Quasi-experimental methods are a cornerstone of applied social science, providing critical answers to causal questions that inform policy and practice. Although open science principles have influenced experimental research norms across the social sciences, these practices are rarely implemented in quasi-experimental research. In this paper, we…

Growing literature documents the promise of active learning instruction in engaging students in college classrooms. Accordingly, faculty professional development (PD) programs on active learning have become increasingly popular in postsecondary institutions; yet, quantitative evidence on the effectiveness of these programs is limited. Using…

Qualitative Comparative Analysis (QCA) is a relatively young method of causal inference that continues to diffuse across the social sciences. However, recent methodological research has found the conservative (QCA-CS) and the intermediate solution type (QCA-IS) of QCA to fail fundamental tests of correctness. Even under conditions otherwise ideal…

Generic language (e.g., "tigers have stripes") leads children to assume that the referenced category (e.g., tigers) is inductively informative and provides a causal explanation for the behavior of individual members. In two preregistered studies with 4- to 7-year-old children (N = 497), we considered the mechanisms underlying these…

Randomized A/B tests allow causal estimation without confounding but are often under-powered. This paper uses a new dataset, including over 250 randomized comparisons conducted in an online learning platform, to illustrate a method combining data from A/B tests with log data from users who were not in the experiment. Inference remains exact and…

A wide range of machine-learning-based approaches have been developed in the past decade, increasing our ability to accurately model nonlinear and nonadditive response surfaces. This has improved performance for inferential tasks such as estimating average treatment effects in situations where standard parametric models may not fit the data well.…

Background: A singular ecological risk factor did not accurately reflect the reality of adolescents' lives and could not fully elucidate the developmental mechanisms of adolescent suicidal ideation. The cumulative effect of multiple ecological risk factors (which may interact synergistically) could have provided a more comprehensive understanding…

Complex social scientific theories are conventionally tested using linear structural equation modeling (SEM). However, the underlying assumptions of linear SEM often prove unrealistic, making the decomposition of direct and indirect effects problematic. Recent advancements in causal mediation analysis can help to address these shortcomings,…

Teleological reasoning is viewed as a major hurdle to evolution education, and yet, eliciting, interpreting, and reflecting upon teleological language presents an arguably greater challenge to the evolution educator and researcher. This article argues that making explicit the role of behavior as a causal factor in the evolution of particular…

Background: In recent years, the penetration rate of smartphones among Korean teenagers has increased, making it critical to clarify the influence of these devices on adolescents' lives. Objective: This study investigated the effects of smartphone dependence on peer relationships and life satisfaction among Korean adolescents. Methods: Using the…

In mixed methods approaches, statistical models are used to identify "nested" cases for intensive, small-n investigation for a range of purposes, including notably the examination of causal mechanisms. This article shows that under a commonsense interpretation of causal effects, large-n models allow no reliable conclusions about effect…

When individuals seek to learn about scientific information, they likely turn to the Internet. There, they will find multiple documents with conflicting points of view and varying degrees of accuracy. Integrating this information is challenging and may evoke epistemic emotions which may, in turn, influence how this information is integrated.…

Implementation fidelity is the degree of compliance with which the core elements of program or intervention practices are used as intended. The scientific literature reveals gaps in defining and assessing implementation fidelity in early intervention: lack of common definitions and conceptual framework as well as their lack of application. Through…

The Jeong (2020) study found that greater use of backward and depth-first processing was associated with higher scores on students' argument maps and that analysis of only the first five nodes students placed in their maps predicted map scores. This study utilized the jMAP tool and algorithms developed in the Jeong (2020) study to determine if the…

Structural equation modeling (SEM) is a statistical method widely used in educational research to investigate relationships between variables. SEM models are typically constructed based on theoretical foundations and assessed through fit indices. However, a well-fitting SEM model alone is not sufficient to verify the causal inferences underlying…