As education constitutes an essential development standard for individuals and societies, researchers have been exploring the use of artificial intelligence (AI) in this domain and have embedded the technology within it through a myriad of applications. In order to provide a detailed overview of the efforts, this article pays particular attention…

Academic misconduct stemming from file-sharing websites is an increasingly prevalent challenge in tertiary education, including information technology and engineering disciplines. Current plagiarism detection methods (e.g., text matching) are largely ineffective for combatting misconduct in programming and mathematics-based assessments. For these…

This article presents an overview of educational robotics (ER) in primary and preschool education. As ER seems to be gaining popularity for its effectiveness as a learning tool, more research needs to be done in this area. Recent results from ER pilot projects advocate for the integration of ER in K-12 education curricula. On the other hand,…

Multiagent systems (MAS) have been demonstrated to be a useful tool for addressing complex problems by breaking them down into simpler tasks. In this article, we explore the potential of the MAS approach for designing educational robotics learning experiences. Specifically, we aim to identify the pedagogical possibilities and technical…

The rapid changes in technology available for teaching and learning have led to a wide variety of potential tools that can be deployed to support a student's education experience. This article examines the learning interfaces for pedagogical virtual reality (VR) environments, including immersive VR (iVR). It also looks at how microlearning (ML)…

Knowledge tracing is a well-known problem in AI for education, consisting of monitoring how the knowledge state of students changes during the learning process and accurately predicting their performance in future exercises. In recent years, many advances have been made thanks to various machine learning and deep learning techniques. Despite their…

Mastering the visually complex characters of the Chinese language poses significant challenges for students. The situation is even worse in Hong Kong, where students with different backgrounds, including students with/without dyslexia and non-Chinese speaking (NCS) students, are placed in the same class. Interactive design has been proven…

Large language models (LLMs) have significantly advanced smart education in the artificial general intelligence era. A promising application lies in the automatic generalization of instructional design for curriculum and learning activities, focusing on two key aspects: 1) customized generation: generating niche-targeted teaching content based on…

Classroom engagement is a critical factor for evaluating students' learning outcomes and teachers' instructional strategies. Traditional methods for detecting classroom engagement, such as coding and questionnaires, are often limited by delays, subjectivity, and external interference. While some neural network models have been proposed to detect…

Smart learning environments (SLEs) leverage technological developments to enable effective, engaging, and personalized learning. SLEs rely on sensor and advanced interconnectivity capabilities to infer and reason. A natural set of affordances for SLEs are those of multisensory environments (MSEs). MSEs enable humans to make full use of their…

Teacher dashboards provide insights on students' progress through visualizations and scores derived from data generated during teaching and learning activities (e.g., response times and task correctness) to improve teaching. Despite the potential usefulness of enhancing teacher dashboards, and the respective teaching practices, with rich…

Fostering productive engagement within teams has been found to improve student learning outcomes. Consequently, characterizing productive and unproductive time during teamwork sessions is a critical preliminary step to increase engagement in teamwork meetings. However, research from the cognitive sciences has mainly focused on characterizing…

Amid the rapid evolution of artificial intelligence (AI), the intricate model structures and opaque decision-making processes of AI-based systems have raised the trustworthy issues in education. We, therefore, first propose a novel three-layer knowledge tracing model designed to address trustworthiness for an intelligent tutoring system. Each…

The education metaverse (Edu-Metaverse), as a simulated extension of the real world, is an infinite virtual space where learners can build their relationships with others and create interactive content. However, preparing learners to engage fully with Edu-Metaverse remains challenging. As technologies on Edu-Metaverse are new to learners, there is…

The educational metaverse promises fulfilling ambitions of immersive learning, leveraging technology-based presence alongside narrative and/or challenge-based deep mental absorption. Most reviews of immersive learning research were outcomes-focused, few considered the educational practices and strategies. These are necessary to provide theoretical…