This work reports on the implementation of a self-contained data-literacy exercise designed for use in undergraduate classes to help students practice data literacy skills such as interpreting and evaluating evidence and assessing arguments based on data. The exercises use already developed data-visualizations to test and develop students' ability…

We provide a computational exercise suitable for early introduction in an undergraduate statistics or data science course that allows students to "play the whole game" of data science: performing both data collection and data analysis. While many teaching resources exist for data analysis, such resources are not as abundant for data…

This paper offers guidance on employing open and creative methods for co- designing critical data and artificial intelligence (AI) literacy spaces and learning activities, rooted in the principles of Data Justice. Through innovative approaches, we aim to enhance participation in learning, research and policymaking, fostering a comprehensive…

Purpose: Arts-integration is a promising approach to building students' abilities to create and critique arguments with data, also known as informal inferential reasoning (IIR). However, differences in disciplinary practices and routines, as well as school organization and culture, can pose barriers to subject integration. The purpose of this…

The COVID epidemic has provided an excellent example of the need to call on a wide variety of statistical tools to address a global problem, and can give students insights into some of the dimensions of data science. Here, we describe some of the characteristics of data that students encounter as citizens. We set out some teaching ideas, which…

We describe a "Day of Giving" university fundraising event that can be used to introduce data visualization to undergraduate students. The project involves integrating data sources, creating a Tableau data model, and designing a heat map that can be embedded into a front-end website. Our activity provides opportunities to discuss various…

Graphical representations appear everywhere in modern society. Their ubiquity has, in part, justified graph literacy as a core competency in education. Graph literacy - the capacity to read and interpret graphs - consists of understanding features, identifying variables, interpreting trends, and forming real-world connections. Experts and novices…

This article describes an activity and resource from The New York Times that can be used to help learners cultivate critical statistical literacy. Critical statistical literacy involves understanding, interpreting, and questioning statistical information to make informed decisions (Casey et al., 2023; Franklin et al., 2015; Weiland, 2017). It is a…

COVID-19 pandemic policies requiring disease testing provide a rich context to build insights on true positives versus false positives. Our main contribution to the pedagogy of data analytics and statistics is to propose a method for teaching updating of probabilities using Bayes' rule reasoning to build understanding that true positives and false…

Integrating the use of large datasets into our teaching provides critical and unique opportunities to build students' skills and conceptual knowledge. Here, we discuss the core components needed to develop effective activities based on large datasets, which align with the 5E learning cycle. Data-based activities should be structured around a…

Utilizing popular murder-mystery texts that transcend boundaries of race, class, age, and sex, students apply Toulmin's 1958 concept of claim, data, warrant (Toulmin, S. E. 2003. The uses of argument. Cambridge University Press). Ultimately, students engage in an activity that demonstrates how argumentation plays a role outside of the college…

Our complex world requires multivariate reasoning to make sense of reality. Within this paper, we offer a sequence of activities designed to develop multivariate reasoning by explicitly connecting data and visualization. The activities were designed based on a hypothetical learning trajectory we conjectured for students with limited experience…

With reference to the framework in The International Data Science in Schools Project, this paper aims to discuss the course design, teaching and learning, and assessment of a foundation course offered in an undergraduate statistics and data science programme. SAS® University Edition (a free software package) is adopted in this foundation course.…

The research sought to study potential efficiency in course design and execution using Constructive Alignment, and then classroom workflow grounded in eduScrum based on the Agile Project Framework of Scrum for graduate classes in managerial analytics. The research measured performance based on the Scrum concept of Velocity, defined as the rate of…

Authentic, "messy data" contain variability that comes from many sources, such as natural variation in nature, chance occurrences during research, and human error. It is this messiness that both deters potential users of authentic data and gives data the power to create unique learning opportunities that reveal the nature of science…