Abstract
Targeted double scoring, or, double scoring of only some (but not all) responses, is used to reduce the burden of scoring performance tasks for several mastery tests (Finkelman, Darby, & Nering, 2008). An approach based on statistical decision theory (e.g., Berger, 1989; Ferguson, 1967; Rudner, 2009) is suggested to evaluate and potentially improve upon the existing strategies in targeted double scoring for mastery tests. An application of the approach to data from an operational mastery test shows that a refinement of the currently used strategy would lead to substantial cost savings.
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