This study documents the effects of social inequality on different dimensions of lexical comprehension in Spanish-speaking Argentinian toddlers, a population in which socioeconomic differences are more striking than in previously studied populations. Using a performance-based forced-choice lexical recognition task implemented on a tablet, an…

Of critical importance to education policy is monitoring trends in education outcomes over time. In the United States, the National Assessment of Educational Progress (NAEP) has provided long-term trend data since 1970; at the state/jurisdiction level, NAEP has provided long-term trend data since 1996. In addition to the national NAEP, all 50…

In 2010, Nolan and Temple Lang proposed "integration of computing concepts into statistics curricula at all levels." The unprecedented growth in data and emphasis on data science has provided an impetus to finally realizing full implementations of this in new statistics and data science programs and courses. We discuss a proposal for the…

The ubiquitous acquisition and generation of data require a reworking of curricula in introductory statistics in tertiary education. We present a renewed curriculum that focuses on scientific thinking, modeling, and simulation-based inference, utilizing R and various R tools such as shiny and learnr apps. We teach statistics from a data-centric…

A major problem in human cognition is to understand how newly acquired information and long-standing beliefs about the environment combine to make decisions and plan behaviors. Over-dependence on long-standing beliefs may be a significant source of suboptimal decision-making in unusual circumstances. While the contribution of long-standing beliefs…

When physicians are asked to determine the positive predictive value from the a priori probability of a disease and the sensitivity and false positive rate of a medical test (Bayesian reasoning), it often comes to misjudgments with serious consequences. In daily clinical practice, however, it is not only important that doctors receive a tool with…

Machine learning, a subdomain of artificial intelligence, is a widespread technology that is molding how chemists interact with data. Therefore, it is a relevant skill to incorporate into the toolbox of any chemistry student. This work presents a workshop that introduces machine learning for chemistry students based on a set of Python notebooks…

There is growing interest in how to better prepare K-12 students to work with data. In this article, we assert that these discussions of teaching and learning must attend to the human dimensions of data work. Specifically, we draw from several established lines of research to argue that practices involving the creation and manipulation of data are…

The traditional instructional approach combined with standard textbook examples provide a disengaging learning environment for students in introductory statistics courses. This article proposes and examines an experiential music-based single-class-period learning activity for an introductory statistics course. This activity teaches students how to…

Teacher attrition is a chronic challenge facing many education systems, and has been shown to negatively impact education quality and equity. Common explanations rooted in occupational choice theory identify pecuniary and non-pecuniary rewards as critical factors in motivating and retaining teachers. Using China Household Income Project (CHIP)…

Art therapy students' art practice might influence professional identity and career commitment. Art therapy graduate students (n = 202) in South Korea participated in a survey. This study introduces the Art Practice Scale and associated exploratory factor analysis, which identified 2 subvariables: art competency and attitude toward artwork. The…

This study presents a latent (item response theory--like) framework of a recently developed classical approach to test scoring, equating, and item analysis, referred to as "D"-scoring method. Specifically, (a) person and item parameters are estimated under an item response function model on the "D"-scale (from 0 to 1) using…

In this article we present and discuss the importance and relevance of the inclusion of spatial data analysis as part of the undergraduate statistics curriculum. Given its usefulness and applicability across a range of disciplines, spatial data are a topic that should receive more emphasis within undergraduate statistics curricula. There exist…

This is the fourth in a series of statistical articles for mathematics teachers. In this article, the authors discuss topics in General Mathematics in Unit 2 Topic 1 (Univariate data analysis and the statistical investigation process) and topics in Essential Mathematics, Unit 2 Topic 1 (Representing and comparing data).

Best practices in statistics and data science courses include the use of real and relevant data as well as teaching the entire data science cycle starting with importing data. A rich source of real and current data is the web, where data are often presented and stored in a structure that needs some wrangling and transforming before they can be…