Doubly robust (DR) estimators that combine regression adjustments and inverse probability weighting (IPW) are widely used in causal inference with observational data because they are claimed to be consistent when either the outcome or the treatment selection model is correctly specified (Scharfstein et al., 1999). This property of "double…

This study contributes to the call for influencing practice by increasing attention to how learning environments can be designed to support learning in statistical inference. We report on a design experiment in secondary school (students 14-16 years old), that resulted in a set of lessons with the learning goal of teaching students how to apply…

This article examines the risk of crossover contamination in individual-level randomization, a common concern in experimental research, in the context of a large-enrollment college course. While individual-level randomization is more efficient for assessing program effectiveness, it also increases the potential for control group students to cross…

Emergent technologies present platforms for educational researchers to conduct randomized controlled trials (RCTs) and collect rich data on study students' performance, behavior, learning processes, and outcomes in authentic learning environments. As educational research increasingly uses methods and data collection from such platforms, it is…

Emergent technologies present platforms for educational researchers to conduct randomized controlled trials (RCTs) and collect rich data to study students' performance, behavior, learning processes, and outcomes in authentic learning environments. As educational research increasingly uses methods and data collection from such platforms, it is…

Educational reform priorities such as emphasis on quantitative modelling (QM) have positioned undergraduate biology instructors as designers of QM experiences to engage students in authentic science practices that support the development of data-driven and evidence-based reasoning. Yet, little is known about how biology instructors adapt to the…

Researchers across many fields have called for greater attention to heterogeneity of treatment effects--shifting focus from the average effect to variation in effects between different treatments, studies, or subgroups. True heterogeneity is important, but many reports of heterogeneity have proved to be false, non-replicable, or exaggerated. In…

Eye movements reveal what is at the center of people's attention, which is assumed to coincide with what they are thinking about. Eye-movement displays (visualizations of a person's fixations superimposed onto the stimulus, for example, as dots or circles) might provide useful information for diagnosing that person's performance. However, making…

Advice on case selection in small-"N" research emphasizes controlling for confounding variables to facilitate inferential tests of a cross-case pattern. Yet many researchers embrace the "mechanismic worldview" and aim to construct explanations. Explanations differ from inferences because one explains an outcome at the…

In this article, we propose a variational Bayes (VB) inference method for the deterministic input noisy AND gate model of cognitive diagnostic assessment. The proposed method, which applies the iterative algorithm for optimization, is derived based on the optimal variational posteriors of the model parameters. The proposed VB inference enables…

Do children always conform to a majority's testimony, or do the pragmatics of that testimony matter? We investigated the influence of pragmatics on conforming to a majority across 2 domains: when learning about object labels and when learning about causal relationships. Four- and 5-year-olds (N = 250) were given a choice between an object endorsed…

To date, hundreds of researchers have employed the method of Qualitative Comparative Analysis (QCA) for the purpose of causal inference. In a recent series of simulation studies, however, several authors have questioned the correctness of QCA in this connection. Some prominent representatives of the method have replied in turn that simulations…

Researchers often seek to synthesize results of multiple studies on the same topic to draw statistical or substantive conclusions and to estimate effect sizes that will inform power analyses for future research. The most popular synthesis approach is meta-analysis. There have been few discussions and applications of other synthesis approaches.…

Retrieval practice of isolated words (e.g., with flashcards) enhances foreign vocabulary learning. However, vocabulary is often encountered in context. We investigated whether retrieval opportunities also enhance contextualized word learning. In two within-subjects experiments, participants encoded 24 foreign words and then read a story to further…

Data reasoning is an essential component of scientific reasoning, as a component of evidence evaluation. In this paper, we outline a model of scientific data reasoning that describes how data sensemaking underlies data reasoning. Data sensemaking, a relatively automatic process rooted in perceptual mechanisms that summarize large quantities of…