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…

This study examines metacognitive monitoring in Turkish preschoolers aged 48--66 months, crucial for their learning and development. A specialised paired-association task was designed to assess higher-order thinking skills in this age group. Data from 160 children (52.5% girls, 47.5% boys; mean age 57.6 months, standard deviation 4.8) were…

Mixed-methods research is employed to investigate the implementation of the Stanislavski system in the study of Thai court drama. This study investigates the successful application of the Stanislavski method in Thai Court Theater, focusing on its role in enabling actors to portray emotions with accuracy and conviction. Research methods encompass…

This literature review delves into the applications and implications of ChatGPT, an artificial intelligence-driven chatbot, in educational settings. As technology continues to permeate the field of education, ongoing debates persist regarding the potential impact on learners' critical thinking skills and the evolving role of educators. Instead of…

The purpose of this study was to investigate if a group of sixth-grade low achievement language minority (LM) students' reading skills could be improved by an intervention designed to train reading fluency, a critical component of reading development, defined as integrating speed and accuracy (reading rate) as well as prosody. The study included…

Background: Autism spectrum disorder and cerebral palsy are prevalent neurodevelopmental disorders. Autistic individuals or individuals with cerebral palsy often struggle with sensory processing that further impacts movement execution. Immersive virtual reality (VR) is a promising assessment and intervention modality to promote motor learning in…

Spatio-temporal processes are ubiquitous and prevalent across disciplines. Understanding the mechanisms underlying processes and integrating this information into models is of great interest, as it can improve forecasting accuracy and align with scientific motivation. Examples of such models include Partial Differential Equation (PDE) Models or…

"Ghosts of the Argonne" is an interactive virtual reality (VR) recreation of the World War 1 (WW1) M1897 "French 75" field artillery gun, intended to teach learners about WW1 and its impact on the world, the role of artillery and artillerymen in this war, and the stories of real soldiers who served. The "Ghosts of the…

The mathematical-related affect research agenda demands studies on the affect-cognition relationship, as well as interventions aimed at improving affective aspects of mathematical learning. The potential of technological environments for promoting cognitive changes in students has been widely informed and there is evidence of their influence in…

This study explores the potential of large language models (LLMs), specifically GPT-4 and Gemini, in generating teaching cases for information systems courses. A unique prompt for writing three different types of teaching cases such as a descriptive case, a normative case, and a project-based case on the same IS topic (i.e., the introduction of…

With recent improvements in machine translation (MT) accuracy, MT has gained unprecedented popularity in second language (L2) learning. Despite the significant number of studies on MT use, the effects of using MT on students' retention of learning or secondary school students' use of MT in L2 writing has rarely been researched. The current study…

Elementary social studies resources have faced criticism for well over 30 years. Text that is too complex (Beck et al., 1989; Beck & McKeown, 1991), contains questionable content (Chu, 2017; Wade, 2012), and is boring to students (Kelley, 2021; Schug, 1982) and teachers (Zhao & Hoge, 2010). More recent studies have found that teachers are…