In multidimensional computerized adaptive testing (MCAT), item selection strategies are generally constructed based on responses, and they do not consider the response times required by items. This study constructed two new criteria (referred to as DT-inc and DT) for MCAT item selection by utilizing information from response times. The new designs…

Recent developments in the use of large-language models have led to substantial improvements in the accuracy of content-based automated scoring of free-text responses. The reported accuracy levels suggest that automated systems could have widespread applicability in assessment. However, before they are used in operational testing, other aspects of…

In computerized adaptive testing, item exposure control methods are often used to provide a more balanced usage of the item pool. Many of the most popular methods, including the restricted method (Revuelta and Ponsoda), use a single maximum exposure rate to limit the proportion of times that each item is administered. However, Barrada et al.…

The purpose of this study was to compare calibration and linking methods for placing pretest item parameter estimates on the item pool scale in a 1-3 computerized multistage adaptive testing design in terms of item parameter recovery. Two models were used: embedded-section, in which pretest items were administered within a separate module, and…

Online calibration is a key technology for item calibration in computerized adaptive testing (CAT) and has been widely used in various forms of CAT, including unidimensional CAT, multidimensional CAT (MCAT), CAT with polytomously scored items, and cognitive diagnostic CAT. However, as multidimensional and polytomous assessment data become more…

In recent years, the application of explainability techniques to automated essay scoring and automated short-answer grading (ASAG) models, particularly those based on transformer architectures, has gained significant attention. However, the reliability and consistency of these techniques remain underexplored. This study systematically investigates…

The purpose of this study is to describe and evaluate a multilingual automated essay scoring (AES) system for grading essays in three languages. Two different sentence embedding models were evaluated within the AES system, multilingual BERT (mBERT) and language-agnostic BERT sentence embedding (LaBSE). German, Italian, and Czech essays were…

Using item-response theory to model rater effects provides an alternative solution for rater monitoring and diagnosis, compared to using standard performance metrics. In order to fit such models, the ratings data must be sufficiently connected in order to estimate rater effects. Due to popular rating designs used in large-scale testing scenarios,…

This article studied two methods to detect mode effects in two credentialing exams. In Study 1, we used a "modal scale comparison approach," where the same pool of items was calibrated separately, without transformation, within two TC cohorts (TC1 and TC2) and one OP cohort (OP1) matched on their pool-based scale score distributions. The…

Designing a multidimensional adaptive test (M-MST) based on a multidimensional item response theory (MIRT) model is critical to make full use of the advantages of both MST and MIRT in implementing multidimensional assessments. This study proposed two types of automated test assembly (ATA) algorithms and one set of routing rules that can facilitate…

The emergence of sophisticated AI tools such as ChatGPT, coupled with the transition to remote delivery of educational assessments in the COVID-19 era, has led to increasing concerns about academic integrity and test security. Using AI tools, test takers can produce high-quality texts effortlessly and use them to game assessments. It is thus…

By tailoring test forms to the test-taker's proficiency, Computerized Adaptive Testing (CAT) enables substantial increases in testing efficiency over fixed forms testing. When used for formative assessment, the alignment of task difficulty with proficiency increases the chance that teachers can derive useful feedback from assessment data. The…

The field of educational measurement places validity and fairness as central concepts of assessment quality. Prior research has proposed embedding fairness arguments within argument-based validity processes, particularly when fairness is conceived as comparability in assessment properties across groups. However, we argue that a more flexible…

A key consideration when giving any computerized adaptive test (CAT) is how much adaptation is present when the test is used in practice. This study introduces a new framework to measure the amount of adaptation of Rasch-based CATs based on looking at the differences between the selected item locations (Rasch item difficulty parameters) of the…

The use of computerized adaptive testing algorithms for ranking items (e.g., college preferences, career choices) involves two major challenges: unacceptably high computation times (selecting from a large item pool with many dimensions) and biased results (enhanced preferences or intensified examinee responses because of repeated statements across…