Disengaged responding poses a severe threat to the validity of educational large-scale assessments, because item responses from unmotivated test-takers do not reflect their actual ability. Existing identification approaches rely primarily on item response times, which bears the risk of misclassifying fast engaged or slow disengaged responses.…

This quantitative, correlational study aims to determine if a predictive relationship exists between teacher perceptions of Tennessee's teacher evaluation and the linear combination of teacher gender, years of experience, and school-level taught (elementary, middle, high). Although teachers have recognized the current teacher evaluation system,…

The global pandemic caused by the SARS-CoV-2 virus brought about a true revolution in the predominant teaching-learning processes (i.e., face-to-face environment) that had been implemented up to that point. In this regard, virtual teaching-learning environments (VTLEs) have gained unprecedented significance. The main objectives of our research…

Background: Behavioural intention (BI) has been predicted using other variables by adopting the technology acceptance model (TAM). However, few studies have examined whether BI can predict learning performance. Objectives: The present study used an extended TAM to investigate whether students' BI is a predictor of their listening learning…

How important are learning strategies or personal attributes for learning outside of domain-specific knowledge or twenty-first-century transversal skills when predicting academic success in higher education? To address this question, we conducted a longitudinal study among 1,681 students at one of the leading universities in Hungary. Students took…

The rapid emergence of agentic artificial intelligence (AI) systems represents a paradigm shift in military operations, demanding fundamental transformation of US military education. This paper presents a comprehensive framework for reskilling and redesigning military education to address critical workforce readiness gaps in the era of autonomous…

Purpose: The emerging field of educational data mining provides an opportunity to process large-scale data emerging from higher education institutions (HEIs) into reliable knowledge. The purpose of this paper is to examine factors influencing persistence amongst students enrolled in a Chemistry major at a South African university using enrolment…

Predicting students' learning outcomes is one of the main topics of interest in the area of Educational Data Mining and Learning Analytics. To this end, a plethora of machine learning methods has been successfully applied for solving a variety of predictive problems. However, it is of utmost importance for both educators and data scientists to…

Although collecting data from multiple informants is highly recommended, methods to model the congruence and incongruence between informants are limited. Bauer and colleagues suggested the trifactor model that decomposes the variances into common factor, informant perspective factors, and item-specific factors. This study extends their work to the…

The aim of the study is to identify variables that explain students' academic performance, determine their relative importance, and consequently, develop an index to distinguish advantaged and disadvantaged schools in pursuit of educational equality. By using this index, we intend to build a model for evaluating schools' overall performance based…

Understanding students' privacy concerns is an essential first step toward effective privacy-enhancing practices in learning analytics (LA). In this study, we develop and validate a model to explore the students' privacy concerns (SPICE) regarding LA practice in higher education. The SPICE model considers "privacy concerns" as a central…

Research on the impact of the Sport Education model (SEM) in motivational terms is prolific and consistent; however, studies that jointly address the effects of the SEM on adolescents' motivational, emotional, and well-being dimensions are scarce. This study aimed to examine the effect of a multi-season SEM-based program on self-determined…

Objective: The purpose of this research study is to examine the use of the Andersen Behavioral Model of Health Services Use in predicting how health impacts the academic performance of college students through predisposing, enabling, and need factors. Participants: Data were collected from 428 college students attending a large university in the…

The large rates of students' failure is a very frequent problem in undergraduate courses, being even more evident in exact sciences. Pointing out the reasons of such problem is a paramount research topic, though not an easy task. An alternative is to use Educational Data Mining techniques (EDM), which enables one to convert data from educational…

Social entrepreneurship is a planned behaviour and rapidly gaining its importance in society. This complex process can be understood by studying intention which is the single best predictor of subsequent behaviour. It helps in understanding the reasons behind the actions undertaken and the manner in which potential entrepreneurs decide and act to…