This paper develops a novel approach called Outcome Trajectory Evaluation (OTE) in response to the long-causal-chain problem confronting the evaluation of research for development (R4D) projects. OTE strives to tackle four issues resulting from the common practice of evaluating R4D projects based on theory of change developed at the start. The…

This paper discusses a three-level model that synthesizes and unifies existing learning theories to model the roles of artificial intelligence (AI) in promoting learning processes. The model, drawn from developmental psychology, computational biology, instructional design, cognitive science, complexity and sociocultural theory, includes a causal…

Recent critiques of physics education research (PER) studies have revoiced the critical issues when drawing causal inferences from observational data where no intervention is present. In response to a call for a "causal reasoning primer" in PER, this paper discusses some of the fundamental issues in statistical causal inference. In…

Over 2000 years ago, Aristotle wrote of four distinct causes at play in the world we know. Those causes, the material cause, the formal cause, the efficient cause, and the final cause, were meant to refer to ontological and, by extension, epistemological concerns, and were powerful enough to be seized upon and used in some form by those of very…

Estimation of causal effects requires making comparisons across groups of observations exposed and not exposed to a a treatment or cause (intervention, program, drug, etc). To interpret differences between groups causally we need to ensure that they have been constructed in such a way that the comparisons are "fair." This can be…

The consequence of a change in school leadership (e.g., principal turnover) on student achievement has important implications for education policy. The impact of such an event can be estimated via the popular Difference in Difference (DiD) estimator, where those schools with a turnover event are compared to a selected set of schools that did not…

This study aimed to comparatively analyse the effects of problem-based learning model (PBLM) on cognitive outputs (CO). The study reviewed quasi-experimental studies on PBLM and CO, focusing on the cognitive outputs of thinking skills, problem-solving skill, and academic achievement. The quantitative data of these studies, comprising 56 articles…

In physiology education, students must learn to recognize and construct causal explanations. This challenges students, in part, because causal explanations in biology manifest in different varieties. Unlike other natural sciences, causal mechanisms in physiology support physiological functions and reflect biological adaptations. Therefore,…

The aim of this research was to investigate the associations between attachment styles, mental well-being and psychological vulnerability. The sample comprised a total of 257 university students including 205 women (79.8%) and 52 men (20.2%). The ages of university students varied from 18 to 34 years [M[subscript age] = 21.37, SD = 2.13]. The…

Context: Prolonged disconnection from school and work represents major setbacks during the transition to adulthood and is a distinct feature of the developmental trajectories of many disadvantaged youths, especially those from a marginalized racial background (Hong and Chung 2022; Shanahan 2000). Differential schooling experiences are hypothesized…

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…