Studied calibration designs that maximize the determinants of Fisher's information matrix on the item parameters for sets of polytomously scored items. Analyzed these items using a number of item response theory models. Results show that for the data and models used, a D-optimal calibration design for an answer or set of answers can reduce the number of examinees required to estimate the item parameters to a certain precision. (SLD)