Matrix decomposition structural equation modeling (MDSEM) is introduced as a novel approach in structural equation modeling, contrasting with traditional structural equation modeling (SEM). MDSEM approximates the data matrix using a model generated by the hypothetical model and addresses limitations faced by conventional SEM procedures by…

Each year, nursing schools spend more on classroom supplies at the nursing lab to help nursing students develop their practical skills before clinical internships. To teach nursing students how to prepare for their experience in the clinic, the nursing school needs to purchase a variety of teaching tools. The objective of this study was to create…

In sparse data meta-analyses (with few trials or zero events), conventional methods may distort results. Although better-performing one-stage methods have become available in recent years, their implementation remains limited in practice. This study examines the impact of using conventional methods compared to one-stage models by re-analysing…

Multidimensional measuring instruments are often used in behavioral, social, educational, marketing, and biomedical research. For these scales, the paper discusses how to find the optimal score based on their components that is associated with the highest possible reliability. Within the framework of structural equation modeling, an approach to…

When a researcher proposes an SEM model to explain the dynamics among some latent variables, the real question in model evaluation is the fit of the model's structural part. A composite index that lumps the fit of the structural part and measurement part does not directly address that question. The need for more attention to structural-level fit…

Leadership knowledge is viewed as an essential aspect of overall leadership learning, yet questions abound as to who decides what forms of knowledge are recognized as legitimate. This article reviews existing frames of leadership knowledge along with prior attempts to codify leadership knowledge. We then examine the function of leadership…

This work explores the complex cognitive processes students engage in when addressing contextual tasks requiring linear and exponential models. Grounded within Piagetian constructivism and the Knowledge in Pieces (KiP) epistemological perspective (diSessa, 1993, 2018), this empirical study in a clinical setting develops a Microgenetic Learning…

The integration of Internet technology and the collaborative development of smart classrooms is an essential step for colleges and universities to advance English instruction reform. This study utilized data mining (DM) technology to analyze the learning process in college English smart classrooms. The results indicate that the DM algorithm used…

Digital citizenship should be an embedded component of all curriculum. In order to teach students to be empowered digital citizens, school librarians must use their libraries as safe spaces to explore the layers of digital citizenship. Through classroom discussions, online learning, and unplugged activities, learners can engage with aspects of…

This Perspective article expands on a working memory-dependent dual-process model, originally proposed by Zheng et al., to elucidate individual differences in the testing effect. This model posits that the testing effect comprises two processes: retrieval-attempt and post-retrieval re-encoding. We substantiate this model with empirical evidence…

Communication is commonly viewed as connecting people through conscious symbolic processes. Infants have an immature communication toolbox, raising the question of how they form a sense of connectedness. In this article, we propose a framework for infants' communication, emphasizing the subtle unconscious behaviors and autonomic contingent signals…

Parallel process latent growth curve mediation models (PP-LGCMMs) are frequently used to longitudinally investigate the mediation effects of treatment on the level and change of outcome through the level and change of mediator. An important but often violated assumption in empirical PP-LGCMM analysis is the absence of omitted confounders of the…

Schools are increasingly encouraged to adopt evidence-based or evidence informed interventions and implement them using insights from implementation science. The literature relating to implementation of interventions in schools has focused largely on universal interventions, particularly for social and emotional learning (SEL), which are designed…

Data extraction is a crucial, yet labor-intensive and error-prone part of evidence synthesis. To date, efforts to harness machine learning for enhancing efficiency of the data extraction process have fallen short of achieving sufficient accuracy and usability. With the release of large language models (LLMs), new possibilities have emerged to…

Relying on multiple documents to answer questions is becoming common for both academic and personal inquiry tasks. These tasks often require students to explain phenomena by taking various causal factors that are mentioned separately in different documents and integrating them into a coherent multi-causal explanation of some phenomena. However,…