The ability to comprehend reading material is a crucial skill for academic and professional success, yet many students struggle with it, negatively impacting their academic performance. This study aimed to assess the effectiveness of AI-based personalised reading platforms in improving reading comprehension among senior high school students. The…

This study aimed at examining the performance of generative artificial intelligence to extract argumentation elements from text. Thus, the researchers developed a web-based framework to provide automated assessment and feedback relying on a large language model, ChatGPT. The results produced by ChatGPT were compared to human experts across…

Current student-centred, multilingual, active teaching methodologies require that teachers have continuous access to texts that are adequate in terms of topic and language competence. However, the task of finding appropriate materials is arduous and time consuming for teachers. To build on automatic readability assessment research that could help…

To address needs in one US state to provide a professional development micro-credential for tens of thousands of educators, we automated an assignment scoring workflow in an online course by developing and refining an AI model to scan submitted assignments and score them against a rubric. This article outlines the AI model development process and…

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…

The pandemic has indeed provided students and teachers worldwide with the experience of technology-infused teaching. Even though the pandemic is almost over, the utilization of technology in mathematics education is still needed and inseparable. Relying on cross-sectional design and phenomenological approach, this research investigates senior high…

The advances of machine learning (ML) in scientific discovery (SD) reveal exciting opportunities to utilize it as a cross-cutting tool for inquiry-based learning in K-12 STEM classrooms. There are, however, limited efforts on providing teachers with sufficient knowledge and skills to integrate ML into teaching. Our study addresses this gap by…

This paper presents a proposal of specific curriculum in Artificial Intelligence (AI) for high school students, which has been organized as a two-year subject. The curriculum was designed based on two premises. The first one is that, although the proposal is targeted to scientific programmes, the involved students and teachers do not have any…

In this study, classifications were made from the data obtained from the Health-Related Physical Fitness Report cards and BMIs of students through data mining methods, artificial neural networks, and decision trees models. Then the classification performances of both models were compared. The body weight and height measurements of the students in…

This article reports on a case study from a larger project exploring ways in which online citizen science projects can enhance students' learning in science and in digital technology. In this case, two teachers integrated the digital technology curriculum with the science capability "interpreting representations" using the engaging…

Early detection is key to intervening with students diagnosed with a specific learning disorder (SLD), which includes problems with spelling, grammar, punctuation, and clarity and organization of written expression, as a means of preventing potential negative consequences from this disorder. Deep convolutional neural networks (CNNs) perform better…

Artificial intelligence is the unification of philosophy, cognitive science, mathematics, neurophysiology, psychology, computer science, information theory, cybernetics, and uncertainty theory. Therefore, it is feasible and necessary to utilize STEAM (Science, Technology, Engineering, Liberal Arts, and Mathematics) education to learn artificial…

Machine learning (ML) methods for causal inference have gained popularity due to their flexibility to predict the outcome model and the propensity score. In this article, we provide a within-group approach for ML-based causal inference methods in order to robustly estimate average treatment effects in multilevel studies when there is cluster-level…

The problem behind our research that was investigated was the evaluation of an artificial intelligence in education tool, namely ASSISTments by seventy one science and technology students in a small city. The objective was to find to what extent the students assimilate this tool. The data collection and instrumentation were done by the tool…

In the context of formative assessment in classrooms, the incorporation of automated evaluation (AE) systems and teachers' interactions with them hold significant importance. This study aimed to investigate the cognitive processes of pre-service teachers as they engaged with an AE system. We developed an unsupervised learning-based AE system, the…