This paper describes a short module for introducing data science to senior school students or other data-science beginners. The design focuses on "data moves." Students use CODAP to do their work.

This paper describes an in-class activity to introduce random assignment, paired data, and learning effect. The activity requires minimal materials, can be completed in a single class period, and is suitable for those using technology to conduct data exploration but can also be adapted for use in a technology-free classroom. The activity consists…

The growth of the data culture has led to calls for improving data literacy among primary and secondary students and their teachers. One approach to improving data literacy is to teach a course devoted to data science but, given the lack of consensus over the term "data science," just what should an introductory data science course…

Gaze data are still uncommon in statistics education despite their promise. Gaze data provide teachers and researchers with a new window into complex cognitive processes. This article discusses how gaze data can inform and be used by teachers both for their own teaching practice and with students. With our own eye-tracking research as an example,…

The data sets used in statistics education have changed over time, from mathematically "well-behaved" ones that facilitated computation, to more context-rich sources and now, with the increasing influence of data science practices, to "found" data, often from open data sites. As data sources change, it is important for…

This article is presented in two parts: in the first part we discuss the use of R and R-related tools when implementing a data science curriculum in the classroom and direct readers to helpful R resources in education, and in the second part, we demonstrate the use of R in exploring COVID-19 data. In particular, we explore ethnic/racial…

In this paper, we investigate an interesting question that came up when reading a problem in a school textbook: What happens to the variance of a dataset in the case of changing one single data point, and why? Some of the answers are not surprising but here we find the full answer and demonstrate the understanding of it suitable for school…

The explosion in availability and variety of data requires learning experiences that reveal more of the data world faster and develop practical skills with digital technologies. Key high-level goals of the International Data Science in Schools Project (IDSSP) include having students continually immersed in the cycle of learning from data, and data…

While a dot plot depicts data on a quantitative variable without distortion, a boxplot shows only the five-number summary. For large data, to aid in counting, we propose an IVY plot as a companion to a dot plot. Also, for large data, if the variable is approximately normally distributed, as a companion to a boxplot, we propose a Gaussian interval…

In the contemporary workplace, data scientists who are capable of interdisciplinary collaboration are in high demand. Universities need to provide data science students with a plethora of learning opportunities that involve collaboration in interdisciplinary contexts and engagement with industry partners. Curtin University and Lab Tests Online…

Although the use of real-world data sets is encouraged when teaching statistics, it can be difficult for instructors to find meaningful data for introducing students to univariate descriptive statistics such as the mean, median, and percentiles. The recent lead contamination of the water supply in Flint, Michigan, provides a real-life data set…

College-level statistics courses emphasize the use of the coefficient of determination, R-squared, in evaluating a linear regression model: higher R-squared is better. This often gives students an impression that higher R-squared implies better predictability since textbooks tend to use sample data to support the theory and students rarely have an…

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…

Data and its applications are increasingly ubiquitous in the rapidly digitizing world and consequently, students across different disciplines face increasing demand to develop skills to answer both academia's and businesses' increasing need to collect, manage, evaluate, apply and extract knowledge from data and critically reflect upon the derived…

Students have intuitive notions of the meaning of variability; some may see variability as how values in a set vary from each other. This article provides a measure of variability that is based on that conception. We introduce this new measure and a method for calculating it. Finally, we prove that this measure is equivalent to the population…