In the past decade, moderated mediation analysis has been extensively and increasingly employed in social and behavioral sciences. With its widespread use, it is particularly important to ensure the moderated mediation analysis will not bring spurious results. Spurious effects have been studied in both mediation and moderation analysis, but this…

Variability is underemphasized in domains such as engineering. Statistics and data science education research offers a variety of frameworks for understanding variability, but new frameworks for domain applications are necessary. This study investigated the professional practices of working engineers to develop such a framework. The Neglected,…

Students with or at-risk of High Incidence Disabilities (HID) experience negative short and long-term outcomes. To intervene, many schools have elected to implement evidence-based practices within Multi-Tiered Systems of Support (MTSS), such as Response to Intervention (RTI). MTSS target the academic and behavioral progress of students deemed 'at…

Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…

This article revisits how the end points of plotted line segments should be selected when graphing interactions involving a continuous target predictor variable. Under the standard approach, end points are chosen at ±1 or 2 standard deviations from the target predictor mean. However, when the target predictor and moderator are correlated or the…

The popularity of online surveys has increased the prominence of using weights that capture units' probabilities of inclusion for claims of representativeness. Yet, much uncertainty remains regarding how these weights should be employed in analysis of survey experiments: Should they be used or ignored? If they are used, which estimators are…

Factor analysis is a versatile class of psychometric techniques used by researchers to provide insight into the psychological dimensions (factors) that may account for the relationships among variables in a given dataset. The primary goal of a factor analysis is to determine a more parsimonious set of variables (i.e., fewer than the number of…

In tiered instructional systems (Response to Intervention [RTI]/Multitier System of Supports [MTSS]) that rely on ongoing assessment of students at risk of experiencing academic difficulties, the ability to make informed decisions using student data is critical for student learning. Prior research has demonstrated that, on average, teachers have…

Self-report data have contributed to a rich understanding of learning and motivation; yet, self-report measures present challenges to researchers studying students' experiences in small-group contexts. Rather than using self-report data alone, we argue that fusing self-report and observational data can yield a broader understanding of students'…

Adopting a two-phase explanatory sequential mixed methods research design, the current study examined the impact of student teaching experiences on pre-service teachers' readiness for technology integration. In phase-1 of quantitative investigation, 2-level growth curve models were fitted using online repeated measures survey data collected from…

We developed a criterion-referenced student rating of instruction (SRI) to facilitate formative assessment of teaching. It involves four dimensions of teaching quality that are grounded in current instructional design principles: Organization and structure, Assessment and feedback, Personal interactions, and Academic rigor. Using item response…

Quantitative and statistical literacy are core domains in the undergraduate psychology curriculum. An important component of such literacy includes interpretation of visual aids, such as tables containing results from statistical analyses. This article presents results of a quasi-experimental study with longitudinal follow-up that tested the…

A major obstacle to developing evidenced-based policy is the difficulty of implementing randomized experiments to answer all causal questions of interest. When using a nonexperimental study, it is critical to assess how much the results could be affected by unmeasured confounding. We present a set of graphical and numeric tools to explore the…

Digital skills are increasingly important for labour market outcomes and social participation. Do they also matter for academic performance? This paper investigates the effects of digital literacy on educational outcomes by merging data from the Italian National Assessment in secondary schools with an original data-set on performance tests of…

Every day, students collect, organize, and analyze data to make decisions. In this data-driven world, people need to assess how much trust they can place in summary statistics. The results of every survey and the safety of every drug that undergoes a clinical trial depend on the correct application of appropriate statistics. Recognizing the…