Building on Item Response Theory we introduce students’ optimal 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.
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Paper provided by University of the Basque Country - Department of Foundations of Economic Analysis II in its series DFAEII Working Papers with number
200708.
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Find related papers by JEL classification: A20 - General Economics and Teaching - - Economics Education and Teaching of Economics - - - General D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty I2 - Health, Education, and Welfare - - Education
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