Solving mathematical (math) word problems (MWP) automatically is a challenging research problem in natural language processing, machine learning, and education (learning) technology domains, which has gained momentum in the recent years. Applications of solving varieties of MWPs can increase the efficacy of teaching-learning systems, such as…

We examine the accuracy of p values obtained using the asymptotic mean and variance (MV) correction to the distribution of the sample standardized root mean squared residual (SRMR) proposed by Maydeu-Olivares to assess the exact fit of SEM models. In a simulation study, we found that under normality, the MV-corrected SRMR statistic provides…

Past work investigating spatial cognition suggests better mental rotation abilities for those who are fluent in a signed language. However, no prior work has assessed whether fluency is needed to achieve this performance benefit or what it may look like on the neurobiological level. We conducted an electroencephalography experiment and assessed…

The current study explores the ability to predict argumentative claims in structurally-annotated student essays to gain insights into the role of argumentation structure in the quality of persuasive writing. Our annotation scheme specified six types of argumentative components based on the well-established Toulmin's model of argumentation. We…

Knowledge tracing (KT), the task of tracking the knowledge state of each student over time, has been assessed actively by artificial intelligence researchers. Recent reports have described that Deep-IRT, which combines Item Response Theory (IRT) with a deep learning model, provides superior performance. It can express the abilities of each student…

Existing approaches to measuring writing performance are insufficient in terms of both technical adequacy as well as feasibility for use as a screening measure. This study examined the validity and diagnostic accuracy of several approaches to automated text evaluation as well as written expression curriculum-based measurement (WE-CBM) to determine…

We examined the extent to which automated written expression curriculum-based measurement (aWE-CBM) can be accurately used to computer score student writing samples for screening and progress monitoring. Students (n = 174) with learning difficulties in Grades 1-12 who received 1:1 academic tutoring through a community-based organization completed…

As the accuracy of evaluations is important to teachers, it is essential to examine their perceptions about accuracy (Cho & Schunn, 2018; Plunkett & Dyson, 2018). Understanding teachers' perceptions of accuracy are significant because an evaluation system's effectiveness depends on the teachers' belief that it is accurate (Lewis, 2018;…

Early literacy curriculum-based measures (CBMs) are widely used as universal screeners within multi-tiered systems of support in reading (MTSS-R) for (1) evaluating the overall effectiveness of the reading system and (2) assigning students to supplemental and intensive interventions. Evidence supporting CBM validity for these purposes have…

Purpose: This study evaluates the effectiveness of a nonword repetition (NWR) task in discriminating between Palestinian Arabic-speaking children with developmental language disorder (DLD) and age-matched typically developing (TD) children. Method: Participants were 30 children with DLD aged between 4;0 and 6;10 (years;months) and 60 TD children…

In the present study, the Teacher Formative Assessment Literacy Scale (TFALS), developed by Yan and Pastore (2022a), was translated into Turkish to examine the factor structure and psychometric characteristics of the scale in a Turkish sample. Data was collected from 318 teachers, of whom 168 were males and 150 were females, working in different…

Single-case designs substantiate the effectiveness of interventions for people with disabilities and other populations through the repeated measurement of behavior over time. Consequently, employing accurate and reliable systems of measurement is critical to the validity of single-case designs. Much of the data in single-case research are…

Background: Since it was first launched, ChatGPT, a Large Language Model (LLM), has been widely used across different disciplines, particularly the medical field. Objective: The main aim of this review is to thoroughly assess the performance of the distinct version of ChatGPT in subspecialty written medical proficiency exams and the factors that…

Presented study seeks to examine the potential applications of the OpenAI language model, GPT-3, within the realm of education. Specifically, the inquiry focuses on the feasibility of utilizing GPT-3 to generate essays based on customized prompts. To this end, the experimentation involved providing GPT-3 with tailored prompts derived from diverse…

Purpose: ChatGPT is a generative artificial intelligence (AI) technology that can solve multiple complex tasks. ChatGPT-4 can facilitate educational empowerment in China through technology to understand and generate Chinese text. Although ChatGPT's benefits have been widely discussed, its educational capabilities have not been systematically…