Rasch common-item equating is often used in high-stakes testing to maintain equivalent passing standards across test administrations. If unaddressed, item parameter drift poses a major threat to the accuracy of Rasch common-item equating. We compared the performance of well-established and newly developed drift detection methods in small and large…

In this study, classifications were made from the data obtained from the Health-Related Physical Fitness Report cards and BMIs of students through data mining methods, artificial neural networks, and decision trees models. Then the classification performances of both models were compared. The body weight and height measurements of the students in…

The rapid advancement of powerful Large Language Models (LLMs), such as ChatGPT and Llama, has revolutionized the world by bringing new creative possibilities and enhancing productivity. However, these advancements also pose significant challenges and risks, including the potential for misuse in the form of fake news, academic dishonesty,…

Measurement invariance holds when a latent construct is measured in the same way across different levels of background variables (continuous or categorical) while controlling for the true value of that construct. Using Monte Carlo simulation, this paper compares the multiple indicators, multiple causes (MIMIC) model and MIMIC-interaction to a…

Background: Differentiating typical language development (TD) and developmental language disorder (DLD) in a bilingual context is difficult. The societal language is often the only mutual language of the child and the SLT. It has been shown that when assessing second language (L2) performance using tools developed for monolingual children,…

Agreement statistics and measures of prediction accuracy are often used to assess the quality of two measures of a construct. Agreement statistics are appropriate for measures that are supposed to be interchangeable, whereas prediction accuracy statistics are appropriate for situations where one variable is the target and the other variables are…

Educational data mining has become an effective tool for exploring the hidden relationships in educational data and predicting students' academic achievements. This study proposes a new model based on machine learning algorithms to predict the final exam grades of undergraduate students, taking their midterm exam grades as the source data. The…

In a novel version of the classic dot-pattern prototype-distortion paradigm of category learning, Homa et al. (2019) tested a condition in which individual training instances never repeated, and observed results that they claimed severely challenged exemplar models of classification and recognition. Among the results was a dissociation in which…

Quantum physics forms the basis for exciting new technologies, including quantum computers, quantum encryption, and quantum entanglement. The advancement of science and technology highlights the importance of mastering quantum physics and its applications, not only at the college level but also as early as high school. In this multiple case study,…

Multistage testing (MST), an adaptive test delivery mode that involves algorithmic selection of predefined item modules rather than individual items, offers a practical alternative to linear and fully computerized adaptive testing. However, interactions across stages between item modules and examinee groups can lead to challenges in item…

Purpose: This study examines the accuracy of Interaction Detection in Early Childhood Settings (IDEAS), a program that automatically transcribes audio files and estimates linguistic units relevant to speech-language therapy, including part-of-speech units that represent features of language complexity, such as adjectives and coordinating…

Adults with dyslexia may find difficulties in reading the messages on variable message signs (VMS) while driving. These signs are an essential part of the traffic communication systems, aimed at informing road users of special circumstances, such as congestion, traffic diversion, or unexpected events. A driving simulation experiment was conducted…

Sign language is considered as the important communication means among the normal people and the deaf. Therefore, developing communication systems to help those people is an important issue. In this paper, the neutrosophic technique and fuzzy c-means are applied to detect and recognize the alphabet Arabic sign language. The proposed system starts…

Feasible and accurate assessment tools developed for non-specialists are needed to scale community-based models of autism evaluation. The purpose of this study was to evaluate use of the Screening Tool for Autism in Toddlers and Young Children (STAT) when used by primary care practitioners (n = 10) across a statewide system of early diagnosis set…

The development of technology-enhanced innovative items calls for practical models that can describe polytomous testlet items. In this study, we evaluate four measurement models that can characterize polytomous items administered in testlets: (a) generalized partial credit model (GPCM), (b) testlet-as-a-polytomous-item model (TPIM), (c)…