In statistics classes, the central limit theorem has been demonstrated using simulation-based illustrations. Known population distributions such as a uniform or exponential distribution are often used to consider the behavior of the sample mean in simulated samples. Unlike such simulations, a number of real-data-based simulations are here…

The authors discuss the use of surveys for collecting data from a population sample and emphasise the importance of being careful with the language of data collection. [For "The Data Files 5: Graphs for Exploring Relationships," see EJ1355504.]

Current developments in the statistics community suggest that modern statistics education should be structured holistically, that is, by allowing students to work with real data and to answer concrete statistical questions, but also by educating them about alternative frameworks, such as Bayesian inference. In this article, we describe how we…

The use of group work projects is common in introductory statistics courses, including projects where students collect their own data. However, the COVID-induced lockdown at the start of 2020 meant that data collection was compromised. In this study, we examine a situation where students were permitted to use artificial (made-up) data for their…

Although self-report surveys are widely used for data collection, data quality can vary across populations because certain groups are more likely to engage in insufficient effort responding (IER). Our study examined how different levels of the educational system--student groups, schools, and cultural contexts--affect data quality due to IER, using…

Engaging and motivating students in undergraduate statistics courses can be enhanced by using topical peer-reviewed publications for analyses as part of course assignments. Given the popularity of on-campus therapy dog stress-reduction programs, this topic fosters buy-in from students whilst providing information regarding the importance of mental…

The digital era has significantly reshaped journalism, emphasizing the pivotal role of data-driven reporting. This review delves into the nexus of data journalism and journalism education, investigating dominant study characteristics, challenges, and gaps for future research. Examining 41 relevant articles through the Arksey and O'Malley…

With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…

Better data is needed on disability in Global Partnership for Education (GPE) partner countries to understand the extent to which children with disabilities are excluded from education, so that countries can make evidence-based and inclusive education policy and plans, and progress can be monitored globally. As part of its work helping to build…

Statistics need data and data need context. Contexts from across the curriculum can be the most powerful in creating interest, reward, and enthusiasm for both teachers and students. The activity described here is based in STEM, employing aspects of each field to create and solve a hypothetical problem of escaping from an erupting volcano (Science)…

Typically, training in Russia for professionals includes school, university, and postgraduate education. People make their choice regarding university or job after school, and they choose jobs after university. These are very sensitive matters. Help in making the right choice is a real asset. The Russian Association of Statisticians (RASt) is an…

Learning about probability can pose difficulties for students at all levels. Performing probability experiments using games can encourage students to develop understandings of probability grounded in real events. In this reflective paper, we explore the thinking of a group of students and teachers as they reasoned about experimental and…

Statistical education is a very important area of research because it builds knowledge and promotes innovation in the courses of this discipline. Based on the advances in this area, changes in the content and approaches of the courses at all educational levels have been promoted in several countries. In this study, we examine programs of…

This paper describes the evolution of "recognition of need for data" and "strategical thinking", two types of thinking identified by Wild and Pfannkuch in their Framework for Statistical Thinking in Empirical Enquiry, as well as its relevance for math teacher professional development. The research was carried out with ten…

This article presents the design and implementation of a study and research path for teacher education (SRP-TE) based on the Anthropological Theory of the Didactic. The goal is to analyze this teacher education proposal for inclusive statistics education aiming to overcome constraints derived from the phenomenon of the transparency of data…