Assessing achievement is a complex task due to its dependence on multiple factors and the hierarchical structure of educational data, yet surveys like TIMSS offer valuable insights into its determining factors like students' mathematics anxiety. However, disregarding the nested structure of data and ignoring the assumptions of models causes poor…

The rapid emergence of generative artificial intelligence (GenAI) in academic settings has led to growing concerns about its impact on writing and assessment practices. This paper reviews the latest literature on detecting GenAI-generated content and explores the challenges and potential solutions faced by educators. This study identifies various…

The present study employs a systematic thematic analysis of the extant academic literature on the subject of 'technology in reading' to explore its conceptual evolution and educational implications. The PRISMA framework was used to analyse 6081 peer-reviewed articles published between 1944 and July 2025 through bibliometric methods. The findings…

Children's math learning (N = 217; M[subscript age] = 4.87 years; 63% European American, 96% college-educated families) from an intelligent character game was examined via social meaningfulness (parasocial relationships [PSRs]) and social contingency (parasocial interactions, e.g., math talk). In three studies (data collected in the DC area:…

Artificial Intelligence (AI) is attracting a great deal of attention and it is important to investigate the public perceptions of AI and their impact on the perceived credibility of research evidence. In the literature, there is evidence that people overweight research evidence when framed in neuroscience findings. In this paper, we present the…

Designing intelligent services for workplace learning presents a special challenge for researchers and developers of learning technology. One of the reasons is that considering learning as a situated and social practice is nowhere so important than in the case where learning is tightly integrated with workplace practices. The current paper…

This study developed and evaluated machine learning algorithms to predict children's physical activity category from raw accelerometer data collected at the hip. Fifty participants (mean age = 13.9 ± 3.0 y) completed 12 activity trials that were categorized into 5 categories: sedentary (SED), light household activities and games (LHHAG),…

The goal of knowledge tracing is to track the state of a student's knowledge as it evolves over time. This plays a fundamental role in understanding the learning process and is a key task in the development of an intelligent tutoring system. In this paper we propose a novel approach to knowledge tracing that combines techniques from matrix…

Supervised machine learning has become one of the most important methods for developing educational and intelligent tutoring software; it is the backbone of many educational data mining methods for estimating knowledge, emotion, and other aspects of learning. Hence, in order to ensure optimal utilization of computing resources and effective…

Social robot in service is radically changing the ways of performing tasks and it becomes a distinct and valuable nascent. To achieve persist autonomy, robotic systems implement a closed-loop consisting of at least planning, reasoning and acting phases. From the continual loop perspective, this paper presents the ROSPlan framework, as a task…

Background: Though pedagogical artificial agents are expected to play a crucial role in the years to come, earlier studies provide inconsistent results regarding their effect on learning. This might be because their potential for exhibiting subtle nonverbal behaviours we know from human teachers has been untapped. What is more, there is little…

Attrition in longitudinal studies is a major threat to the representativeness of the data and the generalizability of the findings. Typical approaches to address systematic nonresponse are either expensive and unsatisfactory (e.g., oversampling) or rely on the unrealistic assumption of data missing at random (e.g., multiple imputation). Thus,…

Contributions: The Chinese University of Hong Kong (CUHK)-Jockey Club AI for the Future Project (AI4Future) co-created the first pretertiary AI curriculum at the secondary school level for Hong Kong and evaluated its efficacy. This study added to the AI education community by introducing a new AI curriculum framework. The preposttest multifactors…

Institutions and universities have started using e-learning systems to reach the potential students from all over the world by decreasing costs of investments. The speed of technological developments increases the importance of e-learning systems and their technology-based components. E-learning systems also decrease the costs of both institutions…

The continual evolution of employment opportunities in the present industrial era has raised the need for career-long expert advice. Similar to other fields, thankfully technology has come to our rescue in the area of career guidance also. This paper presents a systematic review of Expert Systems (ES) developed for career guidance, course…