Researchers tasked with understanding the effects of educational technology innovations face the challenge of providing evidence of causality. Given the complexities of studying learning in authentic contexts interwoven with technological affordances, conducting tightly-controlled randomized experiments is not always feasible nor desirable. Today,…

In parallel process latent growth curve mediation models, the mediation pathways from treatment to the intercept or slope of outcome through the intercept or slope of mediator are often of interest. In this study, we developed causal mediation analysis methods for these mediation pathways. Particularly, we provided causal definitions and…

Structural equation modeling (SEM) is a statistical method widely used in educational research to investigate relationships between variables. SEM models are typically constructed based on theoretical foundations and assessed through fit indices. However, a well-fitting SEM model alone is not sufficient to verify the causal inferences underlying…

This systematic review examines the application of Partial Least Squares Structural Equation Modeling (PLS-SEM) in educational technology research from 2013 to 2023. Following PRISMA guidelines, 57 studies were selected from Scopus and Web of Science databases. The review process involved rigorous screening, data extraction, and analysis using…

Background/Context: Social network methodology is particularly relevant to the types of social structures found in education research. The current study develops a finite mixture approach for clustering ensembles of networks (NetMix). Following a structural equation modeling framework, NetMix simultaneously estimates a measurement model comprised…

The purpose of this review is to present what we know about paternalistic leadership (PL) in education. Systematic content analysis was adopted to identify the manifest and latent information across 29 identified empirical studies obtained through the core educational leadership and management journals and the two databases, Education Resources…

Background/purpose: It revisits Partial Least Squares Structural Equation Modeling (PLS-SEM) as a robust tool for analyzing non-normal data and small samples, offering predictive modeling advantages. This study also compares the merits, practical applications, and added value of both tools in tackling complicated research issues, notably in…

Multilevel structural equation models (MSEMs) are well suited for educational research because they accommodate complex systems involving latent variables in multilevel settings. Estimation using Croon's bias-corrected factor score (BCFS) path estimation has recently been extended to MSEMs and demonstrated promise with limited sample sizes. This…

Complex data structures are ubiquitous in psychological research, especially in educational settings. In the context of randomized controlled trials, students are nested in classrooms but may be cross-classified by other units, such as small groups. Furthermore, in many cases only some students may be nested within a unit while other students may…

Complex data structures are ubiquitous in psychological research, especially in educational settings. In the context of randomized controlled trials, students are nested in classrooms but may be cross-classified by other units, such as small groups. Further, in many cases only some students may be nested within a unit while other students may not.…

This paper presents a new methodological model termed Airbag Moderation: That the relationship between two variables varies as a function of a third, and that this third variable depends upon one of the others. Airbag Moderation extends and bridges a number of theories and it can be implemented using existing statistical models and software…

Multilevel structural equation modeling (MSEM) allows researchers to model latent factor structures at multiple levels simultaneously by decomposing within- and between-group variation. Yet the extent to which the sampling ratio (i.e., proportion of cases sampled from each group) influences the results of MSEM models remains unknown. This article…

This study explores the role of perceived utility, social influence, and ethical concerns in the adoption of AI-based data analysis tools among academic researchers in China, focusing on differences between public and private universities. The research aims to identify key drivers and barriers influencing the integration of AI technology in…

The relevance and prominence of the partial least squares structural equation modeling (PLS-SEM) method has recently increased in higher education research, especially in explanatory and predictive studies. We therefore first aim to assess previous PLS-SEM applications by providing a systematic review; second, we aim to highlight and summarize…

Part of the evidence used to corroborate school motivation theories relies on modeling methods that estimate cross-lagged effects between constructs, that is, reciprocal effects from one occasion to another. Yet, the reliability of cross-lagged models rests on the assumption that students do not differ in their trajectories of growth over time…