The essence of human intelligence lies in its ability to learn continuously, accumulating past knowledge to aid in future learning and problem-solving endeavors. In contrast, the current machine learning paradigm often operates in isolation, lacking the capacity for continual learning and adaptation. This deficiency becomes apparent in the face of…

Based on Folk theory, Media Equation, and AI literacy research, the study constructed an interview outline and selected 72 students in 4th and 5th grade in three primary schools located in the Minhang and Putuo districts of Shanghai (two in the Minhang district and one in the Putuo district) as the study participants for focus group interviews.…

Academic integrity fosters a culture of honesty, trust, and respect within the educational community. Evidence indicates that manual plagiarism checks through human judgment remain prevalent in undergraduate theses, terminal assignments, and group projects in developing countries. To fill this gap, we engaged with students and staff of the Kwame…

Data visualization is a powerful strategy for using graphics to represent data for effective communication and analysis. Unfortunately, creating effective data visualizations is a challenge for both novice and expert design users. The task often involves an iterative process of trial and error, which by its nature, is time-consuming. Designers…

The personalization of curriculum plays a pivotal role in supporting students in achieving their unique learning goals. In recent years, researchers have dedicated efforts to address the challenge of personalizing curriculum through diverse techniques and approaches. However, it is crucial to acknowledge the phenomenon of student forgetting, as…

Generative AI presents significant opportunities for instructional designers to create content and personalize online learning environments. Alongside its benefits, generative AI also poses ethical considerations and potential risks, such as perpetuating biases or disrupting the learning process. Navigating these complexities requires an approach…

We develop a "latent variable forest" (LV Forest) algorithm for the estimation of latent variable scores with one or more latent variables. LV Forest estimates unbiased latent variable scores based on "confirmatory factor analysis" (CFA) models with ordinal and/or numerical response variables. Through parametric model…

Existing systems for automating the assessment of risk-of-bias (RoB) in medical studies are supervised approaches that require substantial training data to work well. However, recent revisions to RoB guidelines have resulted in a scarcity of available training data. In this study, we investigate the effectiveness of generative large language…

The rapid development of generative artificial intelligence (GenAI) technologies has sparked widespread discussions about their potential applications in higher education. However, little is known about how students from various disciplines engage with GenAI tools. This study explores undergraduate students' GenAI knowledge, usage intentions, and…

This article analyses how ChatGPT may be used in L2 pronunciation teaching and learning, especially when explicit pronunciation instruction is integrated into a communicative approach to language teaching. The possible use of ChatGPT for production practice, listening practice, and obtaining explanations and examples of target L2 features is…

Evaluating the quality of university exam papers is crucial for universities seeking institutional and program accreditation. Currently, exam papers are assessed manually, a process that can be tedious, lengthy, and in some cases, inconsistent. This is often due to the focus on assessing only the formal specifications of exam papers. This study…

In learning analytics and in education at large, AI explanations are always computed from aggregate data of all the students to offer the "average" picture. Whereas the average may work for most students, it does not reflect or capture the individual differences or the variability among students. Therefore, instance-level…

Early detection of autism spectrum condition is crucial for children to maximally benefit from early intervention. The study examined a machine learning model predicting the increased likelihood for autism from wellness records from 0 to 24 months. The study included 591,989 non-autistic and 12,846 autistic children. A gradient boosting model with…

This study employs advanced data mining techniques to investigate the DASS-42 questionnaire, a widely used psychological assessment tool. Administered to 680 students at Necmettin Erbakan University's Ahmet Kelesoglu Faculty of Education, the DASS-42 comprises three distinct subscales--depression, anxiety and stress--each consisting of 14 items.…

Whether machine learning algorithms effectively predict college students' course outcomes using learning management system data is unknown. Identifying students who will have a poor outcome can help institutions plan future budgets and allocate resources to create interventions for underachieving students. Therefore, knowing the effectiveness of…