This study compares how the generative AI (GenAI) large language model (LLM) ChatGPT performs in grading university exams compared to human teachers. Aspects investigated include consistency, large discrepancies and length of answer. Implications for higher education, including the role of teachers and ethics, are also discussed. Three…

Prior research highlights the benefits of multimode surveys and best practices for item-by-item (IBI) and matrix-type survey items. Some researchers have explored whether mode differences for online and paper surveys persist for these survey item types. However, no studies discuss measurement invariance when both item types and online modes are…

Adaptive measurement of change (AMC) is a psychometric method for measuring intra-individual change on one or more latent traits across testing occasions. Three hypothesis tests--a Z test, likelihood ratio test, and score ratio index--have demonstrated desirable statistical properties in this context, including low false positive rates and high…

The multiple-choice (MC) item format has been widely used in educational assessments across diverse content domains. MC items purportedly allow for collecting richer diagnostic information. The effectiveness and economy of administering MC items may have further contributed to their popularity not just in educational assessment. The MC item format…

Item parameter drift (IPD) is the systematic differentiation of parameter values of items over time due to various reasons. If it occurs in computer adaptive tests (CAT), it causes errors in the estimation of item and ability parameters. Identification of the underlying conditions of this situation in CAT is important for estimating item and…

Computational Thinking (CT) skill was a part of the global framework of reference on Digital Literacy for Indicator 4.4.2, widely developed in mathematics and science learning. This study aimed to promote an assessment tool using a two-tier Computerized Adaptive Test (CAT). The study used the Design and Development Research (DDR) method with four…

In this study, Kernel test equating methods were compared under NEAT and NEC designs. In NEAT design, Kernel post-stratification and chain equating methods taking into account optimal and large bandwidths were compared. In the NEC design, gender and/or computer/tablet use was considered as a covariate, and Kernel test equating methods were…

The Social Shapes Test (SST) is a measure of social intelligence which does not use human faces or rely on extensive verbal ability. The SST has shown promising validity among adults without autism spectrum disorder (ASD), but it is uncertain whether it is suitable for adults with ASD. We find measurement invariance between adults with (n = 229)…

Background: Computerised adaptive tests (CATs) are tests that provide personalised, efficient and accurate measurement while reducing testing time, depending on the desired level of precision. Schools have different types of assessments that can benefit from a significant reduction in testing time to varying degrees, depending on the area of…

Analyses that reveal how treatment effects vary allow researchers, practitioners, and policymakers to better understand the efficacy of educational interventions. In practice, however, standard statistical methods for addressing heterogeneous treatment effects (HTE) fail to address the HTE that may exist "within" outcome measures. In…

Scoring constructed-response items can be highly difficult, time-consuming, and costly in practice. Improvements in computer technology have enabled automated scoring of constructed-response items. However, the application of automated scoring without an investigation of test equating can lead to serious problems. The goal of this study was to…

This article introduces the Quality of Item Pool (QIP) Index, a novel approach to quantifying the adequacy of an item pool of a computerized adaptive test for a given set of test specifications and examinee population. This index ranges from 0 to 1, with values close to 1 indicating the item pool presents optimum items to examinees throughout the…

In this digital ITEMS module, Dr. Sue Lottridge, Amy Burkhardt, and Dr. Michelle Boyer provide an overview of automated scoring. Automated scoring is the use of computer algorithms to score unconstrained open-ended test items by mimicking human scoring. The use of automated scoring is increasing in educational assessment programs because it allows…

This dissertation develops and applies sophisticated Item Response Theory (IRT) methods to address fundamental measurement challenges in cognitive testing, focusing on the Armed Services Vocational Aptitude Battery (ASVAB) data from the National Longitudinal Survey of Youth (NLSY). The first chapter implements a confirmatory multidimensional IRT…

The computerized adaptive tests (CAT) apply an adaptive process in which the items are tailored to individuals' ability scores. The multidimensional CAT (MCAT) designs differ in terms of different item selection, ability estimation, and termination methods being used. This study aims at investigating the performance of the MCAT designs used to…