A growing body of research is focusing on integrating artificial intelligence (AI) and computational thinking (CT) to enhance student learning outcomes. Many researchers have designed instructional activities to achieve various learning goals within this field. Despite the prevalence of studies focusing on instructional design and student learning…

Academic dropout remains a significant challenge for education systems, necessitating rigorous analysis and targeted interventions. This study employs machine learning techniques, specifically random forest (RF) and feature tokenizer transformer (FTT), to predict academic attrition. Utilizing a comprehensive dataset of over 40 000 students from an…

Generative AI has the potential to support teachers with writing instruction and feedback. The purpose of this study was to explore and compare feedback and data-based instructional suggestions from teachers and those generated by different AI tools. Essays from students with and without disabilities who struggled with writing and needed a…

Artificial agents, such as voice-controlled conversational agents (VCAs) built into smart devices, are becoming more prevalent in daily and educational contexts, enhancing the possibility of using them as language partners. However, research has primarily focused on the cognitive or affective outcomes of using these agents, overlooking questions…

As artificial intelligence (AI) technology rapidly advances, it becomes imperative to equip students with tools to navigate through the many intricate ethical considerations surrounding its development and use. Despite growing recognition of this necessity, the integration of AI ethics into higher education curricula remains limited. This paucity…

Artificial intelligence (AI) has been rapidly developing, both in the education field and beyond, in recent years. Due to this fast-paced nature, special education teachers may not be aware of the availability of AI that could be pertinent to their practice. In this manuscript, five AI platforms that are readily available for special education…

The most recent Council on Social Work Education's Educational Policy and Accreditation Standards (EPAS) demands that social workers develop competence in the ethical and professional deployment of technology. Arguably, artificial intelligence has become a critical element in the technological landscape, most recently with the advent of Generative…

Biomedical engineering capstone design courses provide a salient opportunity to discuss ethical considerations in engineering. As technology and society develop and change, new challenges constantly arise related to how society and technology inform each other. In this space, ethical training for engineering students is critically important for…

The study aimed to examine the impact of academic leaders' possession of digital literacy on their attitudes toward artificial intelligence applications in leadership work in light of the diffusion of innovation theory at Umm Al-Qura University (UQU). The study used a descriptive correlational approach with a random sampling method, and overall,…

In higher education, academic advising is crucial to students' decision-making. Data-driven models can benefit students in making informed decisions by providing insightful recommendations for completing their degrees. To suggest courses for the upcoming semester, various course recommendation models have been proposed in the literature using…

We propose a novel approach to address the issue of college student attrition by developing a hybrid model that combines a structural neural network with a piecewise exponential model. This hybrid model not only shows the potential to robustly identify students who are at high risk of dropout, but also provides insights into which factors are most…

The current study aims at assessing the factors which could affect students' use of ChatGPT. The study proposed a theoretical model that included five factors. Data were collected from 136 students using a questionnaire. The data were analyzed using two steps: CFA for measuring the model and SEM for analyzing the relationships and testing…

Student drop-out is one of the most burning issues in STEM higher education, which induces considerable social and economic costs. Using machine learning tools for the early identification of students at risk of dropping out has gained a lot of interest recently. However, there has been little discussion on dropout prediction using interpretable…

Adapting the Technology Acceptance Model (TAM) framework, this study investigates English teachers' perspectives on the intention to adopt and integrate ChatGPT in their classrooms. This study utilizes quantitative cross-sectional research with 114 respondents answering the online questionnaire. The Structural Equation Modeling (SEM) statistical…

The growing impact and importance of artificial intelligence in society has led to an increasing interest for the potential of artificial intelligence as an educational tool in schools to aid both students and teachers. In this study we investigate digitally skilled K-12 mathematics teachers' (N=85) attitudes towards and expectations on the role…