In recent times, Educational Data Mining and Learning Analytics have been abundantly used to model decision-making to improve teaching/learning ecosystems. However, the adaptation of student models in different domains/courses needs a balance between the generalization and context specificity to reduce the redundancy in creating domain-specific…

This study approaches the identification and prediction of transformative research topics by using the concepts of catastrophe theory. Based on the evaluation model of catastrophe theory, 11 indicators were selected for four different aspects: growth rate, economic and social influence, network characteristics and the degree of uncertainty in…

Automatic short answer grading is an important research direction in the exploration of how to use artificial intelligence (AI)-based tools to improve education. Current state-of-the-art approaches use neural language models to create vectorized representations of students responses, followed by classifiers to predict the score. However, these…

Predicting student performance in Massive Open Online Courses (MOOCs) is important to aid in retention efforts. Researchers have demonstrated that video watching features can be used to accurately predict student test performance on video quizzes employing neural networks to predict video test grades from viewing behavior including video searching…

No studies have analyzed the presence of mentoring programs on Canadian postsecondary websites. Filling this crucial gap, this study examined the official websites of 96 Canadian postsecondary institutions -- which accounts for every university in Canada -- to assess the presence of mentoring programs. Results suggest that public institutions (n =…

In the context of education big data, it uses data mining and learning analysis technology to accurately predict and effectively intervene in learning. It is helpful to realize individualized teaching and individualized teaching. This research analyzes student life behavior data and learning behavior data. A model of student behavior…

While prior work has explored the relationship between career-focused educational programming on deviant and criminal behavior for incarcerated and delinquent individuals, there is little empirical evidence as to how career and technical education (CTE) participation in traditional high school settings may link to later interaction with the…

Prosocial behaviours appear very early in a child's development, suggesting that they are the basis for building social relationships. Previous studies have shown that two main factors influence decisions about pro-social behaviour: in-group membership and reciprocity. The main aim of this study was to investigate which of these motives children…

This paper investigated consequences of measurement error in the pretest on the estimate of the treatment effect in a pretest-posttest design with the analysis of covariance (ANCOVA) model, focusing on both the direction and magnitude of its bias. Some prior studies have examined the magnitude of the bias due to measurement error and suggested…

In the context of Bayesian factor analysis, it is possible to compute plausible values, which might be used as covariates or predictors or to provide individual scores for the Bayesian latent variables. Previous simulation studies ascertained the validity of mean plausible values by the mean squared difference of the mean plausible values and the…

Selection methods are commonly used in talent acquisition to predict future job performance and to find the best candidates, but questionnaire-based assessments can be lengthy and lead to candidate fatigue and poor engagement, affecting completion rates and producing poor data. Gamification can mitigate some of these issues through greater…

Purpose: Our audio--vocal system involves a negative feedback system that functions to correct for fundamental frequency (f[subscript 0]) errors in production. Therefore, automatic and opposing responses appear when an unexpected change in voice pitch is present in auditory feedback. This study explores following responses to pitch perturbation in…

The goal of this study was to describe how underlying vocabulary knowledge manifests into vocabulary usage, and in turn, how usage predicts writing quality among adult basic education (ABE) learners. ABE learners were administered tasks that measured vocabulary knowledge, in the forms of both vocabulary breadth and depth. Participants were also…

Objectives: The purpose of this study is to examine the influence of social media engagement, which includes frequency of using social media platforms (FSMP) and social media involvement, on the academic distraction and academic performance of the student. The study further tests the moderating role of attention control on the relationship between…

This work explores how population-based engagement prediction can address cold-start at scale in large learning resource collections. The paper introduces: (1) VLE, a novel dataset that consists of content and video based features extracted from publicly available scientific video lectures coupled with implicit and explicit signals related to…