As an excellent means of improving students' effective learning, knowledge tracking can assess the level of knowledge mastery and discover latent learning patterns based on students' historical learning evaluation of related questions. The advantage of knowledge tracking is that it can better organize and adjust students' learning plans, provide…

The ability to predict upcoming events is essential in infancy because it enables babies to process information optimally and have successful goal-directed interactions with their environment. In this article, we examine how infants generate predictions in perception, cognition, and action, and address whether and how their predictions are…

The recommendation is an active area of scientific research; it is also a challenging and fundamental problem in online education. However, classical recommender systems usually suffer from item cold-start issues. Besides, unlike other fields like e-commerce or entertainment, e-learning recommendations must ensure that learners have the adequate…

Projecting confidence during conversation or presentation is a critical skill. To effectively display confidence, speakers must employ a blend of verbal and non-verbal signals. A predictive model that leverages rich multimodal cues to measure a speaker's confidence must also mitigate biases that develop through data labelling practices, inherent…

Interest in the gender gap in the physical sciences has been ongoing for a number of years. This study aimed to explore differences in gender based on self-perception. The use of a post-examination survey was used to examine the role of gender in grade perception in chemistry courses over a several-year period. This included courses for…

This systematic review sheds light on the role of ontologies in predicting achievement among online learners, in order to promote their academic success. In particular, it looks at the available literature on predicting online learners' performance through ontological machine-learning techniques and, using a systematic approach, identifies the…

Student feedback literacy is emphasised in recent literature as a critical attribute of university graduates. Although the impacts of epistemic beliefs on specific dimensions of student feedback literacy have been discussed in the literature, there is still a lack of quantitative research to investigate the strength of such impacts. This study…

Predicting academic performance in Educational Data Mining has been a significant research area. This involves utilizing machine learning techniques to analyze data from educational settings. Predicting student academic performance is a complex task due to the influence of multiple factors. This research uses supervised machine-learning approaches…

Knowledge tracing (KT) models predict how students will perform on future interactions, given a sequence of prior responses. Modern approaches to KT leverage "deep learning" techniques to produce more accurate predictions, potentially making personalized learning paths more efficacious for learners. Many papers on the topic of KT focus…

In Computer Science (CS) education, understanding factors contributing to students' programming difficulties is crucial for effective learning support. By identifying specific issues students face, educators can provide targeted assistance to help them overcome obstacles and improve learning outcomes. While identifying sources of struggle, such as…

Rhythm production requires the integration of perceptual predictions and performance monitoring mechanisms to adjust actions, yet the role of auditory prediction remains underexplored. To address this, electroencephalography was recorded from 70 non-musicians as they synchronized with and reproduced rhythms containing notes of varying…

Purpose: The challenges of language assessment in bilinguals include a lack of assessment tools and bilingual speech-language pathology services. Additionally, the weighting of subtests in standardized tests has not been empirically explored to maximize sensitivity and specificity. Language exposure might also inform the decision to diagnose…

Purpose: Predictive coding theories posit that autism is characterized by an over-adjustment to prediction errors, resulting in frequent updates of prior beliefs. Atypical weighting of prediction errors is generally considered to negatively impact the construction of stable models of the world, but may also yield beneficial effects. In a novel…

The nodules on the roots of soybeans provide N that the plant uses for growth and development. The goal of this study is to observe if the number of nodules on the taproot, volume of nodules on the taproot, the total number of nodules, or the number of nodules on the secondary roots in the early growth stages of soybeans have a significant…

This paper looks at the tension between the desire to claim predictive ability for Agent-Based Models (ABMs) and its extreme difficulty for social and ecological systems, suggesting that this is the main cause for the continuance of a rhetoric of prediction that is at odds with what is achievable. Following others, it recommends that it is better…