This article introduces a collection of four datasets, similar to Anscombe's quartet, that aim to highlight the challenges involved when estimating causal effects. Each of the four datasets is generated based on a distinct causal mechanism: the first involves a collider, the second involves a confounder, the third involves a mediator, and the…

Researchers tasked with understanding the effects of educational technology innovations face the challenge of providing evidence of causality. Given the complexities of studying learning in authentic contexts interwoven with technological affordances, conducting tightly-controlled randomized experiments is not always feasible nor desirable. Today,…

Alarmed by his students' random use of causal language in their essays, James Edward Carroll resolved to help his students improve their understanding of causal processes. Carroll decided to introduce his students to the metaphors that historians use to describe causation in the historiography of the Salem witch trials. By modelling how historians…

Pretend play is often hypothesized in a global sense to be an effective context for young children's learning, but there is much still to learn about whether all types of information can be learned equally and whether all types of pretend play are equally beneficial. The present study tests whether preschoolers can learn a simple, novel causal…

Most current statistics courses include some instruction relevant to causal inference. Whether this instruction is incorporated as material on randomized experiments or as an interpretation of associations measured by correlation or regression coefficients, the way in which this material is presented may have important implications for…

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…

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…

This study examines the relationship between teachers' technology proficiencies and their level of integrating technology into their lessons. In this research, which was designed in a relational survey model, as data collection tools, the "Technology Proficiency Self-Assessment Scale for 21st Century Learning" developed by Christensen…

The purpose of the present study is to analyze the digital competence of Higher Education students, as a function of their academic performance (have either repeated or a not previously), as well as to predict its significant predictors. For this, an ex-post factor and a sample of 17301 students from Chile (Latin America) were utilized. A…

The concept of correlation arises in Unit 3 of General Mathematics in the Australian Curriculum (ACARA, 2010-present). University students will meet the topic in applied statistics subjects in courses on business, psychology, research methods as well as in mathematical subjects on probability and statistics. When students are introduced to the…

Feedback loop reasoning is an essential part of systems thinking, which includes the analysis and description of system behaviour and regulative measures. In feedback loops, every change can simultaneously represent a cause and an effect. Research on reasoning in feedback loops is limited to investigating students' existing mental models. This…

Using socio-scientific issues (SSI) in the science learning environment can promote student motivation to learn and make learning experiences more meaningful. Embedding model-based reasoning opportunities in science lessons can promote substantial science learning. However, how these both work together to promote science learning is a little…

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,…

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…

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…