01843nas a2200169 4500008004100000245012200041210006900163300001200232490000700244520124800251100001201499700001101511700001401522700001101536700001401547856011201561 2012 eng d00aComparison Between Dichotomous and Polytomous Scoring of Innovative Items in a Large-Scale Computerized Adaptive Test0 aComparison Between Dichotomous and Polytomous Scoring of Innovat a493-5090 v723 a
This study explored the impact of partial credit scoring of one type of innovative items (multiple-response items) in a computerized adaptive version of a large-scale licensure pretest and operational test settings. The impacts of partial credit scoring on the estimation of the ability parameters and classification decisions in operational test settings were explored in one real data analysis and two simulation studies when two different polytomous scoring algorithms, automated polytomous scoring and rater-generated polytomous scoring, were applied. For the real data analyses, the ability estimates from dichotomous and polytomous scoring were highly correlated; the classification consistency between different scoring algorithms was nearly perfect. Information distribution changed slightly in the operational item bank. In the two simulation studies comparing each polytomous scoring with dichotomous scoring, the ability estimates resulting from polytomous scoring had slightly higher measurement precision than those resulting from dichotomous scoring. The practical impact related to classification decision was minor because of the extremely small number of items that could be scored polytomously in this current study.
1 aJiao, H1 aLiu, J1 aHaynie, K1 aWoo, A1 aGorham, J uhttp://iacat.org/content/comparison-between-dichotomous-and-polytomous-scoring-innovative-items-large-scale01659nas a2200145 4500008004100000245004900041210004800090260009700138520115900235100001301394700001101407700001401418700001101432856007001443 2009 eng d00aDeveloping item variants: An empirical study0 aDeveloping item variants An empirical study aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aLarge-scale standardized test have been widely used for educational and licensure testing. In computerized adaptive testing (CAT), one of the practical concerns for maintaining large-scale assessments is to ensure adequate numbers of high-quality items that are required for item pool functioning. Developing items at specific difficulty levels and for certain areas of test plans is a wellknown challenge. The purpose of this study was to investigate strategies for varying items that can effectively generate items at targeted difficulty levels and specific test plan areas. Each variant item generation model was developed by decomposing selected source items possessing ideal measurement properties and targeting the desirable content domains. 341 variant items were generated from 72 source items. Data were collected from six pretest periods. Items were calibrated using the Rasch model. Initial results indicate that variant items showed desirable measurement properties. Additionally, compared to an average of approximately 60% of the items passing pretest criteria, an average of 84% of the variant items passed the pretest criteria. 1 aWendt, A1 aKao, S1 aGorham, J1 aWoo, A uhttp://iacat.org/content/developing-item-variants-empirical-study00574nas a2200133 4500008004100000245007700041210006900118260011100187100001000298700001400308700001400322700001100336856009300347 2009 eng d00aLimiting item exposure for target difficulty ranges in a high-stakes CAT0 aLimiting item exposure for target difficulty ranges in a highsta aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing. {PDF File, 1.1 aLi, X1 aBecker, K1 aGorham, J1 aWoo, A uhttp://iacat.org/content/limiting-item-exposure-target-difficulty-ranges-high-stakes-cat