This paper presents the conceptual design of a simulation-based training system that supports pre-service teachers in developing discourse competence for facilitating accountable classroom talk on socio-scientific issues (SSI). The system is grounded in research on dialogic teaching, conceptual change, teacher reflection, and the TPACK framework.…

This study concludes that traditional logistic regression models, particularly those using ACT Composite scores, tend to demonstrate better fairness metrics across subgroups compared to a fairness-aware machine learning gradient-boosted machine model. The exclusion of race/ethnicity from predictive models does not introduce notable bias and may…

Machine translation tools have gained increasing popularity among translation learners, transforming their translation learning behaviors. However, it is unclear how learners' continuance intention to use these tools is affected yet. Based on the task-technology fit (TTF) model and the value-based adoption model (VAM), the present study examined…

The rapid adoption of generative artificial intelligence (AI) chatbots, particularly ChatGPT, among university students reflects significant changes in the teaching and learning process. This study examines the usage patterns, motivations, and attitudes of 974 university students who use generative chatbots in academic settings. Results indicate…

Generative AI technologies are rapidly transforming educational practices, creating both opportunities and challenges for teacher-preparation programs. As these advanced tools become increasingly prevalent in classrooms, understanding the factors that influence pre-service teachers' acceptance and adoption of such technologies has become…

Generative Artificial Intelligence (GAI), with its distinctive capabilities, is inducing profound transformations across multiple industries. In the realm of higher education, a centered around human intellect and pedagogical advancement, these emerging technologies are at a pivotal juncture of change. Within the scope of GAI, the dynamics of…

Purpose: This study investigates the relationships between distributed leadership, innovative work behavior (IWB), and teachers' perceptions of artificial intelligence (AI) implementation in Ghanaian schools. Specifically, it explores the direct and indirect effects of distributed leadership on teachers' perceptions of AI, with IWB acting as a…

Previous studies have used cluster analysis to address the diagnostic heterogeneity of autism spectrum disorder, but have been limited by identifying subgroups solely on the basis of core autism symptoms. The present study aimed to identify sleep phenotypes and their clustering with core autism symptoms in youth diagnosed with autism. 1397…

Machine learning algorithms have been widely used for identifying at-risk students. Current research focuses on timeliness and accuracy of the predictions, leading to a heavy reliance on demographic data, which introduces severe bias issues. This study develops fairness-aware machine learning models to identify at-risk students in high school…

The integration of artificial intelligence (AI) into nursing education is essential for equipping future nurses with the skills required to navigate an increasingly technology-driven healthcare environment. This study aimed to validate the Arabic version of the Unified Theory of Acceptance and Use of Technology (UTAUT-2012) model in assessing…

Objective: The current project aims to identify individuals in urgent need of mental health care, using a machine learning algorithm (random forest). Comparison/contrast with conventional regression analyses is discussed. Participants: A total of 2,409 participants were recruited from an anonymous university, including undergraduate and graduate…

This study explores the effects of embedding Socio-Scientific Issues (SSI) into vocational design education on students' ethics awareness, social responsibility, and design performance. A mixed-methods quasi-experimental design was employed, involving 80 vocational design students divided into an experimental group (SSI-based workshop) and a…

We evaluate impacts heterogeneity of an Early Childhood Intervention, with respect to the Educational Attainment Polygenic Score (EA4 PGS) constructed from DNA data based on GWAS weights from a European population. We find that the EA4 PGS is predictive of several measures of child development, mother's IQ and, to some extent, educational…

Generative Artificial Intelligence (GenAI) is a transformative technology in education, especially in lesson planning (LP). This research examines pre-service teachers' (PSTs) perceptions of GenAI benefits and ethical risks in LP, with consideration for the Technology Acceptance Model (TAM). The findings show that PSTs are generally cognizant of…

Little is known about how to develop frameworks for using AI to support learning in English Literature within higher education. This paper presents research that developed a framework for employing AI in the study of the fourteenth-century English poet Geoffrey Chaucer. Studying Chaucer presents challenges for modern readers, as it requires an…