The education sector has been quick to recognize the power of predictive analytics to enhance student success rates. However, there are challenges to widespread adoption, including the lack of accessibility and the potential perpetuation of inequalities. These challenges present in different stages of modeling, including data preparation, model…

The current research used the Proficient Academic Reader (PAR) framework to explore whether reading strategies, task awareness, and motivation predicted college students' literacy skills over and above foundational skills (e.g., decoding, vocabulary). Specifically, the current research investigated the unique contribution of the PAR constructs to…

This study analyzes the predictive factors influencing the entrepreneurial intentions of students at higher education institutions (HEIs) in a peripheral European region. The study includes a sample of 594 students and uses structural equation models for data analysis. The results show that the attitude to behavior and perceived behavioral control…

Purpose: This study aims to investigate factors that could predict the continued usage of e-learning systems, such as the learning management systems (LMS) at a Technical University in Ghana using machine learning algorithms. Design/methodology/approach: The proposed model for this study adopted a unified theory of acceptance and use of technology…

The current research used the Proficient Academic Reader (PAR) framework to explore whether reading strategies, task awareness, and motivation predicted college students' literacy skills over and above foundational skills (e.g., decoding, vocabulary). Specifically, the current research investigated the unique contribution of the PAR constructs to…

We propose a novel approach to address the issue of college student attrition by developing a hybrid model that combines a structural neural network with a piecewise exponential model. This hybrid model not only shows the potential to robustly identify students who are at high risk of dropout, but also provides insights into which factors are most…

Examining the blended learning (b-learning) acceptance is not a new research topic, and it has been tackled by many scholars. Nevertheless, the analysis of information systems (IS) models that are used to study the acceptance of b-learning is regarded as a topic of great importance. To examine these models and afford scholars a holistic view of…

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.…

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…

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…

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…

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…

Objective: Extreme sport participation and injury rates have increased in recent decades. This study aimed to investigate sub-dimensions of impulsivity and sensation seeking that contribute to participation and injury risk in extreme sports. Participants: Data included cross-sectional survey responses from 7,109 college students (Mage=19.68, SD =…