Moderated multiple regression (MMR) has become a fundamental tool for applied researchers, since many effects are expected to vary based on other variables. However, the inherent complexity of MMR creates formidable challenges for adequately performing power analysis on interaction effects to ensure reliable and replicable research results. Prior…

This study investigates the capabilities of Large Language Models to simulate counselling clients in educational role-plays in comparison to human role-players. Initially, we recorded role-playing sessions, where novice counsellors interacted with human peers acting as clients, followed by role-plays between humans and clients simulated by…

This study examined the implementation of an objective structured clinical examination (OSCE) as a competency-based assessment in a graduate speech-language pathology program. Although OSCEs are widely used in health professions education, they remain less common in speech-language pathology. OSCEs provide opportunities to assess clinical skills…

Despite the availability and potential usefulness of demographic and contextual data in many quantitative studies within engineering education, the preference for ANOVA over regression models remains prevalent, often without clear justification. A mapping review of literature from the EJEE and JEE spanning 2012-2022 identified 98 studies using…

Computational and atmospheric chemistry are two important branches of contemporary chemistry. With the present topical nature of climate change and global warming, it is more crucial than ever that students are aware of and exposed to atmospheric chemistry, with an emphasis on how modeling may aid in understanding how atmospherically relevant…

Learner agency, often understood in terms of self-direction and negotiated engagement, is considered important in technical and vocational education and training (TVET). Yet nurturing and supporting agency is resource-intensive and difficult. In this paper, we consider learner agency for online TVET--a setting where content delivery models can be…

This study builds on the simulation framework of a recent paper by Stanley and Doucouliagos ("Research Synthesis Methods" 2023;14;515--519). S&D use simulations to make the argument that meta-analyses using partial correlation coefficients (PCCs) should employ a "suboptimal" estimator of the PCC standard error when…

Schools and school teachers often focus on content aimed at delaying sexual debut and preventing teenage pregnancy, and address the impacts of risky behaviours on infant health. Infant simulators are increasingly used in health education courses. However, it is unclear how effective this education is. In this review, we examined the evidence for…

Medical simulations allow trainees to work within teams to develop their self-regulated learning (SRL) and socially-shared regulated learning (SSRL) skills (Bransen et al., 2022). Both skillsets help to better prepare medical trainees for the multifaceted challenges inherent in clinical practice. SRL skills are imperative in empowering learners to…

The rapid evolution of digital marketing, characterized by the surge in digital channels and data, has amplified the demand for graduates specialized in digital marketing analytics (DMA). Yet, marketing educators contend with insufficient theoretical guidance and practical pedagogical methods in the course design that aligns with industry…

Model-Implied Instrumental Variable Two-Stage Least Squares (MIIV-2SLS) is a limited information, equation-by-equation, noniterative estimator for latent variable models. Associated with this estimator are equation-specific tests of model misspecification. One issue with equation-specific tests is that they lack specificity, in that they indicate…

Real data are unlikely to be exactly normally distributed. Ignoring non-normality will cause misleading and unreliable parameter estimates, standard error estimates, and model fit statistics. For non-normal data, researchers have proposed a distributionally-weighted least squares (DLS) estimator to combines the normal theory based generalized…

In this study, we introduced a cross-classified multidimensional nominal response model (CC-MNRM) to account for various response styles (RS) in the presence of cross-classified data. The proposed model allows slopes to vary across items and can explore impacts of observed covariates on latent constructs. We applied a recently developed variant of…

Simulations were conducted to establish best practice in hyperparameter optimization and accounting for clustering in Generalized Linear Mixed-Effects Model Trees (GLMM trees). Using data-driven best practices, the relationship between a 9th Grade On-Track to Graduate (9G-OTG) indicator and observed high school graduation within four years was…

The use of high-fidelity simulation and standardized patients (SPs) in occupational therapy (OT) education is expanding. However, the implementation of simulation varies across programs, leading to inconsistent outcomes and research limitations. Furthermore, details on SP use and training are lacking in OT literature. This article aims to provide…