider:|| Postal: Avenida Lehendakari Aguirre, 83, 48015 Bilbao|
Web page: http://www.dfaeii.ehu.es
More information through EDIRC
|Order Information:|| Postal: Dpto. de Fundamentos del Análisis Económico II, = Facultad de CC. Económicas y Empresariales, Universidad del País Vasco, Avda. Lehendakari Aguirre 83, 48015 Bilbao, Spain|
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Maya Bar-Hillel & David Budescu & Yigal Attali, 2005. "Scoring and keying multiple choice tests: A case study in irrationality," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 4(1), pages 3-12, 06.