Given the increased focus of educational research on what works for whom and under what circumstances over the last decade, educational researchers are increasingly turning toward mixture models to identify heterogeneous subgroups among students. Such data are inherently nested, as students are nested within classrooms and schools. Yet there has…

Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in…

There is an increasing number of datasets with many participants, variables, or both, in education and other fields that often deal with large, multilevel data structures. Once initial confirmatory hypotheses are exhausted, it can be difficult to determine how best to explore the dataset to discover hidden relationships that could help to inform…

This case study considers how a non-equivalent control group design was used in a PhD study examining the impact of a multiple intelligence teaching approach on student engagement and learning. Two groups of second year undergraduate nursing students undertook the study: a treatment group (n = 26) and a control group (n = 18). The intervention for…

Explains genetic algorithms, a means of generating logical rules that predict one variable by relating it to others. Describes how they can be applied to analysis of survey data. (SK)