This study conducted a comprehensive comparison of Item Response Theory (IRT) linking methods applied to a bifactor model, examining their performance on both multiple choice (MC) and mixed format tests within the common item nonequivalent group design framework. Four distinct multidimensional IRT linking approaches were explored, consisting of…

This article presents the process of constructing and validating a test of metalinguistic awareness (MLA) for young school children (age 8-10). The test was developed between 2021 and 2023 as part of the MetaLearn research project, financed by The Research Council of Norway. The research team defines MLA as using metalinguistic knowledge at a…

Response styles pose great threats to psychological measurements. This research compares IRTree models and anchoring vignettes in addressing response styles and estimating the target traits. It also explores the potential of combining them at the item level and total-score level (ratios of extreme and middle responses to vignettes). Four models…

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…

This report describes the process of developing and validating the enhanced ACT. The report describes the changes made to the test content and the processes by which these design decisions were implemented. The authors describe how they shared the overall scope of the enhancements, including the initial blueprints, with external expert panels,…

Starting in April 2025, ACT will introduce enhanced forms of the ACT® test for national online testing, with a full rollout to all paper and online test takers in national, state and district, and international test administrations by Spring 2026. ACT introduced major updates by changing the test lengths and testing times, providing more time per…

The current paper intends to exploit the Many Facet Rasch Model to investigate and compare the impact of situations (items) and raters on test takers' performance on the Written Discourse Completion Test (WDCT) and Discourse Self-Assessment Tests (DSAT). In this study, the participants were 110 English as a Foreign Language (EFL) students at…

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 study aimed to propose a new method for scoring C-Tests as measures of general language proficiency. In this approach, the unit of analysis is sentences rather than gaps or passages. That is, the gaps correctly reformulated in each sentence were aggregated as sentence score, and then each sentence was entered into the analysis as a polytomous…

VocQGen is an automated tool designed to generate multiple-choice cloze (MCC) questions for vocabulary assessment in second language learning contexts. It leverages several natural language processing (NLP) tools and OpenAI's GPT-4 model to produce MCC items quickly from user-specified word lists. To evaluate its effectiveness, we used the first…