Purpose: The paper aims to present a new two stage local causal learning algorithm -- HEISA. In the first stage, the algorithm discoveries the subset of features that better explains a target variable. During the second stage, computes the causal effect, using partial correlation, of each feature of the selected subset. Using this new algorithm,…

Causal effects are commonly defined as comparisons of the potential outcomes under treatment and control, but this definition is threatened by the possibility that either the treatment or the control condition is not well defined, existing instead in more than one version. This is often a real possibility in nonexperimental or observational…

Over the last two decades, statistics educators have made important changes to introductory courses. Current guidelines emphasize developing statistical thinking in students and exposing them to the entire investigative process in the context of interesting research questions and real data. As a result, many concepts (confounding, multivariable…

Background: Causes produce effects via underlying mechanisms that must be inferred from observable and unobservable structures. Preschoolers show sensitivity to mechanisms in machine-like systems with perceptually distinct causes and effects, but little is known about how children extend causal reasoning to the natural continuous processes studied…

There are many different debates regarding the time spent on Instagram by social media addiction and life satisfaction. In consequence, in this research, it is aimed to reveal the variables that predict the time spent on Instagram by university students. The research is done in accordance with the causal and correlation model by using a…

This study synthesizes existing research to explore factors affecting student attrition in Thai higher education institutions and develop a causal model for dropout risk. The synthesis uses a mixed-method approach following PRISMA 2020 guidelines, drawing on six years of Thai contextual studies on student attrition, academic intention, commitment,…

The benefits of studying topics accompanied by adjunct displays are well established in the literature; however, less is understood about the durability of these learning benefits. Therefore, in the current study, we investigate the cognitive benefits of causal diagrams over time. Undergraduate participants (N = 194) recruited from teacher…

A historic period of state divestment in public higher education, exacerbated by the "Great Recession" and attendant financial repercussions, has significantly altered public higher education financing. The most significant impact has been cost shift from the state to students via increasing tuition rates. These changes threaten student…

In the article "Rethinking Traditional Methods of Survey Validation" Andrew Maul describes a minimalist validation methodology for survey instruments, which he suggests is widely used in some areas of psychology and then critiques this methodology empirically and conceptually. He provides a reduction ad absurdum argument by showing that…

Researchers often include covariates when they analyze the results of randomized controlled trials (RCTs), valuing the increased precision of the estimates over the potential of inducing small-sample bias when doing so. In this paper, we develop a sufficient condition which ensures that the inclusion of covariates does not cause small-sample bias…

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…

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…

Student success and drop-out predictions have gained increased attention in recent years, connected to the hope that by identifying struggling students, it is possible to intervene and provide early help and design programs based on patterns discovered by the models. Though by now many models exist achieving remarkable accuracy-values, models…

Systems thinking is recognized as an essential skill for understanding complex problem solving and decision making associated with many of the contemporary issues faced by individuals and communities. In this article, our goal is to contribute to the knowledge of curriculum and pedagogy of formal systems thinking teaching in higher education. We…

While a growing body of literature has documented the negative impacts of exclusionary punishments, such as suspensions, on academic outcomes, less is known about how teachers vary in disciplinary behaviors and the attendant impacts on students. We use administrative data from North Carolina elementary schools to examine the extent to which…