Individual participant data meta-analysis (IPDMA) projects obtain, check, harmonise and synthesise raw data from multiple studies. When undertaking the meta-analysis, researchers must decide between a two-stage or a one-stage approach. In a two-stage approach, the IPD are first analysed separately within each study to obtain aggregate data (e.g.,…

This study is a meta-analysis of overall recruitment rate (ORR) in probability-based online panel research. In this study, we included 23 general population probability-based online panels (out of 28 identified and described) covering 15 countries and provided a comprehensive overview of their methodological approaches to recruitment. We…

Learning Analytics (LA) is increasingly applied to assess and foster creativity in educational settings. Whereas existing applications have shown promise in STEM contexts, less is known about the diversity of approaches across educational domains. Therefore, we conducted a scoping review that systematically mapped LA applications for creativity in…

The number of meta-analyses of aggregate data has dramatically increased due to the facility of obtaining data from publications and the development of free, easy-to-use, and specialised statistical software. Even when meta-analyses include the same studies, their results may vary owing to different methodological choices. Assessment of the…

Interest in understanding creativity through Programme for International Student Assessment (PISA) data is on the rise, yet researchers face methodological challenges in synthesizing findings across various constructs, measures, and datasets. Meta-analysis--a valuable methodology for synthesizing quantitative data--remains underutilized in…

When performing an aggregate data meta-analysis of a continuous outcome, researchers often come across primary studies that report the sample median of the outcome. However, standard meta-analytic methods typically cannot be directly applied in this setting. In recent years, there has been substantial development in statistical methods to…

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…

Meta-analysts often encounter missing covariate values when estimating meta-regression models. In practice, ad hoc approaches involving data deletion have been widely used. The current study investigates the performance of different methods for handling missing covariates in meta-regression, including complete-case analysis (CCA), shifting-case…

The potential of data analytics in higher education is well acknowledged. Yet, there is a notable gap in the literature regarding the practical application of theoretical frameworks for its implementation and evaluation. While research has investigated data analytics for personalised learning, student success prediction, and programme assessment,…

Researchers may have at their disposal the raw data of the studies they wish to meta-analyze. The goal of this study is to identify, illustrate, and compare a range of possible analysis options for researchers to whom raw data are available, wanting to fit a structural equation model (SEM) to these data. This study illustrates techniques that…

Technologies and teaching practices can provide a rich log data, which enables learning analytics (LA) to bring new insights into the learning process for ultimately enhancing student success. This type of data has been used to discover student online learning patterns, relationships between online learning behaviors and assessment performance.…

Comparative education is advancing with a growing emphasis on innovative research methodologies; however, integrating these approaches to address complex global education challenges remains difficult. While traditional qualitative methods are valuable, they often fail to capture the multifaceted nature of today's educational landscape. This review…

Scale errors are intriguing phenomena in which a child tries to perform an object-specific action on a tiny object. Several viewpoints explaining the developmental mechanisms underlying scale errors exist; however, there is no unified account of how different factors interact and affect scale errors, and the statistical approaches used in the…

In 2009, John Hattie's book Visible Learning: A Synthesis of over 800 Meta-Analyses Relating to Achievement brought big data to education. In the decade and a half since Visible Learning was originally published it has been aggressively marketed and has now grown into a large suite of branded books, tools, and products. Visible Learning continues…

Individual participant data meta-analyses (IPD-MAs) have several benefits over standard aggregate data meta-analyses, including the consideration of additional participants, follow-up time, and the joint consideration of study- and participant-level heterogeneity for improved diagnostic and prognostic model development and evaluation. However,…