Effect sizes are important because they are an accessible way to indicate the practical importance of observed associations or differences. Standardized mean difference (SMD) effect sizes, such as Cohen's d, are widely used in education and the social sciences -- in part because they are relatively easy to calculate. However, SMD effect sizes…

While correlated data methods (like random effect models and generalized estimating equations) are commonly applied in practice, students may struggle with understanding the reasons that standard regression techniques fail if applied to correlated outcomes. To this end, this article presents an in-class activity using results from Monte Carlo…

Ten years after the announcement of the "rise of the super experiment" at Educational Data Mining 2012, challenges to implementing "internet scale" educational experiments often persist for educational technology providers, especially when they seek to test substantive instructional interventions. Studies that deploy and test…

In 2020, Year 12 students at John Curtin College of the Arts, were required to model COVID-19 data from five different countries in order to find correlations between daily infections and unemployment rates, in order to make future predictions. Work received from students demonstrated how the task successfully provided unique learning…

Descriptive analyses of socially important or theoretically interesting phenomena and trends are a vital component of research in the behavioral, social, economic, and health sciences. Such analyses yield reliable results when using representative individual participant data (IPD) from studies with complex survey designs, including educational…

Purpose: This paper aims to introduce the extended qualitative content analysis (EQCA) method to integrate data-reducing and data-complicating research steps when conducting qualitative research on the United Nations and other international institutions. Design/methodology/approach: EQCA supplements the method of qualitative content analysis,…

This Equity Tool, intended to support when critically reading a research study/report, provides a brief introduction to key concepts and issues involved in using largescale research, calling attention to high profile controversies, and providing explicit linkages to desegregation areas (race, sex, nationality, religion). The first part (Table 1)…

In this short thought-piece, I attempt to capture the type of freewheeling discussions I had with our late colleague, Mika Seppälä, a research mathematician from Helsinki. Mika, not being a psychometrician or learning scientist, was blissfully free from the design constraints that experts sometimes ingest, unwittingly. I also draw on delightful…

Two of the most important issues facing those in the field of academic advising are the use of technology and data analytics. There is no question that technology and data will shape the delivery and expectations for academic advising in higher education in the years to come. This chapter explores the intersections between advising, technology,…

A common motivation for adding control variables to statistical models is to reduce the potential for spurious findings when analyzing non-experimental data and to thereby allow for more reliable causal inferences. However, as I show here, unless "all" potential confounding factors are included in an analysis (which is unlikely to be…

Social network analysis (SNA) consists of a broad set of frameworks and methods to assess how direct and indirect relationships influence individual functioning. Although interest in SNA has steadily increased in the psychological sciences, school psychology has not kept pace. This article provides a general overview of core SNA concepts,…

Since the publishing of Nolan and Temple Lang's "Computing in the Statistics Curriculum" in 2010, the American Statistical Association issued new recommendations in the revised GAISE college report. To reflect modern practice and technologies, they emphasize giving students experience with multivariable thinking. Students develop…

The authors have developed a visualization tool to assist higher education stakeholders in exploring options in higher education performance and accountability. The tool allows users to visualize quickly differences between programs and institutions along a number of dimensions. This report draws five insights from the visualization tool: (1)…

Data collected from surveys can result in hundreds of variables and thousands of respondents. This implies that time and energy must be devoted to (a) carefully entering the data into a database, (b) running preliminary analyses to identify any problems (e.g., missing data, potential outliers), (c) checking the reliability and validity of the…

This paper provides a tutorial on epistemic network analysis (ENA), a novel method for identifying and quantifying connections among elements in coded data and representing them in dynamic network models. Such models illustrate the structure of connections and measure the strength of association among elements in a network, and they quantify…