This study investigated the impact of scoring polytomous items later on measurement precision, classification accuracy, and test security in mixed-format adaptive testing. Utilizing the shadow test approach, a simulation study was conducted across various test designs, lengths, number and location of polytomous item. Results showed that while…

Multistage testing (MST), an adaptive test delivery mode that involves algorithmic selection of predefined item modules rather than individual items, offers a practical alternative to linear and fully computerized adaptive testing. However, interactions across stages between item modules and examinee groups can lead to challenges in item…

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)

This paper focuses on a version of sequential mastery testing (i.e., classifying students as a master/nonmaster or continuing testing and administering another item or testlet) in which response behavior is modeled by a multidimensional item response theory (IRT) model. First, a general theoretical framework is outlined that is based on a…

Two operational item pools were used to investigate the performance of stratum computerized adaptive tests (CATs) when items were assigned to strata based on empirical estimates of item difficulty or human judgments of item difficulty. Items from the first data set consisted of 54 5-option multiple choice items from a form of the ACT mathematics…

A method of item pool design is proposed that uses an optimal blueprint for the item pool calculated from the test specifications. The blueprint is a document that specifies the attributes that the items in the computerized adaptive test (CAT) pool should have. The blueprint can be a starting point for the item writing process, and it can be used…

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…

This study examined performance of a simulated computerized adaptive test that was designed to help direct the development of a medical recertification examination. The item pool consisted of 229 single-best-answer items from a random sample of 3,000 examinees, calibrated using the two-parameter logistic model. Examinees' responses were known. For…