An operational multistage adaptive test (MST) requires the development of a large item bank and the effort to continuously replenish the item bank due to concerns about test security and validity over the long term. New items should be pretested and linked to the item bank before being used operationally. The linking item volume fluctuations in…

Multidimensional forced-choice (FC) questionnaires have been consistently found to reduce the effects of socially desirable responding and faking in noncognitive assessments. Although FC has been considered problematic for providing ipsative scores under the classical test theory, item response theory (IRT) models enable the estimation of…

Measurement errors attributable to cultural issues are complex and challenging for educational assessments. We need assessment tests sensitive to the cultural heterogeneity of populations, and psychometric methods appropriate to address fairness and equity concerns. Built on the research of culturally responsive assessment, this dissertation…

Purpose: This study introduces a framework to produce very short versions of the MacArthur-Bates Communicative Development Inventories (CDIs) by combining the Bayesian-inspired approach introduced by Mayor and Mani (2019) with an item response theory-based computerized adaptive testing that adapts to the ability of each child, in line with…

Calibration of new items online has been an important topic in item replenishment for multidimensional computerized adaptive testing (MCAT). Several online calibration methods have been proposed for MCAT, such as multidimensional "one expectation-maximization (EM) cycle" (M-OEM) and multidimensional "multiple EM cycles"…

In this study we compared five item selection procedures using three ability estimation methods in the context of a mixed-format adaptive test based on the generalized partial credit model. The item selection procedures used were maximum posterior weighted information, maximum expected information, maximum posterior weighted Kullback-Leibler…

It is shown that deviations of estimated from true values of item difficulty parameters, caused for example by item calibration errors, the neglect of randomness of item difficulty parameters, testlet effects, or rule-based item generation, can lead to systematic bias in point estimation of person parameters in the context of adaptive testing.…

For computerized adaptive tests (CATs) to work well, they must have an item pool with sufficient numbers of good quality items. Many researchers have pointed out that, in developing item pools for CATs, not only is the item pool size important but also the distribution of item parameters and practical considerations such as content distribution…

In recent years, many computerized test systems have been developed for diagnosing students' learning profiles. Nevertheless, it remains a challenging issue to find an adaptive testing algorithm to both shorten testing time and precisely diagnose the knowledge status of students. In order to find a suitable algorithm, four adaptive testing…

An adaptive testing method is presented that controls the speededness of a test using predictions of the test takers' response times on the candidate items in the pool. Two different types of predictions are investigated: posterior predictions given the actual response times on the items already administered and posterior predictions that use the…

Response times on items can be used to improve item selection in adaptive testing provided that a probabilistic model for their distribution is available. In this research, the author used a hierarchical modeling framework with separate first-level models for the responses and response times and a second-level model for the distribution of the…

Used a simulation to investigate the applicability to computerized adaptive test data of a differential item functioning (DIF) analysis method. Results show the performance of this empirical Bayes enhancement of the Mantel Haenszel DIF analysis method to be quite promising. (SLD)

Explored procedures to detect test takers using item preknowledge in computerized adaptive testing and suggested a Bayesian posterior log odds ratio index for this purpose. Simulation results support the use of the odds ratio index. (SLD)

This paper suggests several item selection criteria for adaptive testing that are all based on the use of the true posterior. Some of the ability estimators produced by these criteria are discussed and empirically criticized. (SLD)

This study applied the maximum expected information (MEI) and the maximum posterior-weighted information (MPI) approaches of computer adaptive testing item selection to the case of a test using polytomous items following the partial credit model. The MEI and MPI approaches are described. A simulation study compared the efficiency of ability…