The use of advanced quantitative methods within mixed methods research has been investigated in a limited capacity. In particular, hierarchical linear models are a popular approach to account for multilevel data, such as students within schools, but its use and value as the quantitative strand in a mixed methods study remains unknown. This article…

Cluster Randomized Trial (CRT) designs are inherently multilevel and reflect the hierarchical structure of schools and the wider education system. To capture this multilevel nature, CRTs are commonly analysed using multilevel (or hierarchical) linear models. It is fairly common for CRT designs and analyses to include school and individual/pupil…

To plan cluster-randomized trials with sufficient statistical power to detect intervention effects on student achievement, researchers need multilevel design parameters, including measures of between-classroom and between-school differences and the amounts of variance explained by covariates at the student, classroom, and school level. Previous…

This article presents 3 standardized effect size measures to use when sharing results of an analysis of mediation of treatment effects for cluster-randomized trials. The authors discuss 3 examples of mediation analysis (upper-level mediation, cross-level mediation, and cross-level mediation with a contextual effect) with demonstration of the…

Learning paths have the potential to play an important role in the way educators serve their learners. Empirical research about learning paths is scarce, particularly in a secondary education setting. The present quasi-experimental study took place in the context of a biology course involving 360 secondary school students. A 2 × 2 factorial…