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Abstract
In computer-based tests (CBT), the ideal distribution of item difficulty reflects the distribution of examinee’s ability, but often tests have a shortage of items toward the harder end of the spectrum. This investigation examines whether existing multiple-choice type items with a known difficulty value could be modified to increase item difficulty in a predictable way. Items from a large item bank were modified by either replacing a distractor (the “nudge” method) or adding a second key to create a new multiple-response type item (a more substantial revision called the “shove” method). Results suggest that the “shove” method was more successful in predictably creating more difficult items.
Karen A. Sutherland, Pearson VUE
John A. Stahl, Pearson VUE
Ada Woo, National Council of State Boards of Nursing