Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these…

Dashboards have become a crucial element of contemporary business operation and management; therefore, it is desirable for business students to acquire knowledge of them. This article investigates the effectiveness of designing learning activities around investment dashboards in the context of introductory business analytics (IBA) courses. We…

"Not only SQL" (NoSQL) databases have become widespread across organizations, enabling sophisticated, data-driven applications to be highly available, distributed, and cloud-based, such as e-commerce, social media, online multiplayer games, and video streaming. However, NoSQL is still sparsely found in MIS and analytics curricula. This…

In the fall of 2009 and in the spring of 2012, supported by the National Institute of General Medical Sciences (NIGMS) in the National Institutes of Health (NIH), we designed a course "Phylogenetic Analysis and Molecular Evolution" (PAME), the first cross-listed course across three different colleges (College of Arts and Sciences,…

Data science surrounds us in contexts as diverse as climate change, air pollution, route-finding, genomics, market manipulation, and movie recommendations. To open the "data-science-black-box" for lower secondary school students, we developed a data science teaching unit focusing on the analysis of environmental data, which we embedded…

The influx of data and the advances in computing have led to calls to update the introductory statistics curriculum to better meet the needs of the contemporary workforce. To this end, we developed the COMputational Practices in Undergraduate TEaching of Statistics (COMPUTES) instrument, which can be used to measure the extent to which computation…

Data literacy is a growing area of focus across multiple disciplines in higher education. The dominant forms of introduction focus on computational toolchains and statistical ways of knowing. As data driven decision-making becomes more central to democratic processes, a larger group of learners must be engaged in order to ensure they have a seat…

Traditionally, statistical computing courses have taught the syntax of a particular programming language or specific statistical computation methods. Since Nolan and Temple Lang's seminal paper, we have seen a greater emphasis on data wrangling, reproducible research, and visualization. This shift better prepares students for careers working with…

Informed by critical data literacy efforts to promote social justice, this paper uses qualitative methods and data collected during two years of workplace ethnography to characterize the notion of critical novice data work. Specifically, we analyze everyday language used by novice data workers at DataWorks, an organization that trains and employs…

Revisiting the seminal 2010 Nolan and Temple Lang article on the role of computing in the statistics curricula, we discuss several trends that have emerged over the last ten years. The rise of data science has coincided with a broadening audience for learning statistics and using computational packages and tools. It has also increased the need for…

Data science has maintained its popularity for about 20 years. This study adopts a bottom-up approach to understand what data science is by analyzing the descriptions of courses offered by the data science programs in the United States. Through topic modeling, 14 topics are identified from the current curricula of 56 data science programs. These…

In an increasingly data driven world, the need for a qualified STEM workforce is essential. Increasing the diversity of this workforce increases the social and economic possibilities for the individual as well as national economic status and global prominence in innovation and technology. The Curriculum and Community Enterprise for Restoration…

Established in December 2016, the National Academies of Sciences, Engineering, and Medicine's Roundtable on Data Science Postsecondary Education was charged with identifying the challenges of and highlighting best practices in postsecondary data science education. Convening quarterly for 3 years, representatives from academia, industry, and…