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AI InsightThe results show that: (1) KLP, D-optimality, and V1 performed better in recovering domain scores, and all outperformed V2 with respect to precision; (2) although V1 and V2 offer improved item bank usage rates, KLP, D-optimality, V1, and V2 produced an unbalanced distribution of item exposure rates; (3) all exposure control strategies improve the exposure uniformity greatly and with very little loss in psychometric precision; (4) RPG and MPI perform similarly in exposure control, and outperformed RT exposure control method.
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Özet
This study aims to investigate the effect of different item exposure controlling strategies on item selection methods in the context of multidimensional computerized adaptive testing (MCAT). Additionally, this study aims to examine to what extend the restrictive threshold (RT) and the restrictive progressive (RPG) exposure methods suppress the item exposure rates and increase the exposure rates of underexposed items without losing psychometric precision in MCAT. For this purpose, the performance of four item selection methods with and without exposure controls are evaluated and compared so as to determine how results differ when item exposure controlling strategies are applied with Monte-Carlo simulation method. The four item selection methods employed in this study are D-optimality, Kullback–Leibler information (KLP), the minimized error variance of linear combination score with equal weight (V1), the composite score with optimized weight (V2). On the other hand, the maximum priority index (MPI) method proposed for unidimensional CAT and two other item exposure control methods, that are RT and RPG methods proposed for cognitive diagnostic CAT, are adopted. The results show that: (1) KLP, D-optimality, and V1 performed better in recovering domain scores, and all outperformed V2 with respect to precision; (2) although V1 and V2 offer improved item bank usage rates, KLP, D-optimality, V1, and V2 produced an unbalanced distribution of item exposure rates; (3) all exposure control strategies improve the exposure uniformity greatly and with very little loss in psychometric precision; (4) RPG and MPI perform similarly in exposure control, and outperformed RT exposure control method.
Abstract
This study aims to investigate the effect of different item exposure controlling strategies on item selection methods in the context of multidimensional computerized adaptive testing (MCAT). Additionally, this study aims to examine to what extend the restrictive threshold (RT) and the restrictive progressive (RPG) exposure methods suppress the item exposure rates and increase the exposure rates of underexposed items without losing psychometric precision in MCAT. For this purpose, the performance of four item selection methods with and without exposure controls are evaluated and compared so as to determine how results differ when item exposure controlling strategies are applied with Monte-Carlo simulation method. The four item selection methods employed in this study are D-optimality, Kullback–Leibler information (KLP), the minimized error variance of linear combination score with equal weight (V1), the composite score with optimized weight (V2). On the other hand, the maximum priority index (MPI) method proposed for unidimensional CAT and two other item exposure control methods, that are RT and RPG methods proposed for cognitive diagnostic CAT, are adopted. The results show that: (1) KLP, D-optimality, and V1 performed better in recovering domain scores, and all outperformed V2 with respect to precision; (2) although V1 and V2 offer improved item bank usage rates, KLP, D-optimality, V1, and V2 produced an unbalanced distribution of item exposure rates; (3) all exposure control strategies improve the exposure uniformity greatly and with very little loss in psychometric precision; (4) RPG and MPI perform similarly in exposure control, and outperformed RT exposure control method.