Predicting student performance using educational data is a significant area of machine learning research. However, class imbalance in datasets and the challenge of developing interpretable models can hinder accuracy. This study compares different variations of the Synthetic Minority Oversampling Technique (SMOTE) combined with classification…

Throughout a programming course, students develop various source code tasks. Using these tasks to track students' progress can provide clues to the strengths and weaknesses found in each learning topic. This practice allows the teacher to intervene in learning in the first few weeks of class and maximize student gains. However, the biggest…

Due to the development of deep learning technology, its application in education has received increasing attention from researchers. Intelligent agents based on deep learning technology can perform higher order intellectual tasks than ever. However, the high deployment cost of deep learning models has hindered their widespread application in…

Surface anatomy is an important skill for students in preparation for patient care, and peer examination is often used to teach musculoskeletal and surface anatomy. An alternative pedagogical approach is to use bodies represented in artworks. Represented bodies display fictive anatomy, providing students with the opportunity to apply their…

The open online course (MOOC) platform has seen an increase in usage, and there are a growing number of courses accessible for people to select. An effective method is urgently needed to recommend personalized courses for users. Although the existing course recommendation models consider that users' interests change over time, they often model…

Three quantitative methods are compared for their ability to understand different COVID-19 fatality ratios in 33 OECD countries. Linear regression provides a limited overview without sensitivity to the diversity of cases. Cluster Analysis and Dynamic Patterns Synthesis (DPS) gives scrutiny to the granularity of case similarities and differences,…

Autism has been associated with increased mortality risk among adult populations, but little is known about the mortality risk among children and young people (0-24 years). We used a 15-year nationwide birth cohort study using linked health and non-health administrative data to estimate the mortality risk among Autistic children and young people…

Discrete-time survival analysis (DTSA) models are a popular way of modeling events in the social sciences. However, the analysis of discrete-time survival data is challenged by missing data in one or more covariates. Negative consequences of missing covariate data include efficiency losses and possible bias. A popular approach to circumventing…

This paper is part 4 in a series of workshops that examine the properties of some simple models of vocabulary networks. This Workshop explores how the overall activity level of a vocabulary network can be altered by changing the connections in the network (i.e., by implementing relinking events). The Workshop is linked to an online practice room…

Knowledge tracing aims to model and predict students' knowledge states during learning activities. Traditional methods like Bayesian Knowledge Tracing (BKT) and logistic regression have limitations in granularity and performance, while deep knowledge tracing (DKT) models often suffer from lacking transparency. This paper proposes a…

We propose a simple computational model that describes potential mechanisms underlying the organization and development of the lexical-semantic system in 18-month-old infants. We focus on two independent aspects: (i) on potential mechanisms underlying the development of taxonomic and associative priming, and (ii) on potential mechanisms underlying…

In structural equation modeling, relationships between exogenous and endogenous variables are often assumed to be linear though that is not a requirement. A recent trend in modeling latent interactions and moderations has stimulated further inquiry into nonlinear relationships and the analysis techniques associated with those types of models.…

An individualist (I) or collectivist (C) cultural orientation affects individuals' attitudes, behaviours and values. This study aimed to identify the first-year secondary-school students' I-C profiles and explore their implications for students' trait emotional intelligence (EI), emotions towards school and academic achievement (GPA) throughout…

Matrix decomposition structural equation modeling (MDSEM) is introduced as a novel approach in structural equation modeling, contrasting with traditional structural equation modeling (SEM). MDSEM approximates the data matrix using a model generated by the hypothetical model and addresses limitations faced by conventional SEM procedures by…

Each year, nursing schools spend more on classroom supplies at the nursing lab to help nursing students develop their practical skills before clinical internships. To teach nursing students how to prepare for their experience in the clinic, the nursing school needs to purchase a variety of teaching tools. The objective of this study was to create…