This study conducted a bibliometric analysis to investigate the trends and patterns in the application of artificial intelligence (AI) in mathematics education during the period 2020-2025. By analyzing a large dataset of scholarly publications, the study aims to identify the key research areas, influential researchers, and emerging trends in this…

Generative AI is revolutionizing education by enhancing personalized learning, fostering innovation, and transforming traditional teaching methodologies, making it a critical tool for the future of education. This study aims to explore the impact of generative AI (Gen-AI) technologies, focusing on academic and learning performance, publication…

This study explores academics' perspectives on integrating artificial intelligence (AI) into Moroccan higher education (HE). A questionnaire examining perceived benefits, challenges, and influence of demographic factors was distributed to 103 faculty members at the college of Arts and Humanities, Sidi Mohamed Ben Abdellah University in Fez,…

While generative artificial intelligence (AI) tools are gradually being integrated into educational practice, their actual usability in classroom settings remains insufficiently understood. This mixed-methods research was designed as a small-sample pilot study, offering preliminary insights to inform a future large-scale scientific evaluation. The…

Generative artificial intelligence (AI) has the potential to be transformative or to amplify misrepresentations and biases. Generative AI text-to-image production using DALL-E 3 was evaluated for gender and ethnicity biases among Australian academics. DALL-E 3 produced multiple iterations of images using a variety of prompts. Collectively, 81…

This study explores secondary school teachers' perspectives on artificial intelligence (AI)- supported tools through qualitative in-depth interviews with 16 teachers of English as a foreign language in Kazakhstan. The research aimed to understand teachers' views on pedagogy, their knowledge of AI, and their perceptions of its opportunities and…

This study aimed to utilise artificial intelligence (AI) tools to create animations to assess the impact of AI-created cartoons on vocabulary growth and motivation levels among learners. For this purpose, 80 Omani EFL learners with a pre-intermediate level of English proficiency were randomly assigned to an experimental and a control group, each…

Research on artificial intelligence (AI) in education has mainly focused on the measurement instruments relevant to learning about AI and framing AI literacy as learning about AI. The present study's focus, however, was on developing and validating a scale pertinent to learning with generative artificial intelligence (GenAI) in higher education.…

Background: The rapid advancement of artificial intelligence (AI) has raised significant ethical concerns, prompting higher education institutions to reconsider how they prepare future STEM professionals to navigate such concerns responsibly. Despite growing efforts to integrate AI ethics into higher education, a lack of consensus and standardized…

As artificial intelligence (AI) technologies become increasingly integrated into educational settings, understanding the factors that influence teachers' acceptance or resistance to AI is critical, particularly in the STEM education sector. Despite growing interest in AI in education, few studies have examined the psychological and cultural…

The crucial role of teachers' interpersonal communication skills in diverse aspects of second language (L2) education has been endorsed by prior scholarship. Such significance multiplies in artificial intelligence (AI)-mediated education in which interaction fosters understanding and using content and feedback. Nevertheless, the literature has…

Recently, with the advancement in 2D imaging techniques and 3D visual sensors such as LiDAR, RGB-D cameras, etc. The use of 2D and 3D data is ubiquitous in various fields like autonomous driving, AR, and VR. Therefore, we are faced with an ever-increasing demand for approaches toward the automatic processing and analysis of data from multiple…

We propose an innovative, effective, and data-agnostic method to train a deep-neural network model with an extremely small training dataset, called VELR (Voting-based Ensemble Learning with Rejection). In educational research and practice, providing valid labels for a sufficient amount of data to be used for supervised learning can be very costly…

Massive Open Online Courses (MOOCs) make high-quality learning accessible to students from all over the world. On the other hand, they are known to exhibit low student performance and high dropout rates. Early prediction of student performance in MOOCs can help teachers intervene in time in order to improve learners' future performance. This is…

Multimodal imaging studies targeting preschoolers and low-functioning autism spectrum disorder (ASD) patients are scarce. We applied machine learning classifiers to parameters from T1-weighted MRI and DTI data of 58 children with ASD (age 3-6 years) and 48 typically developing controls (TDC). Classification performance reached an accuracy,…