As technologies have been improved, item preknowledge has become a common concern in the test security area. The present study proposes an unsupervised-learning-based approach to detect compromised items. The unsupervised-learning-based compromised item detection approach contains three steps: (1) classify responses of each examinee as either…

Scientific methods have received widespread attention in recent years. Based on the analytical framework derived from Brandon's matrix consisting of four categories of scientific methods, this paper aims to conduct a content analysis to examine how the diversity of scientific methods is represented in college entrance chemistry examination papers…

To assemble a high-quality test, psychometricians rely on subject matter experts (SMEs) to write high-quality items. However, SMEs are not typically given the opportunity to provide input on which content standards are most suitable for multiple-choice questions (MCQs). In the present study, we explored the relationship between perceived MCQ…

Psychometricians have devoted much research and attention to categorical item responses, leading to the development and widespread use of item response theory for the estimation of model parameters and identification of items that do not perform in the same way for examinees from different population subgroups (e.g., differential item functioning…

There is no need or point to testing of knowledge, attributes, traits, behaviours or abilities of an individual if information obtained from the test is inaccurate. However, by and large, it seems the estimation of psychometric properties of test items in classroomshas been completely ignored otherwise dying slowly in most testing environments. In…

For large-scale assessments, data are often collected with missing responses. Despite the wide use of item response theory (IRT) in many testing programs, however, the existing literature offers little insight into the effectiveness of various approaches to handling missing responses in the context of scale linking. Scale linking is commonly used…

In computerized adaptive testing, overexposure of items in the bank is a serious problem and might result in item compromise. We develop an item selection algorithm that utilizes the entire bank well and reduces the overexposure of items. The algorithm is based on collaborative filtering and selects an item in two stages. In the first stage, a set…

The testlet comprises a set of items based on a common stimulus. When the testlet is used in the tests, there may violate the local independence assumption, and in this case, it would not be appropriate to use traditional item response theory models in the tests in which the testlet is included. When the testlet is discussed, one of the most…

In operational testing, item response theory (IRT) models for dichotomous responses are popular for measuring a single latent construct [theta], such as cognitive ability in a content domain. Estimates of [theta], also called IRT scores or [theta hat], can be computed using estimators based on the likelihood function, such as maximum likelihood…

To mitigate the deleterious effects of rapid guessing (RG) on ability estimates, several rescoring procedures have been proposed. Underlying many of these procedures is the assumption that RG is accurately identified. At present, there have been minimal investigations examining the utility of rescoring approaches when RG is misclassified, and…

Coefficient alpha reliability persists as the most common reliability coefficient reported in research. The assumptions for its use are, however, not well-understood. The current paper challenges the commonly used expressions of coefficient alpha and argues that while these expressions are correct when estimating reliability for summed scores,…

This article compares two methods for detecting local item dependence (LID): residual correlation examination and Rasch testlet modeling (RTM), in a commonly used 3:6 matching format and an extended matching test (EMT) format. The two formats are hypothesized to facilitate different levels of item dependency due to differences in the number of…

Effective educational measurement relies heavily on the curation of well-designed item pools. However, item calibration is time consuming and costly, requiring a sufficient number of respondents to estimate the psychometric properties of items. In this study, we explore the potential of six different large language models (LLMs; GPT-3.5, GPT-4,…

The provision of progress monitoring within publicly funded early childhood classrooms is legally required, supported by empirical research, and recommended by early childhood professional organizations, for teachers providing Part B services under the Individuals with Disabilities Education Act. Despite the widespread recognition of progress…

Extreme response style (ERS), the tendency of participants to select extreme item categories regardless of the item content, has frequently been found to decrease the validity of Likert-type questionnaire results. For this reason, various item response theory (IRT) models have been proposed to model ERS and correct for it. Comparisons of these…