Instructors traditionally lecture on new content before providing practice problems, but learning is often superficial. Exploratory learning before instruction deepens conceptual understanding by giving students a novel activity to explore before direct instruction. We examined how increasing the salience of contrasting cases in exploration versus…

As is rapidly becoming clear, data science increasingly permeates many aspects of life. Educational research recognizes the importance and complexity of learning data science. In line with this imperative, there is a growing need to investigate the factors that influence student performance in data science tasks. In this paper, we aimed to apply…

Background: College students often do not retain what they learn in Statistics in order to apply it in Experimental Psychology. Self-explanation, that is, elaborating on what one is trying to learn by asking questions, making inferences, etc., improves learning and may improve retention. Objective: The purpose of this study was to determine…

Simulation studies are the basic tools of quantitative methodologists used to obtain empirical solutions to statistical problems that may be impossible to derive through direct mathematical computations. The successful execution of many simulation studies relies on the accurate generation of correlated multivariate data that adhere to a particular…

This study investigated first-year undergraduate statistics students' statistical problem-solving skills on the probability of the union of two events, conditional probability, binomial probability distribution, probabilities for x-limits using the z-distribution, x-limit associated with a given probability for a normal distribution, estimating…

Computational Thinking (CT) skills are increasingly recognized as essential for junior high school students, especially in addressing the demands of the digital era. This study explores how CT skills--decomposition, pattern recognition, abstraction, and algorithmic thinking--manifest in learning statistics based on students' cognitive abilities. A…

Purpose: This work aims to introduce basic principles of the Anthropological Theory of Didactics applied to enhance the multicultural sensitivity in engineering statistics classroom. The approach emphasizes understanding learners' socio-cultural backgrounds to tailor educational practices that resonate more effectively with engineering students.…

Statistical knowledge is required for students in a range of disciplines. However, there are limited educator resources that exist for applying statistics to solve real-world problems. This investigation provides one approach to teaching statistics using entrepreneurial-minded learning (as a way to connect real-world applications and value…

In this article we report on middle school students' understanding of concepts related to the second step of the statistical problem-solving process, study design: create a plan and collect data. Students participated in an open-ended statistics lesson involving nonexperimental study design. For this research we analyzed the students' discourse…

In this paper, we describe a course project in which teams of undergraduate students propose and execute an end-to-end analytics project to solve a real-world problem. The project challenges students to implement machine learning, optimization, simulation, or a combination of these three techniques on real-world data that they collect. A…

This article makes a case for introducing moving averages into introductory statistics courses and contemporary modeling/data-based courses in college algebra and precalculus. The authors examine a variety of aspects of moving averages and draw parallels between them and similar topics in calculus, differential equations, and linear algebra. The…

We present an exploratory study of Costa Rican and Spanish students' (11-16-year-olds) competence to compare probabilities in urns and compare ratios in mixture problems. A sample of 704 students in Grades 6 through to Grade 10, 292 from Costa Rica and 412 from Spain, were given one of two forms of a questionnaire with three probability comparison…

The current examined the roles of cognitive strategies using Chi's framework in mobile learning. Three conditions (active, constructive, and interactive) were created for a college statistics I course where students were randomly assigned to each condition. The results indicate constructive and interactive support students' problem solving and…

The statistical problem-solving process is key to the statistics curriculum at the school level, post-secondary, and in statistical practice. The process has four main components: formulate questions, collect data, analyze data, and interpret results. The Pre-K-12 Guidelines for Assessment and Instruction in Statistics Education (GAISE) emphasizes…

Being able to understand, interpret, and critically evaluate data is necessary for all individuals in our society. Using the PreK-12 Guidelines for Assessment and Instruction in Statistics Education-II (GAISE-II; Bargagliotti et al., 2020) curriculum framework, the current paper outlines five evidence-based recommendations that teachers can use to…