Encompassing complex scatter plots, visually friendly infographics, and surprising works of contemporary art, data visualizations are as diverse as the disciplines from which they emerge. Over the past few decades, a strand of data visualizations has emerged that engage with ecological and sustainability topics and issues, such as concerns for the…

This paper describes elementary students' awareness and representation of the aggregate properties and variability of data sets when engaged in predictive reasoning. In a design study, 46 third-graders interpreted a table of historical temperature data to predict and represent future monthly maximum temperatures. The task enabled students to…

Exploratory factor analysis is a statistical method commonly used in psychological research to investigate latent variables and to develop questionnaires. Although such self-report questionnaires are prone to missing values, there is not much literature on this topic with regard to exploratory factor analysis--and especially the process of factor…

'Data as technology' has always been, and continues to be an essential part of the structuring of South African society and education, during and post-colonialism and post-apartheid. In the reconfiguration of South African education post-apartheid, student data constitutes a data frontier as un-mapped, under-utilised and ready for the picking.…

We make a distinction between the operational practice of using an observed score to assess differential item functioning (DIF) and the concept of departure from measurement invariance (DMI) that conditions on a latent variable. DMI and DIF indices of effect sizes, based on the Mantel-Haenszel test of common odds ratio, converge under restricted…

The path to publication is often long, emotional, and bewildering. We share key insights from our experience as authors, educators, and members of the editorial board with The Canadian Journal for the Scholarship of Teaching and Learning that we hope will help authors better understand and navigate the path to publication. In writing a compelling…

Eye tracking is an increasingly popular method in mathematics education. While the technology has greatly evolved in recent years, there is a debate about the specific benefits that eye tracking offers and about the kinds of insights it may allow. The aim of this review is to contribute to this discussion by providing a comprehensive overview of…

Secondary data analysis in educational research has been an established research method for many years. Yet, few publications outline the "how to" of undertaking the process. This paper presents an analysis framework suitable for undertaking secondary data analysis within the field of education. The framework is a modification and an…

This article discusses estimation of average treatment effects for randomized controlled trials (RCTs) using grouped administrative data to help improve data access. The focus is on design-based estimators, derived using the building blocks of experiments, that are conducive to grouped data for a wide range of RCT designs, including clustered and…

This study compares two missing data procedures in the context of ordinal factor analysis models: pairwise deletion (PD; the default setting in Mplus) and multiple imputation (MI). We examine which procedure demonstrates parameter estimates and model fit indices closer to those of complete data. The performance of PD and MI are compared under a…

As a digital learning medium, serious games can be powerful, immersive educational vehicles and provide large data streams for understanding player behavior. Educational data mining and learning analytics can effectively leverage big data in this context to heighten insight into student trajectories and behavior profiles. In application of these…

Realist evaluation (RE) is a research design increasingly used in program evaluation, that aims to explore and understand the influence of context and underlying mechanisms on intervention or program outcomes. Several methodological challenges, however, are associated with this approach. This article summarizes RE key principles and examines some…

In this article I respond to the tendency of the law to approach 'the public interest' as a legal test, thereby drawing the criticism that this narrow notion of what purports to be in the "public" interest is wholly disconnected from the views of actual publics, and lacks social legitimacy. On the other hand, to simply extrapolate…

In data collected from virtual learning environments (VLEs), item response theory (IRT) models can be used to guide the ongoing measurement of student ability. However, such applications of IRT rely on unbiased item parameter estimates associated with test items in the VLE. Without formal piloting of the items, one can expect a large amount of…

Binary item response theory (IRT) models are widely used in educational testing data. These models are not perfect because they simplify the individual item responding process, ignore the differences among different response patterns, cannot handle multidimensionality that lay behind options within a single item, and cannot manage missing response…