Many technology acceptance models used in education were originally designed for general technologies and later adopted by education researchers. This study extends Davis' technology acceptance model to specifically evaluate educational technologies in higher education, focusing on virtual classrooms. Prior research informed the construction of…

Causal inference is a central topic in education research, although oftentimes it relies on observational studies, which makes causal identification methodologically challenging. This manuscript introduces causal graphs as a powerful language for elucidating causal theories and an effective tool for causal identification analysis. It discusses…

Recently, Bayesian diagnostic classification modeling has been becoming popular in health psychology, education, and sociology. Typically information criteria are used for model selection when researchers want to choose the best model among alternative models. In Bayesian estimation, posterior predictive checking is a flexible Bayesian model…

Chronic stress and burnout are prevalent in Division I athletics, yet there is limited research on job burnout and workplace stress among academic advisors specializing in Division I athletics. This study contributes a deeper understanding of the experiences of Division I athletics academic advisors regarding job burnout and its contributing…

Knowledge tracing (KT) models have been a commonly used tool for tracking students' knowledge status. Recent advances in deep knowledge tracing (DKT) have demonstrated increased performance for knowledge tracing tasks in many datasets. However, interpreting students' states on single knowledge components (KCs) from DKT models could be challenging…

In category learning, a growing body of literature has increasingly focused on exploring the impacts of interleaving in contrast to blocking. The sequential attention hypothesis posits that interleaving draws attention to the differences between categories while blocking directs attention toward similarities within categories [4, 5]. Although a…

The objective of this work was the theoretical modeling of a construct based on teaching practice about the perception that pupils have of difficulties in problem solving (PS) in experimental sciences, specifically physics, to predict pupil performance in PS. The research was carried out with an incidental sample of second year of secondary…

Mediation analysis plays an important role in understanding causal processes in social and behavioral sciences. While path analysis with composite scores was criticized to yield biased parameter estimates when variables contain measurement errors, recent literature has pointed out that the population values of parameters of latent-variable models…

Several concerted movements toward mathematical modeling have been seen in the last decade, reflecting the growing global relationship between the role of mathematics in the context of modern science, technology and real life. The literature has mainly covered the theoretical basis of research questions in mathematical modeling and the use of…

JMP® Pro has introduced a new structural equation modeling (SEM) platform to its suite of multivariate methods of analysis. Utilizing their graphical user interface, JMP Pro has created a SEM platform that is easily navigable for both experienced and novice SEM users. As a new platform, JMP Pro does not have the capacity to implement certain…

The paper delineates three elements of an entrepreneurial university in practice through innovations demonstrating the academic entrepreneurial transition: the "Novum Trivium," Professors of Practice (PoPs) and Link initiatives. The "Novum Trivium" provides a model for the integration of entrepreneurship into a liberal arts…

Cyberbullying has become increasingly prevalent, particularly on social media. There has also been a steady rise in cyberbullying research across a range of disciplines. Much of the empirical work from computer science has focused on developing machine learning models for cyberbullying detection. Whereas machine learning cyberbullying detection…

The nonequivalent groups with anchor test (NEAT) design is widely used in test equating. Under this design, two groups of examinees are administered different test forms with each test form containing a subset of common items. Because test takers from different groups are assigned only one test form, missing score data emerge by design rendering…

Automatic short-answer grading (ASAG) is a key component of intelligent tutoring systems. Deep learning is an advanced method to deal with recognizing textual entailment tasks in an end-to-end manner. However, deep learning methods for ASAG still remain challenging mainly because of the following two major reasons: (1) high-precision scoring…

What is the aim of giftedness? Is the goal to narrow in on the gifts of a select few or to nurture everyone's gifts such that they may be exchanged with each other? Drawing from creativity theory, we emphasize the possible interactive element of giftedness. Current paradigms risk ignoring hidden creativities and for potential to remain in the…