Background: California's unprecedented grant investment in the community school strategy through the California Community Schools Partnership Program (CCSPP) offers a significant opportunity for transformative, equity-centered, whole-child school reform (Maier & Niebuhr, 2021). Community schools are grounded in partnerships that schools…

Purpose: This paper examines the integration of artificial intelligence (AI) in organizational training and development through an evidence-based lens, addressing the gap between technological enthusiasm and pedagogical effectiveness in workplace learning contexts. Design/methodology/approach: An integrative literature review methodology was…

Collaborative problem solving is widely recognized as a critical 21st-century skill. Assessing collaborative problem solving depends on coding the communication data using a construct-relevant framework, and this process has long been a major bottleneck to scaling up such assessments. Based on five datasets and two coding frameworks, we…

This research focuses on developing innovator skills in a group of innovators in the higher education level in the field of business administration, emphasizing the use of creative learning processes to promote innovator skills. The purpose of this research is to 1) Studying the characteristics of higher education innovators. 2) Develop a…

Dysgraphia is a learning disability that impairs children's written expression, mainly handwriting but also coherence at the same time. This research work was conducted to know the effectiveness of Chat Generative Pre-trained Transformer (ChatGPT)-based intervention, in assisting children with dysgraphia to enhance their writing skills. The…

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…

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…

In comparison to children and young students, adult learners usually exhibit more complex learning behaviors and psychological needs during the learning process. Designing social robots for adult learners has, thus, been a challenging task and a far less explored area, and it requires the great efforts from both technical and theoretical…