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…

Meta-analyses examining dichotomous outcomes often include single-zero studies, where no events occur in intervention or control groups. These pose challenges, and several methods have been proposed to address them. A fixed continuity correction method has been shown to bias estimates, but it is frequently used because sometimes software (e.g.,…

In Bayesian random-effects meta-analysis, the use of weakly informative prior distributions is of particular benefit in cases where only a few studies are included, a situation often encountered in health technology assessment (HTA). Suggestions for empirical prior distributions are available in the literature but it is unknown whether these are…

Component network meta-analysis (CNMA) compares treatments comprising multiple components and estimates the effects of individual components. For network meta-analysis, a standard network plot with nodes for treatments and edges for direct comparisons between treatments is drawn to visualize the evidence structure and the connections between…

The purpose of this systematic review was to survey available measures of creativity for pk12 students for assessments characteristics and reporting of psychometric properties. Using the PRISMA framework, we identified 42 unique articles with 48 assessments meeting our inclusion criteria. Then, two coders independently coded all articles using a…

Many Americans dream of a college degree, but earning one requires time and money. As one solution, prior learning assessment (PLA) documents college-level learning gained outside the classroom for academic credit and can make the difference between earning or not earning a college degree. However, the literature lacks an integrative and…

When meta-analyzing heterogeneous bodies of literature, meta-regression can be used to account for potentially relevant between-studies differences. A key challenge is that the number of candidate moderators is often high relative to the number of studies. This introduces risks of overfitting, spurious results, and model non-convergence. To…

Purpose: Listening is the gateway to learning in the mainstream classroom; however, classrooms are noisy environments, making listening challenging. Therefore, speech-in-noise tests that realistically incorporate the complexity of the classroom listening environment are needed. The aim of this article was to review the speech stimuli, noise…

Impact evaluation and measurement are highly complex and can pose challenges for both social impact providers and funders. Measuring the impact of social interventions requires the continuous exploration and improvement of evaluation approaches and tools. This article explores the available evidence on meta-evaluation--the "evaluation of…

Background/Context: Methodological background: Meta-analysis typically depends on the assumption that true effects follow the normal distribution. While assuming normality of effect "estimates" is often supported by a central limit theorem, normality for the distribution of interventions' "true" effects is a computational…

Background: Self-related information is difficult to ignore and forget, which brings valuable implications for educational practice. Self-referential encoding techniques involve integrating self-referencing cues during the processing of learning material. However, the evidence base and effective implementation boundaries for these techniques in…

Writing and mathematics are essential in academic achievement. In the present study, we investigated whether writing skills and mathematics skills are related and if so, whether their relation is moderated by participants' grade level (a proxy for developmental phase), subskills of mathematics and writing skills, and assessment characteristics…

Context: Computing Education Research (CER) is critical to help the computing education community and policy makers support the increasing population of students who need to learn computing skills for future careers. For a community to systematically advance knowledge about a topic, the members must be able to understand published work thoroughly…

Students' academic achievement is a central predictor of a long list of important educational outcomes, such as access to higher education and socioeconomic success. Prior studies have extensively focused on identifying variables that are related to academic achievement and an important variable in this context appears to be students' personality.…

Recently, machine learning (ML) has evolved and finds its application in higher education (HE) for various data analysis. Studies have shown that such an emerging field in educational technology provides meaningful insights into several dimensions of educational quality. An in-depth analysis of the application of ML could have a positive impact on…