The mathematical abilities of children with autism spectrum condition have been understudied. Magnitude representation is a fundamental numerical ability that emerges early in development and is linked to children's learning of formal mathematics. It remains unclear about whether children with autism spectrum condition differ from their peers…

The potential of artificial intelligence (AI) in transforming education has received considerable attention. This study aims to explore the potential of large language models (LLMs) in assisting students with studying and passing standardized exams, while many people think it is a hype situation. Using primary education as an example, this…

Language immersion programs seek to develop multilingual, multiliterate individuals able to engage with academic content. Studies of immersion students' language development provide details regarding language proficiency and accuracy, yet they generally do not address how features of written, academic language, for example, syntactic and lexical…

Derivational suffixes are known to play a crucial role in assigning stress to multi-syllabic words among native English speakers. However, it is unclear whether second language (L2) learners of English can effectively use derivational suffixes as stress cues in written words. To address this gap, we studied if native Chinese-speaking adults…

This study aims to develop a scale to measure the design thinking process and to evaluate the reliability and validity of this scale. It fills this gap by introducing a 36-item scale specifically designed to measure design thinking abilities across the five key stages of the design thinking process: empathize, define, ideate, prototype, and test,…

This study aimed to evaluate the efficacy of the Repeated Reading and Visual Comprehension Program (TOGAP) developed to support the reading comprehension skills of primary school students with specific learning disabilities (SLD) in the 2nd, 3rd, and 4th grades. The research was conducted with four primary school students with SLD. The changing…

Children with Developmental Language Disorder (DLD) show a wide range of impairments, including poor pre-reading skills and decoding difficulties due to phonological deficits and such difficulties have significant repercussions on the acquisition of written language. However, evidence about reading processes and development is mainly available for…

Large Language Models (LLMs) have the potential to improve education by personalizing learning. However, ChatGPT-generated content has been criticized for sometimes producing false, biased, and/or hallucinatory information. To evaluate AI's ability to return clear and accurate anatomy information, this study generated a custom interactive and…

Automatic Speech Scoring (ASS) has increasingly become a useful tool in oral proficiency testing for Second Language (L2) learners. However, limited studies investigate the alignment of ASS indices with the Complexity, Accuracy, and Fluency (CAF)--the three dimensions in evaluating L2 speakers' oral proficiency, and the subsequent impact indices…

This study examined the relationships between word reading and rapid automatized naming (RAN) for objects and letters in Arabic-speaking children with and without dyslexia to determine potential modulating effects of color on naming by comparing children's performance on color and black-white RAN plates. Participants were 114 Arabic-speaking third…

Purpose: There are well-established guidelines for the recording, transcription, and analysis of spontaneous oral language samples by researchers, educators, and speech pathologists. In contrast, there is presently no consensus regarding methods for the written documentation of sign language samples. The Handshape Analysis Recording Tool (HART) is…

Monitoring students' academic progress is vital for ensuring timely completion of their studies and supporting at-risk students. Educational Data Mining (EDM) utilizes machine learning and feature selection to gain insights into student performance. However, many feature selection algorithms lack performance forecasting systems, limiting their…

In recent years, some models for binary and graded format responses have been proposed to assess unipolar variables or "quasi-traits." These studies have mainly focused on clinical variables that have traditionally been treated as bipolar traits. In the present study, we have made a proposal for unipolar traits measured with continuous…

A Monte Carlo simulation study was conducted to compare fit indices used for detecting the correct latent class in three dichotomous mixture item response theory (IRT) models. Ten indices were considered: Akaike's information criterion (AIC), the corrected AIC (AICc), Bayesian information criterion (BIC), consistent AIC (CAIC), Draper's…

This investigation examines the efficacy of multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) over fixed-effects models when performing intersectional studies. The research questions are as follows: (1) What are typical strata representation rates and outcomes on physics research-based assessments? (2) To what…