Acquiescence is the tendency of participants to shift their responses to agreement. Lechner et al. (2019) introduced the following mechanisms of acquiescence: social deference and cognitive processing. We added their interaction into a theoretical framework. The sample consists of 557 participants. We found significant medium strong relationship…

This study compares the psychometric properties of scales developed using Exploratory Factor Analysis (EFA), Self-Organizing Map (SOM), and Andrich's Rating Scale Model (RSM). Data for the research were collected by administering the "Statistical Attitude Scale" trial form, previously used in a separate study, to 808 individuals. First,…

When learning with self-testing alone, will a learner make inferences between the tested items? This study examines whether self-testing's benefits extend beyond isolated facts to support broader connections between the facts. Comparing self-testing to self-explanation (a strategy known to facilitate inferential learning), we find that while…

Rasch modelling is a powerful tool for evaluating item performance, measuring drift in difficulty over time, and comparing students who sat assessments at different times or at different sites. Here, we use data from thirty UK medical schools to describe the benefits of Rasch modelling in quality assurance and the barriers to using it. Sixty…

"A Practical Guide to Language Assessment" helps educators at every level redefine their approach to language assessment. Grounded in extensive research and aligned with the latest advances in language education, this comprehensive guide introduces foundational concepts and explores key principles in test development and item writing.…

Enemy items are two test items that should not be presented to a candidate on the same test. Identifying enemies is essential for personnel assessment, as they weaken the measurement precision and validity of a test. In this research, we examined the effectiveness of lexical and semantic natural language processing techniques for identifying enemy…

Online calibration estimates new item parameters alongside previously calibrated items, supporting efficient item replenishment. However, most existing online calibration procedures for Cognitive Diagnostic Computerized Adaptive Testing (CD-CAT) lack mechanisms to ensure content balance during live testing. This limitation can lead to uneven…

This study introduces a new chi-square test statistic for testing the equality of response frequencies among distracters in multiple-choice tests. The formula uses the information from the number of correct answers and wrong answers, which becomes the basis of calculating the expected values of response frequencies per distracter. The method was…

Assessment is viewed as an important means to understand learners' performance in the learning process. A good assessment method is based on high-quality examination questions. However, generating high-quality examination questions manually by teachers is a time-consuming task, and it is not easy for students to obtain question banks. To solve…

The use of unidimensional scales that contain both positively and negatively worded items is common in both the educational and psychological fields. However, dimensionality investigations of these instruments often lead to a rejection of the theorized unidimensional model in favor of multidimensional structures, leaving researchers at odds for…

Test developers and psychometricians have historically examined measurement bias and differential item functioning (DIF) across a single categorical variable (e.g., gender), independently of other variables (e.g., race, age, etc.). This is problematic when more complex forms of measurement bias may adversely affect test responses and, ultimately,…

Traditional estimators of reliability such as coefficients alpha, theta, omega, and rho (maximal reliability) are prone to give radical underestimates of reliability for the tests common when testing educational achievement. These tests are often structured by widely deviating item difficulties. This is a typical pattern where the traditional…

Random item effects item response theory (IRT) models, which treat both person and item effects as random, have received much attention for more than a decade. The random item effects approach has several advantages in many practical settings. The present study introduced an explanatory multidimensional random item effects rating scale model. The…

This dissertation examines the effectiveness of machine learning algorithms and feature engineering techniques for analyzing process data and predicting test performance. The study compares three classification approaches and identifies item-specific process features that are highly predictive of student performance. The findings suggest that…

Computer adaptive testing (CAT) is an increasingly common mode of test administration offering improved test security, better measurement precision, and the potential for shorter testing experiences. This article presents a new item selection algorithm based on a generalized objective function to support multiple types of testing conditions and…