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…

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 study highlights the role and importance of advanced, machine learning-driven predictive models in enhancing the accuracy and timeliness of identifying students at-risk of negative academic outcomes in data-driven Early Warning Systems (EWS). K-12 school districts have, at best, 13 years to prepare students for adulthood and success. They…

Purpose: Anomia, or word-finding difficulty, is a prevalent and persistent feature of aphasia, a neurogenic language disorder affecting millions of people in the United States. Anomia assessments are essential for measuring performance and monitoring outcomes in clinical settings. This study aims to evaluate the reliability of response time (RT)…

Purpose: This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability. Design/methodology/approach: The real-world…

Background: Dyslexia is a specific reading disability characterized by word recognition difficulties that can qualify a student for special education services under the "Individuals with Disabilities Education Act" (IDEA; 2004; Yudin, 2015). As of 2024, 49 US states have legislation defining dyslexia and enumerating for schools…

The present study aimed to validate a Spanish-version of the Basic Psychological Needs at Work Scale (BPNWS-Sp) and to examine the associations between needs satisfaction and engagement and burnout in secondary education teachers. Using a sample of 584 secondary education teachers, the results supported the three-factor model, composite…

Dynamic assessment methods, initially developed by Feuerstein in the 1970s, have been recommended as being more equitable for identifying the academic abilities of students who may not perform well on traditional assessments due to these learners' cultural, linguistic, or economic differences from the population for whom the traditional measures…

Critically examining common statistical approaches and their strengths and weaknesses is an important step in advancing recreation and leisure sciences. To continue this critical examination and to inform methodological decision making, this study compared three approaches to determine how alternative approaches may result in contradictory…

Federal education legislation continues to emphasize the role of assessment in elementary and secondary schools. Perhaps most prominently, the Elementary and Secondary Education Act (ESEA), as amended by the Every Student Succeeds Act (ESSA; P.L. 114-95), requires the use of test-based educational accountability systems in states and specifies the…