Study success in Higher Education is of primary importance in the European policy agenda. Yet, given the diverse educational landscape across countries and institutions, more coordinated action is needed to gain a more solid knowledge of the dropout phenomenon. This study aims to gain a better insight into students' dropout based on an integrated…

In sample survey analysis, accurate population mean estimation is an important task, but traditional approaches frequently ignore the intricacies of real-world data, leading to biassed results. In order to handle uncertainties, indeterminacies, and ambiguity, this work presents an innovative approach based on neutrosophic statistics. We proposed…

Bayesian Knowledge Tracing (BKT) is a well-established model for formative assessment, with optimization typically using expectation maximization, conjugate gradient descent, or brute force search. However, one of the flaws of existing optimization techniques for BKT models is convergence to undesirable local minima that negatively impact…

The nature of teaching and learning has evolved over the years, especially as technology has evolved. Innovative application of educational analytics has gained momentum. Indeed, predictive analytics have become increasingly salient in education. Considering the prevalence of learner-system interaction data and the potential value of such data, it…

Inclusive education is a key goal of modern educational reforms, yet its implementation is complex. This study examines the roles of teacher attitudes and self-efficacy in predicting their intentions to use inclusive practices across five western countries: Canada, Germany, Greece, Italy, and Switzerland. The study identified both significant…

The American Family Health Study (AFHS) collected family health and fertility data from a national probability sample of persons aged 18-49 between September 2021 and May 2022, using web and mail exclusively. In July 2022, we surveyed AFHS respondents and gauged their willingness to become part of a national web panel that would create novel…

Student attrition represents one of the greatest challenges facing U.S. postsecondary institutions. Approximately 40 percent of students seeking a bachelor's degree do not graduate within 6 years; among nontraditional students, who make up half of the undergraduate population, dropout rates are even higher. In this study, we developed a machine…

Traditionally, researchers employ human raters for scoring responses to creative thinking tasks. Apart from the associated costs this approach entails two potential risks. First, human raters can be subjective in their scoring behavior (inter-rater-variance). Second, individual raters are prone to inconsistent scoring patterns…

Knowledge of results (KR), particularly its informational role, has often been regarded as redundant for learning interception-like tasks, such as coincidence-anticipation timing tasks. However, it is possible that the KR's guiding effect might be detrimental to motor adaptation, instead of only redundant, leading to a dependency on KR and…

Caregivers play an outsized role in shaping early life experiences and development, but we often lack mechanistic insight into "how" exactly caregiver behavior scaffolds the neurodevelopment of specific learning processes. Here, we capitalized on the fact that caregivers differ in how predictable their behavior is to ask if infants'…

Background: There is growing interest in research understanding the individual-specific predictors of child callous-unemotional (CU) traits, particularly in early childhood. Objective: This study reviewed evidence from studies that investigated the relationship between early child temperament factors (between 0 and 3 years) and CU traits in…

Higher education institutions need to be responsible for understanding the characteristics and qualities of learners who decide to take courses with them; online vs. on-campus and what it takes to keep them learning at an institution. Taking heed and modifying structures, communications, and services will help learners and institutions in this…

Lagged dependent variables (LDVs) are often used as predictors in ordinary least squares (OLS) models in the social sciences. Although several estimators are commonly employed, little is known about their relative merits in the presence of classical measurement error and different longitudinal processes. We assess the performance of four commonly…

This article provides an overview of different computational options for inference following normal theory maximum likelihood (ML) estimation in structural equation modeling (SEM) with incomplete normal and nonnormal data. Complete data are covered as a special case. These computational options include whether the information matrix is observed or…

This article provides evidence about predictive relationships between features of community college interventions and their impacts on student progress. This evidence is based on analyses of student-level data from large-scale randomized trials of 39 (mostly) community college interventions. Specifically, the evidence consistently indicates that…