Many recent studies have looked at the viability of applying recurrent neural networks (RNNs) to educational data. In most cases, this is done by comparing their performance to existing models in the artificial intelligence in education (AIED) and educational data mining (EDM) fields. While there is increasing evidence that, in many situations,…

Through simulated data, five multidimensional computerized adaptive testing (MCAT) selection procedures with varying test lengths are examined and compared using different stopping rules. Fixed item exposure rates are used for all the items, and the Priority Index (PI) method is used for the content constraints. Two stopping rules, standard error…

If classification in a limited number of categories is the purpose of testing, computerized adaptive tests (CATs) with algorithms based on sequential statistical testing perform better than estimation-based CATs (e.g., Eggen & Straetmans, 2000). In these computerized classification tests (CCTs), the Sequential Probability Ratio Test (SPRT) (Wald,…

The generalized graded unfolding model (GGUM) has been recently developed to describe item responses to Likert items (agree-disagree) in attitude measurement. In this study, the authors (a) developed two item selection methods in computerized classification testing under the GGUM, the current estimate/ability confidence interval method and the cut…

In sequential mastery testing (SMT), assessment via computer is used to classify examinees into one of two mutually exclusive categories. Unlike paper-and-pencil tests, SMT has the capability to use variable-length stopping rules. One approach to shortening variable-length tests is stochastic curtailment, which halts examination if the probability…

Several classical approaches and alternative approaches to item selection for computerized adaptive testing (CAT) are reviewed and compared. The study also describes procedures for constrained CAT that may be added to classical item selection approaches to allow them to be used for applied testing. (TJH)

This paper presents a derivation of an average between-test overlap index as a function of the item exposure index, for fixed-length computerized adaptive tests (CAT). This relationship is used to investigate the simultaneous control of item exposure at both the item and test levels. Implications for practice as well as future research are also…

Item exposure control, test-overlap minimization, and the efficient use of item pool are some of the important issues in computerized adaptive testing (CAT) designs. The overexposure of some items and high test-overlap rate may cause both item and test security problems. Previously these problems associated with the maximum information (Max-I)…

In a variable-length adaptive test with a stopping rule that relied on the asymptotic standard error of measurement of the examinee's estimated true score, M. S. Stocking (1987) discovered that it was sufficient to know the examinee's true score and the number of items administered to predict with some accuracy whether an examinee's true score was…

Extended the use of a beta prior in trait estimation to the maximum expected a posteriori (MAP) method of Bayesian estimation. This new method, essentially unbiased MAP, was compared with MAP, essentially unbiased expected a posteriori, weighted likelihood, and maximum-likelihood estimation methods. The new method significantly reduced bias in…

TAILOR, a computer program which implements an approach to tailored testing, was examined by Monte Carlo methods. The evaluation showed the procedure to be highly reliable and capable of reducing the required number of tests items by about one half. (Author/JKS)

As adaptive testing moves toward operational implementation in large scale testing programs, where it is important that adaptive tests be as parallel as possible to existing linear tests, a number of practical issues arise. This paper concerns three such issues. First, optimum item pool size is difficult to determine in advance of pool…

A series of computer simulations was run to measure the relationship between testlet validity and the factors of item pool size and testlet length for both adaptive and linearly constructed testlets. Results confirmed the generality of earlier empirical findings of H. Wainer and others (1991) that making a testlet adaptive yields only marginal…

The basic equations of item response theory provide a foundation for inferring examinees' abilities and items' operating characteristics from observed responses. In practice, though, examinees will usually not have provided a response to every available item--for reasons that may or may not have been intended by the test administrator, and that…

Error indices (bias, standard error of estimation, and root mean square error) obtained on different scales of measurement under different test termination rules in a computerized adaptive test (CAT) context were examined. Four ability estimation methods were studied: (1) maximum likelihood estimation (MLE); (2) weighted likelihood estimation…