Purpose: Children's enjoyment of school (ES) and academic performance (AP) are two important factors of educational success. This study investigated the mechanism of the effect of school-home communication (SHC) on ES and AP, testing the mediating roles of caregiver participation in school activities (CPSA), interactive learning (IL), and cultural…

This study investigates how individual differences related to creative and verbal fluencies can be differentiated and modelled through the linguistic features that manifest in student writing. Using computational linguistics, we analyzed samples of intrapersonal writing to extract linguistic features that align to specific dimensions of language.…

AI-powered predictive systems have high margins of error. However, data visualisations of algorithmic systems in education and other social fields tend to visualise certainty, thus invisibilising the underlying approximations and uncertainties of the algorithmic systems and the social settings in which these systems operate. This paper draws on a…

Numerous developmental findings suggest that infants and toddlers engage predictive processing during language comprehension. However, a significant limitation of this research is that associative (bottom-up) and predictive (top-down) explanations are not readily differentiated. Following adult studies that varied predictiveness relative to…

Purpose: Dynamic Systems Theory (DST) has been used as a foundational lens through which to observe and understand child development and disorders. Childhood apraxia of speech (CAS) is a motor planning speech disorder that can be difficult to treat. This tutorial outlines how a DST framework can be used to understand the therapy process for…

The use of educational data mining and machine learning to analyse large data sets collected by educational institutions has the potential to discover valuable insights for decision-making. One such area that has gained attention is to predict student performance by analysing large educational data sets. In the relevant literature, many studies…

Student's shift of attention away from a current learning task to task-unrelated thought, also called mind wandering, occurs about 30% of the time spent on education-related activities. Its frequent occurrence has a negative effect on learning outcomes across learning tasks. Automated detection of mind wandering might offer an opportunity to…

Evidence of processing costs for unexpected words presented in place of a more expected completion remains elusive in the eye-movement literature. The current study investigated whether such prediction error costs depend on the source of constraint violation provided by the prior context. Participants' eye movements were recorded as they read…

On 24 June 1994 at Fairchild Air Force Base, during practice for an air show, a low-flying B-52H aircraft banked its wings vertically and crashed. Emphasizing the activity of modeling drag and gravity, these notes examine the possibility of recovery with several models. First, with algebra, historical data lead to a model where in a free fall near…

Resilient students attain high levels of academic achievement despite the presence of chronic socioeconomic disadvantage. Identifying factors that promote resilience in the domain of science is crucial to making equitable and high-quality science education accessible for all students. Rooted in the opportunity-propensity framework, this study…

Complex Machine Learning (ML) models used to support decision-making in peer-to-peer (P2P) lending often lack clear, accurate, and interpretable explanations. While the game-theoretic concept of Shapley values and its computationally efficient variant Kernel SHAP may be employed for this aim, similarly to other existing methods, the latter makes…

Automated scoring is a current hot topic in creativity research. However, most research has focused on the English language and popular verbal creative thinking tasks, such as the alternate uses task. Therefore, in this study, we present a large language model approach for automated scoring of a scientific creative thinking task that assesses…

The Critical Thinking Assessment Test (CAT) is a tool for evaluating students' critical thinking skills in various educational institutions within and outside the United States. While institutions regard the CAT as a high-stakes assessment, students may perceive it as a low-stakes test due to its lack of personal or academic repercussions. This…

Predictive modelling in the education domain can be utilised to significantly improve teaching and learning experiences. Massive Open Online Courses (MOOCs) generate a large volume of data that can be exploited to predict and evaluate student performance based on various factors. This paper has two broad aims. Firstly, to develop and tune several…

In the current educational landscape, where large amounts of data are being produced by institutions, Educational Data Mining (EDM) emerges as a critical discipline that plays a crucial role in extracting knowledge from this data to help academic policymakers make decisions. EDM has a primary focus on predicting students' academic performance.…