Mixture models have been developed to enable detection of within-subject differences in responses and response times to psychometric test items. To enable mixture modeling of both responses and response times, a distributional assumption is needed for the within-state response time distribution. Since violations of the assumed response time…

This article proposes a class of cognitive diagnosis models (CDMs) for polytomously scored items with different link functions. Many existing polytomous CDMs can be considered as special cases of the proposed class of polytomous CDMs. Simulation studies were carried out to investigate the feasibility of the proposed CDMs and the performance of…

Item response theory provides various important advantages for exams carried out or to be carried out digitally. For computerized adaptive tests to be able to make valid and reliable predictions supported by IRT, good quality item pools should be used. This study examines how adaptive test applications vary in item pools which consist of items…

Purpose: This study aims to compare the performances of Item Response Theory (IRT) equating and kernel equating (KE) methods based on equating errors (RMSD) and standard error of equating (SEE) using the anchor item nonequivalent groups design. Method: Within this scope, a set of conditions, including ability distribution, type of anchor items…

Cognitive and metacognitive processes during learning depend on accurate monitoring, this investigation examines the influence of immediate item-level knowledge of correct response feedback on cognition monitoring accuracy. In an optional end-of-course computer-based review lesson, participants (n = 68) were randomly assigned to groups to receive…

Forced-choice questionnaires can prevent faking and other response biases typically associated with rating scales. However, the derived trait scores are often unreliable and ipsative, making interindividual comparisons in high-stakes situations impossible. Several studies suggest that these problems vanish if the number of measured traits is high.…

In assembling testlets (i.e., test forms) with a pool of new and used item blocks, test security is one of the main issues of concern. Strict constraints are often imposed on repeated usage of the same item blocks. Nevertheless, for an assessment administering multiple testlets, a goal is to select as large a sample of testlets as possible. In…

Given the crucial role of feedback in supporting learning in higher education, understanding the factors influencing feedback effectiveness is imperative. Student feedback literacy, that is, the set of attitudes and abilities to make sense of and utilize feedback is therefore considered a key concept. Rigorous investigations of feedback literacy…

Background: Multiple-choice item (MCI) assessments are burdensome for instructors to develop. Artificial intelligence (AI, e.g., ChatGPT) can streamline the process without sacrificing quality. The quality of AI-generated MCIs and human experts is comparable. However, whether the quality of AI-generated MCIs is equally good across various domain-…

This book explores the transformative role of artificial intelligence in educational assessment, catering to researchers, educators, administrators, policymakers, and technologists involved in shaping the future of education. It delves into the foundations of AI-assisted assessment, innovative question types and formats, data analysis techniques,…

An essential component of language instruction is classroom-based assessment, which is used to inform instructional decisions and gauge student progress. The current study explores how EFL teachers visualize developing classroom-based assessments at Debark Secondary Schools in the North Gondar Zone. The study employed a concurrent parallel…

As artificial intelligence (AI) receives wider attention in education, examining teachers' acceptance of AI (TAAI) becomes essential. However, existing instruments measuring TAAI reported limited validity evidence and faced some design challenges, such as missing informed definitions of AI to participants. To fill this gap, this study developed…

Background: Test score comparability in international large-scale assessments (LSAs) is greatly important to ensure test fairness. To effectively compare test scores on an international scale, score linking is widely used to convert raw scores from different linguistic version of test forms into a common score scale. An example is the multigroup…

The introduction of computing education into curricula worldwide requires multi-year assessments to evaluate the long-term impact on learning. However, no single Computational Thinking (CT) assessment spans primary school, and no group of CT assessments provides a means of transitioning between instruments. This study therefore investigated…

This report provides an in-depth comparison of TOEFL iBT® and the Duolingo English Test (DET) in terms of the degree to which both tests assess academic language proficiency in listening, reading, writing, and speaking. The analysis is based on publicly available documentation on both tests, including sample test questions available on the test…