Prediction of item psychometric indices from item characteristics automatically extracted from the stem and option text
by Carmen Garcia, Vicente Ponsoda, Alejandro Sierra
International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL), Vol. 21, No. 2/3, 2011

Abstract: This study has four main parts: first, some of the 31 guidelines proposed by Haladyna et al. (2002) were converted to 39 features that can be automatically extracted from a text file containing the test stem and options. Second, text files of a few multiple choice university exams were collected and the 39 features were extracted. Third, the difficulty and discrimination indices of each item were computed. Finally, linear regression was applied to find which features predict the items' psychometric indices. The number of special adverbs (always, never, …) in the distracters and the discrimination index show the strongest link.

Online publication date: Fri, 20-May-2011

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