This study compares four item selection criteria for a two-category computerized classification testing: (1) Fisher information (FI), (2) Kullback-Leibler information (KLI), (3) weighted log-odds ratio (WLOR), and (4) mutual information (MI), with respect to the efficiency and accuracy of classification decision using the sequential probability…

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…

Computerized classification testing (CCT) is an approach to designing tests with intelligent algorithms, similar to adaptive testing, but specifically designed for the purpose of classifying examinees into categories such as "pass" and "fail." Like adaptive testing for point estimation of ability, the key component is the…

This simulation study sought to compare four different computerized adaptive testing (CAT) content-balancing procedures designed for use in a multidimensional assessment with respect to measurement precision, symptom severity classification, validity of clinical diagnostic recommendations, and sensitivity to atypical responding. The four…

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…

Evaluated three strategies for assigning examinees to grading categories in computerized adaptive testing. The expected a posteriori-based method had more correct classifications in the middle range of grade levels and more errors for the extremes than the golden section search grading test and the Z-score grading test. (SLD)

E-learning provides a convenient and efficient way for learning. Formative assessment not only guides student in instruction and learning, diagnose skill or knowledge gaps, but also measures progress and evaluation. An efficient and convenient e-learning formative assessment system is the key character for e-learning. However, most e-learning…

A scheme is introduced for classifying assessment methods by using a mapping sentence and examples of three tasks from research methodology are provided along with their profiles (structures) based on the mapping sentence. An instrument to determine student assessment preferences is presented and explored. (SLD)

An adaptive testing algorithm is presented based on an alternative modeling framework, and its effectiveness is investigated in a simulation based on real data. The algorithm uses a latent class modeling framework in which assessed latent attributes are assumed to be categorical variables. (SLD)

Studied the use of adaptive testing when examinees are classified into three categories. Established testing algorithms with two different statistical computation procedures and evaluated them through simulation using an operative item bank from Dutch basic adult education. Results suggest a reduction of at least 22% in the mean number of items…

This paper describes a study, now in progress, of new methods for representing the sampling variability of Mantel-Haenszel differential item functioning (DIF) results, based on the system for categorizing the severity of DIF that is now in place at the Educational Testing Service. The methods, which involve a Bayesian elaboration of procedures…

The purpose of this paper is to derive optimal rules for variable-length mastery tests in case three mastery classification decisions (nonmastery, partial mastery, and mastery) are distinguished. In a variable-length or adaptive mastery test, the decision is to classify a subject as a master, a partial master, a nonmaster, or continuing sampling…

Measures of the robustness of disease class-specific diagnostic concepts could play a central role in training programs designed to assure the development of diagnostic competence. In the pilot study, the authors used disease/sign-symptom conditional probability estimates, Monte Carlo procedures, and artificial intelligence (AI) tools to create…

The author analyzes properties of mutual information between dichotomous concepts and test items. The properties generalize some common intuitions about item comparison, and provide principled foundations for designing item-selection heuristics for student assessment in computer-assisted educational systems. The proposed item-selection strategies…