This study incorporates a random forest (RF) approach to probe complex interactions and nonlinearity among predictors into an item response model with the goal of using a hybrid approach to outperform either an RF or explanatory item response model (EIRM) only in explaining item responses. In the specified model, called EIRM-RF, predicted values…

We evaluate impacts heterogeneity of an Early Childhood Intervention, with respect to the Educational Attainment Polygenic Score (EA4 PGS) constructed from DNA data based on GWAS weights from a European population. We find that the EA4 PGS is predictive of several measures of child development, mother's IQ and, to some extent, educational…

Researchers often make claims regarding the importance of predictor variables in multiple regression analysis by comparing standardized regression coefficients (standardized beta coefficients). This practice has been criticized as a misuse of multiple regression analysis. As a remedy, I highlight the use of dominance analysis and random forests, a…

Highly-automated technologies are increasingly incorporated into existing systems, for instance in advanced car models. Although highly automated modes permit non-driving activities (e.g. internet browsing), drivers are expected to reassume control upon a 'take over' signal from the automation. To assess a person's readiness for takeover,…

The purpose of this quantitative correlational-predictive study was to study if and to what extent emotional intelligence and race, individually and/or combined, predict self-efficacy among teachers teaching online at US-based colleges and universities. The theoretical foundation for this study was based on Salovey and Mayer's 1990 Theory of…

Objectives: Although prior research has uncovered shifts in computer science (CS) students' implicit beliefs about the nature of their intelligence across time, little research has investigated the factors contributing to these changes. To address this gap, two studies were conducted in which the relationship between ineffective self-regulation of…

This study aimed to explore the longitudinal trajectories of teacher burnout and vigour across the school year and whether teacher emotional intelligence (EI) at the beginning of the school year would predict membership in the trajectories. A sample of 311 school teachers (M[subscript age] = 42.40 years ± 9.64 years, aged: 24-61) reported their…

Although numerous studies show that intelligence, measured by various tests, is a significant predictor of school achievement, this cognitive variable can only explain about 50% of the variance. It is also known that communicative language ability represents an important basis for learning subject content in the early period of formal education.…

Background: This study aims to assess how well several machine learning (ML) algorithms predict the physical, social, and mental health condition of university students. Objectives: The physical health measurements used in the study include BMI (Body Mass Index), %BF (percentage of Body Fat), BSC (Blood Serum Cholesterol), SBP (Systolic Blood…

This study presents the Academic Investment Model (AIM) as a novel approach to predicting student academic performance by incorporating learning styles as a predictive feature. Utilizing data from 138 Marketing students across China, the research employs a combination of machine learning clustering methods and manual feature engineering through a…

The integration of educational data mining and deep neural networks, along with the adoption of the Apriori algorithm for generating association rules, focuses to resolve the problem of misdirection of students in the university, leading to their failure and dropout. This is reached through the development of an intelligent model that predicts the…

As artificial intelligence (AI) technologies become increasingly integrated into educational settings, understanding the factors that influence teachers' acceptance or resistance to AI is critical, particularly in the STEM education sector. Despite growing interest in AI in education, few studies have examined the psychological and cultural…

Introduction: Teaching is an emotionally challenging profession, sometimes resulting in high levels of stress, burnout, and teacher burnout. It has often been claimed that certain emotional competencies such as emotional intelligence can reduce feelings of burnout in teachers. Method: Method. A descriptive and correlational analysis was made of…

Emotional intelligence, self-concept, academic stress and personality have been associated with university students' academic performance. The aim of this paper was to study the relationship between self-concept and academic stress in Education students from different Universities in the region of Andalusia (Spain), analysing the mediational role…

This research aims to design a helpful methodology for estimating universities' relative impact on students as a sustainability factor in higher education. To this end, the research methodology implemented a two-stage approach. The first stage involves the relative efficiency analysis of the study units using Fuzzy Data Envelopment Analysis. The…