Background: The application of generative artificial intelligence (GenAI) in education has been deepening. However, at the same time, behaviours that jeopardise academic health, such as learners' over-reliance on generative AI and massive plagiarism of generated content of generative AI in essay writing, have begun to emerge, and the issue of…

Background: ChatGPT, as a cutting-edge technology in education, is set to significantly transform the educational landscape, raising concerns about technological ethics and educational equity. Existing studies have not fully explored learners' intentions to adopt artificial intelligence generated content (AIGC) technology, highlighting the need…

Background: Many researchers work on the design and development of multimodal collaboration support systems with AI, yet very few of these systems are mature enough to provide actionable feedback to students in real-world settings. Therefore, a notable gap exists in the literature regarding students' perceptions of such systems and the feedback…

Background: Feedback is an essential part of the educational process as it enriches students' learning experiences, provides information about their current performance, shows them what is lacking in achieving goals, and provides guidance on the strategies needed to achieve those goals. Teachers, especially in crowded classrooms, often have…

Background: The digital literacy landscape has undergone significant changes over the last 5 years, from the impact of the COVID-19 pandemic to the emergence of Artificial Intelligence (AI) technologies. The COVID-19 pandemic hastened the necessity for advanced digital skills for remote work and online collaboration, while the current AI era…

Background: Feedback as one of the most influential factors for learning has been subject to a great body of research. It plays a key role in the development of educational technology systems and is traditionally rooted in deterministic feedback defined by experts and their experience. However, with the rise of generative AI and especially large…

Background: Generative artificial intelligence (GenAI) chatbots extend transformative impact in higher education. Current research requires more comprehensive evaluations of the collaborative learning fostered by students and GenAI chatbots. However, existing articles have rarely explored the dynamic process of student--AI collaboration in higher…

Background: The creation of Intelligent Supervision Platforms in universities leverages Big Data for robust monitoring and decision-making, which significantly enhances overall efficiency and adaptability in educational environments. Objectives: This research focuses on evaluating how Big Data-driven Intelligent Supervision Platforms in…

Background: Artificial intelligence has been reshaping many industries, and education is no exception. When ChatGPT burst onto the scene in late 2022, it ignited conversations among educators and researchers alike. Despite growing interest and experimentation with this technology in university classrooms, the field has been missing a comprehensive…

Background Study: The combination of artificial intelligence (AI) and foreign language learning is emerging as a significant trend in language education. Objectives: This study aimed to investigate the impact of technology acceptance, attitude and motivation on behavioural intentions regarding the use of AI in language learning. Methods:…

Background: Research into enhancing the effectiveness of information delivery in asynchronous video lectures remains sparse. This study analyzes the nonverbal teaching behaviours in asynchronous online videos, drawing comparisons between pre-service and in-service teachers (ITs). Objectives: This research primarily aims to juxtapose the nonverbal…

Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…

Background: This study aims to assess how well several machine learning (ML) algorithms predict the physical, social, and mental health condition of university students. Objectives: The physical health measurements used in the study include BMI (Body Mass Index), %BF (percentage of Body Fat), BSC (Blood Serum Cholesterol), SBP (Systolic Blood…

Background: Online collaborative learning has been broadly applied in the field of higher education. Nevertheless, not all types of collaborative learning can produce the desired learning results. Objectives: To facilitate online collaborative learning, the present study proposed an innovative artificial intelligence-enabled group cognitive…

Background: This study explored the factors that influence the balance between academic integrity and the effective use of GenAI tools in higher education. It focused on the role of institutional guidelines in enhancing the responsible use of GenAI technologies to enhance academic integrity. Objectives: The study was theoretically grounded in the…