A comparison of multi-stage and computerized adaptive tests based on the generalized partial credit model
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A multi-stage test (MST) design is an alternative design for the delivery of automated tests. While computerized adaptive tests (CAT) have dominated testing for the past three decades, increasing interest has been focused on the MST because it offers two advantages that CAT does not: Test sponsors and test developers can see an entire test before administration because it is pre-constructed from sets of modules of test items, and within a module examinees may skip forward and back through test items and make changes to previously answered items. Due to the dominance of CAT, little research has been devoted to differing MST designs with regard to the number of items per stage and routing rules that direct the selection of the next module after a previous module has been completed. This research used simulated response data for a large national test and the generalized partial credit model to compare a CAT to one of three MST designs that had either decreasing numbers of items per stage, increasing number of items per stage, or the same number of items per stage, and one of three routing rules, maximum information, fixed [theta], or number-right routing. As anticipated, CAT had the best performance with respect to estimating proficiency and item pool use. Among the MSTs, the MST with increasing numbers of items per stage performed the best with respect to estimating proficiency, followed by the MST with decreasing number of items per stage, and equal numbers of items per stage. By routing rule, maximum information performed the best and number-right routing performed the worst. Only one panel was constructed per MST design, so only limited comparisons of item pool use could be made. Although the MST designs did not perform as well as CAT, the differences in estimating proficiency were not large, implying that the MST design is a viable alternative to CAT.