The application of network meta-analysis is becoming increasingly widespread, and for a successful implementation, it requires that the direct comparison result and the indirect comparison result should be consistent. Because of this, a proper detection of inconsistency is often a key issue in network meta-analysis as whether the results can be…

Systematic reviews are a time-consuming yet effective approach to understanding research trends. While researchers have investigated how to speed up the process of screening studies for potential inclusion, few have focused on to what extent we can use algorithms to extract data instead of human coders. In this study, we explore to what extent…

Bayesian estimations of complex regression models with high-dimensional parameter spaces require advanced priors, capable of addressing both sparsity and multicollinearity in the data. The Dirichlet-horseshoe, a new prior distribution that combines and expands on the concepts of the regularized horseshoe and the Dirichlet-Laplace priors, is a…

While multimodality and multiliteracies has been a concept for 25 years (Kalantzis & Cope, 2023; The New London Group, 1996), research on and application of the concept within text complexity measures has been limited. Attempts to assess multiliteracies and multimodality (Jacobs, 2013; Schmerbeck & Lucht, 2017; Wyatt-Smith & Kimber,…

This dissertation used synthetic datasets, semi-synthetic datasets, and a real-world dataset from an educational intervention to compare the performance of 15 machine learning and multiple imputation methods to estimate the individual treatment effect (ITE). In addition, it examined the performance of five evaluation metrics that can be used to…

It is well known that research quality notions vary across research fields. Despite this, humanities quality notions are often portrayed as deviant or particularly hard to grasp. To some extent, this has a historical explanation, as notions from within the humanities have not been the standards used in the development of research evaluation tools.…

Functional group analysis is an essential part of the curriculum for identifying unknown organic compounds. However, traditional methods of analyzing functional groups use excess reagents and generate a large amount of waste material that is difficult to dispose of. This work is focused on alternative methods for detecting functional groups such…

Parallel analysis has been considered one of the most accurate methods for determining the number of factors in factor analysis. One major advantage of parallel analysis over traditional factor retention methods (e.g., Kaiser's rule) is that it addresses the sampling variability of eigenvalues obtained from the identity matrix, representing the…

Meta-analyses of educational research findings frequently involve statistically dependent effect size estimates. Meta-analysts have often addressed dependence issues using ad hoc approaches that involve modifying the data to conform to the assumptions of models for independent effect size estimates, such as by aggregating estimates to obtain one…

In applied universities, innovation and entrepreneurship education (IEE) has entered a new era of comprehensive integration of professional education. However, as a novel educational activity, the evaluation of professional innovation integration still lacks reasonable appraisal standards. This article is based on the basic theory of the…

Students' talent and potential cannot be served until they are recognized by schools or caregivers. While the field of gifted education has had success in identifying talent among many students with talents in reading and mathematics, those with spatial talents are often overlooked. This article reviews how we might identify spatial talent using…

Students' talent and potential cannot be served until they are recognized by schools or caregivers. While the field of gifted education has had success in identifying many students with talents in reading and mathematics, those with spatial talents are often overlooked. This article reviews how we might identify spatial talent using traditional…

The "LFK" index has been promoted as an improved method to detect bias in meta-analysis. Putatively, its performance does not depend on the number of studies in the meta-analysis. We conducted a simulation study, comparing the "LFK" index test to three standard tests for funnel plot asymmetry in settings with smaller or larger…

The evolving complexity of Virtual Reality (VR) technologies necessitates an in-depth investigation of the VR features and their specific utility. Although VR is utilized across various skill-training applications, its successful deployment depends on both technical maturity and context-specific suitability. A comprehensive understanding of…

Knowledge maps have been widely used in knowledge elicitation and representation to evaluate and guide students' learning. To effectively evaluate maps, instructors must select the most informative map features that capture students' knowledge constructs. However, there is currently no clear and consistent criteria to select such features, as…