In this paper, we draw on recent research on so-called Fermi problems and situate the fundamental principles underlying this type of tasks and their use from a task design perspective. We use the models and modelling perspective on teaching and learning to elaborate on aspects related to the design of single-use, as well as sequences of, Fermi…

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,…

Measuring innovation is key to realizing innovation in practice. One of the primary reasons why measurement is important stems from the fundamental principle that what is measured is, in turn, what garners attention and action. Systematic measurement of innovation can enable researchers and practitioners to propose and undertake strategic…

Implementing the Blended Learning model was identified as having a major influence on achieving learning objectives in the classroom. Blended learning facilitates different times and types of student learning so students can learn according to their needs. The purpose of this study is to define the blended learning effectiveness used at MTs…

This paper applies the well-known cognitive bias of loss aversion from behavioural economics to student decisions over engagement with mathematically demanding coursework. This bias is shown to predict behaviour that is consistent with mathematics anxiety in a dynamic model of student engagement. It is shown that these forces can imply…

Assessment is viewed as an important means to understand learners' performance in the learning process. A good assessment method is based on high-quality examination questions. However, generating high-quality examination questions manually by teachers is a time-consuming task, and it is not easy for students to obtain question banks. To solve…

This study examined the visual design processes and strategies used by design experts and non-design college students when composing an infographic. All participants created an infographic on a personal computer and were asked to think aloud as they performed the task. The goal was to identify differences in the strategies utilised to produce…

The development of metaknowledge about models (MKM) and metaknowledge about the modelling process (MKP) are important in pre-service science teachers (PSTs) education. MKM refers to knowledge about the model's entities and its purposes, while MKP refers to knowledge about the components and structure of the modelling process. Assessing MKM and MKP…

This paper presents a model of recurrent multinomial sequences. Though there exists a quite considerable literature on modeling autocorrelation in numerical data and sequences of categorical outcomes, there is currently no systematic method of modeling patterns of recurrence in categorical sequences. This paper develops a means of discovering…

A practice that dates back centuries, apprenticeship is a workforce development model that has gained recent attention in the American higher education system. The researcher conducted a review of existing literature that included apprenticeships in higher education and other models of community college workforce development. Existing literature…