With the popularity of online one-to-one tutoring, there are emerging concerns about the quality and effectiveness of this kind of tutoring. Although there are some evaluation methods available, they are heavily relied on manual coding by experts, which is too costly. Therefore, using machine learning to predict instruction quality automatically…

The complexity of gear concepts, often misunderstood by young children, highlights the need for educational frameworks beyond simple play. To examine the effects of using the prediction, observation, and explanation (POE) model in building block activities, a true experimental design was implemented. A total of 49 preschoolers were randomly…

This dissertation aims to find a correlation between collective teacher efficacy (CTE) and student achievement. Through a quantitative study, the researcher collected data from teachers in high- performing, low socioeconomic elementary schools, specifically those identified as Title I Distinguished Schools in a state in the southeastern region of…

This study elaborates on the pivotal roles of mathematical and statistical models in data-driven predictions in an integrated STEM context using the case of Year 4 students: (?) "a descriptive means" to describe the features of trends and variability of data and (?) "an explanatory means" to explain causal relationships behind…

Self-directed learning (SDL) is a basic individual ability in modern society. It is of great value to explore SDL and its relationship to learners' online learning effectiveness. This study explored the relationships among online learners' personality traits (neuroticism and extraversion), SDL (SDL-approach and SDL-attitude), and perceived online…

In order to promote the growth of contemporary music and the reform of music, this article designs an improved collaborative filtering (CF) algorithm to solve the problem of sparse matrix in traditional recommendation algorithms. The data matrix is dimensionally reduced to find the nearest neighbor, so as to realize personalized recommendation of…

Instructional leaders require timely and predictive data to guide post-pandemic systemic changes. We investigated the predictability of an observational instrument, the Rigor Appraisal, and its association with achievement and other school effectiveness measures in a sample of 53 schools in Illinois. We found that increases in the Rigor Appraisal…

Self-regulated learning (SRL) is an essential skill to achieve one's learning goals. This is particularly true for online learning environments (OLEs) where the support system is often limited compared to a traditional classroom setting. Likewise, existing research has found that learners often struggle to adapt their behaviour to the…

One of the basic tenets of predictive theories of language processing is that of misprediction cost. Post-N400 positive event-related potential (ERP) components are suitable for studying misprediction cost but are not adequately described, especially in older adults, who show attenuated N400 ERP effects. We report a secondary analysis of a…

Automatic grading models are valued for the time and effort saved during the instruction of large student bodies. Especially with the increasing digitization of education and interest in large-scale standardized testing, the popularity of automatic grading has risen to the point where commercial solutions are widely available and used. However,…

Interest in the cognitive precursors of literacy has been increasing in recent years since reading and writing are essential components of functional learning in the first years of schooling and of school success in later educational stages. However, it can be observed that while studies on the relationship between cognitive variables and reading…

The present work focuses on the performance of two types of shrinkage priors--the horseshoe prior and the recently developed regularized horseshoe prior--in the context of inducing sparsity in path analysis and growth curve models. Prior research has shown that these horseshoe priors induce sparsity by at least as much as the "gold…

In this thesis, I use a combination of simulations and empirical data to demonstrate that a small set of structural and functional principles - the basic tenets of predictive coding theory - succinctly accounts for a very wide range of properties in the language processing system. Predictive coding approximates hierarchical Bayesian inference via…

The increasing prevalence of children's attention-deficit hyperactivity disorder (ADHD) and internalizing behaviors requires investigation into putative risk factors. This longitudinal project of 105 preschoolers (54.3% girls; 90% White) examined influences of early life experiences (perinatal stressors, home environment, maternal personality) and…

Student performance modelling is one of the challenging and popular research topics in educational data mining (EDM). Multiple factors influence the performance in non-linear ways; thus making this field more attractive to the researchers. The widespread availability of educational datasets further catalyse this interestingness, especially in…