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…

As digital integration transforms modern society, equipping young learners with computational thinking (CT) skills has become an essential educational goal. However, many education systems face challenges in adapting curricula to include CT, particularly in early childhood education where resources, teacher preparedness, and instructional design…

Design-based research (DBR) has proven to be a robust methodology for transforming educational practice through a systematic cycle of analysis, design, development, and real-world implementation. Its distinctive strength lies in fostering close collaboration between researchers and educators within authentic learning contexts, producing design…

This dissertation is aimed at investigating the impact of missing data and evaluating the performance of five selected methods for handling missing responses in the implementation of Cognitive Diagnostic Models (CDMs). The five methods are: a) treating missing data as incorrect (IN), b) person mean imputation (PM), c) two-way imputation (TW), d)…

Methods for meta-analyzing single-case designs (SCDs) are needed to inform evidence-based practice in clinical and school settings and to draw broader and more defensible generalizations in areas where SCDs comprise a large part of the research base. The most widely used outcomes in single-case research are measures of behavior collected using…

Taped problems is an intervention strategy for addressing mathematics fluency that has been evaluated in multiple single-case design studies. Although its efficacy has been supported in individual studies, no comprehensive quantitative synthesis has been conducted on taped problems. The purpose of this study was to synthesize the literature that…

The current study aimed to review studies on computational thinking (CT) indexed in Web of Science (WOS) and ERIC databases. A thorough search in electronic databases revealed 96 studies on computational thinking which were published between 2006 and 2016. Studies were exposed to a quantitative content analysis through using an article control…

The purpose of this paper is to provide an easy template for the inclusion of the Bayes factor in reporting experimental results, particularly as a recommendation for articles in the "Journal of Problem Solving." The Bayes factor provides information with a similar purpose to the "p"-value--to allow the researcher to make…

Apprentice and trainee data are reported by the State and Territory Training Authorities to National Centre for Vocational Education Research (NCVER) on a quarterly basis, starting at the September quarter of 1994. The set of data submitted that quarter is referred to as Collection 1. The sets of data submitted in subsequent quarters are referred…

This methodological brief introduces basic procedures and issues for conducting a high-quality meta-analysis in gifted education. Specifically, we discuss issues such as how to select a topic and formulate research problems, search for and identify qualified studies, code studies and extract data, choose and calculate effect sizes, analyze data,…

It is common in regression discontinuity analysis to control for high order (third, fourth, or higher) polynomials of the forcing variable. We argue that estimators for causal effects based on such methods can be misleading, and we recommend researchers do not use them, and instead use estimators based on local linear or quadratic polynomials or…

Two-phase designs in epidemiological studies of autism prevalence introduce methodological complications that can severely limit the precision of resulting estimates. If the assumptions used to derive the prevalence estimate are invalid or if the uncertainty surrounding these assumptions is not properly accounted for in the statistical inference…

Missing data are a common occurrence in survey-based research studies in education, and the way missing values are handled can significantly affect the results of analyses based on such data. Despite known problems with performance of some missing data handling methods, such as mean imputation, many researchers in education continue to use those…

Nearly all quantitative analyses in higher education draw from incomplete datasets-a common problem with no universal solution. In the first part of this paper, we explain why missing data matter and outline the advantages and disadvantages of six common methods for handling missing data. Next, we analyze real-world data from 5,905 students across…

Apprentice and trainee data are reported by the State and Territory Training Authorities to NCVER (National Centre for Vocational Education Research) on a quarterly basis, starting at the September quarter of 1994. The set of data submitted that quarter is referred to as Collection 1. The sets of data submitted in subsequent quarters are referred…