Cybersecurity content is typically taught and assessed using Bloom's Taxonomy to ensure that students acquire foundational and higher-order knowledge. In this study we show that when students are given the objectives written in the form of a competency-based statements, students have a more clearly defined outcome and are be able to exhibit their…

Item compromise has long posed challenges in educational measurement, jeopardizing both test validity and test security of continuous tests. Detecting compromised items is therefore crucial to address this concern. The present literature on compromised item detection reveals two notable gaps: First, the majority of existing methods are based upon…

This research study holds practical significance for educators, school administrators, and mental health professionals. The study utilized structural equation modeling on two samples of elementary school students in grades three to five to create and validate condensed versions of the Social-Emotional Health Survey-Primary and the Me and My School…

This open access book maps the role of challenge-based learning (CBL) in the transformation of higher education pedagogy, towards being sector-informed as well as student-driven. CBL democratises the process of learning by repositioning students as drivers, who are empowered to make decisions on course content, assess needs in the real world and…

Most English learners (ELs) eventually gain sufficient English proficiency to be reclassified and receive instruction without linguistic supports. Though well-identified, prior regression discontinuity estimates for the effect of reclassification are estimated too imprecisely to detect policy-relevant effects. Applying a student fixed-effect…

Research on engineering practice and its relationship with engineering education is getting increased attention in the engineering education literature recently. In this article, we present a study of engineering practice in an electrical power utility company that focused specifically on the learning practices of professional engineers. Through…

We propose an innovative, effective, and data-agnostic method to train a deep-neural network model with an extremely small training dataset, called VELR (Voting-based Ensemble Learning with Rejection). In educational research and practice, providing valid labels for a sufficient amount of data to be used for supervised learning can be very costly…

Using cognitive diagnostic modeling (CDM), this study identified subtypes of mathematics learning disability (MLD) based on children's numerical skills and examined the language and spatial precursors of these subtypes. Participants were 99 MLD children and 420 low achievers identified from 1839 Finnish children (966 boys) who were followed from…

Multimodal imaging studies targeting preschoolers and low-functioning autism spectrum disorder (ASD) patients are scarce. We applied machine learning classifiers to parameters from T1-weighted MRI and DTI data of 58 children with ASD (age 3-6 years) and 48 typically developing controls (TDC). Classification performance reached an accuracy,…

In online courses, discussion forums play a key role in enhancing student interaction with peers and instructors. Due to large enrolment sizes, instructors often struggle to respond to students in a timely manner. To address this problem, both traditional machine learning (ML) (e.g., Random Forest) and deep learning (DL) approaches have been…

Many educational and psychological studies have shown that the development of students is generally step-by-step (i.e. ordinal development) to a specific level. This study proposed a novel longitudinal learning diagnosis model with polytomous attributes to track students' ordinal development in learning. Using the concept of polytomous attributes…

This study analyzed the influence of rhetoric in the endorsement text on the willingness of the crowd to participate in citizen science projects. Four categories of endorsers were studied: professors, students, industrial researchers, and amateur researchers. Using 1243 endorsement texts from 543 citizen science projects as the corpus, the effects…

Purpose: This article provides a tutorial introduction to ordinal pattern analysis, a statistical analysis method designed to quantify the extent to which hypotheses of relative change across experimental conditions match observed data at the level of individuals. This method may be a useful addition to familiar parametric statistical methods…

A text semantic classification is an essential approach to recognizing the verbal intention of online learners, empowering reliable understanding, and inquiry for the regulations of knowledge construction amongst students. However, online learning is increasingly switching from static watching patterns to the collaborative discussion. The current…

Development dyslexia (DD) is a common language disorder, that significantly affects children. Despite having ordinary intelligence, dyslexic people struggle with reading, writing, and comprehension in their native tongue. It is still unclear whether dyslexic kids have difficulties with visuo-spatial working memory. Using meta-analysis, this gap…