In this Methods Showcase Article, we illustrate mixed-effects modeling with a multinomial dependent variable as a means of explaining complexities in language. We model data on future-time reference in second language Spanish, which consists of a nominal dependent variable that has three levels, measured over 73 participants. We offer step-by-step…

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…

Academic institutions today are experiencing a legion of security risks that are increasingly impeding their mission of producing high-quality graduates, guarding reason and educational integrity, and ultimately advancing human civilisation. The Enterprise Security Risk Management (ESRM) model represents a potential solution to the dynamic threats…

The world's move to a global economy has an impact on the high rate of student academic failure. Higher education, as the affected party, is considered crucial in reducing student academic failure. This study aims to construct a prediction (predictive model) that can forecast students' time to graduation in developing countries such as Indonesia,…

This quantitative study investigates the predictive power of machine learning (ML) models on degree completion among adult learners in higher education, emphasizing the enhancement of data-driven decision-making (DDDM). By analyzing three ML models - Random Forest, Gradient-Boosting machine (GBM), and CART Decision Tree - within a not-for-profit,…

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…

Text is a burgeoning data source for psychological researchers, but little methodological research has focused on adapting popular modeling approaches for text to the context of psychological research. One popular measurement model for text, topic modeling, uses a latent mixture model to represent topics underlying a body of documents. Recently,…

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 article will address predictors of success for online students. A survey questionnaire was used to gather data concerning online students' social and educational readiness levels at a four-year private university in the Midwestern United States. Of the 4,050 potential participants, 250 (6.23%) responded to the survey. Stepwise regression…

Purpose: The direction of causality between job satisfaction and job performance (known as the holy grail of industrial psychologists) is undetermined and related research findings in different organizational contexts are mixed. Based on the ample literature, mainly from Western countries, on the relationship between job satisfaction and job…

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…

Student dropout is a major concern in studies investigating retention strategies in higher education. This study identifies which variables are important to predict student dropout, using academic data from 3583 first-year students on the Business Administration (BA) degree at the University of Barcelona (Spain). The results indicate that two…

Individuals with autism increasingly enroll in universities, but little is known about predictors for their success. This study developed predictive models for the academic success of autistic bachelor students (N = 101) in comparison to students with other health conditions (N = 2465) and students with no health conditions (N = 25,077). We…