Effective undergraduate statistical education requires training using real-world data. Textbook datasets seldom match the complexities and messiness of real-world data and finding these datasets can be challenging for educators. Consulting and industrial datasets often have nondisclosure agreements. Academic datasets often require subject area…

There is wide agreement that ethical considerations are a valuable aspect of a data science curriculum, and to that end, many data science programs offer courses in data science ethics. There are not always, however, explicit connections between data science ethics and the centuries-old work on ethics within the discipline of philosophy. Here, we…

Some in our discipline have recently voiced the opinion that political science is a data science. What follows from this argument is that we as instructors are training the next generation of data scientists, especially professionals and researchers who will work with big data. This paper explores the implications for political science education,…

When we imagine the work of a data analyst, we often picture meaningful data analysis and beautiful data visualizations. Although that is an exciting part of the job, data analysts actually spend the majority of their time acquiring, cleaning, and preparing data for analysis. This teaching case guides students through some of the most common data…

The design and analysis of experiments (DOE) has historically been an important part of an education in statistics, and with the increasing complexity of modern production processes and the advent of large-scale online experiments, it continues to be highly relevant. In this article, we provide an extensive review of the literature on DOE…

Assessment and institutional research offices have too much data and too little time. Standard reporting often crowds out opportunities for innovative research. Fortunately, advancements in data science now offer a clear solution. It is equal parts technique and philosophy. The first and easiest step is to modernize data work. This column…

The rapidly increasing capacity of technology to collect, organize, and manage data has spurred changes in the practice of statistics: new methods of collecting data, large data sets, new forms of data, different ways to visualize and represent data, and recognition of the importance of being able to understand and to communicate data-based…

The objectives of this study were to identify gaps in educational training for undergraduate and graduate students in agricultural data science, propose paths for filling these gaps, and provide an annotated list of resources currently available to different training levels. Data in this study was collected through three voluntary surveys catered…

The field of teacher education is subject to intense scrutiny and policy reform and within this context, the voices of those working within the field are often marginalised. Drawing on our larger study of teacher educators, we addressed the key research question: "How do those who work in the field of teacher education articulate and…

The development of data science curricula has gained attention in academia and industry. Yet, less is known about the pedagogical practices and tools employed in data science education. Through a systematic literature review, we summarize prior pedagogical practices and tools used in data science initiatives at the higher education level.…

With increased focus on data literacy and data science education in K-12, little is known about what makes a data set preferable for use by classroom teachers. Given that educational designers often privilege authenticity, the purpose of this study is to examine how teachers use features of data sets to determine their suitability for authentic…

This scoping review explores the intersection of climate change education and technology usage in the classroom. We conducted a scoping review of 93 articles to ascertain what, if any, trends exist across this body of scholarship. Findings indicate that technology serves to provide learners with refutation experiences for accepting and making…

This study examined the data science career preference, data science skills, and core competencies of 416 students from fourteen Nigerian universities using a Google Forms-created structured online questionnaire. A convenience sampling technique was adopted to select the participants. Data were analysed using both descriptive and inferential…

Preparing the new generation to be data-literate citizens is a pressing challenge, and some explorations have been made to cultivate K-12 students' data science skills and attitudes. However, there is a lack of instructional models to guide the design of data science programs in K-12 due to its complex and interdisciplinary nature as well as the…

Mathematics education is like many scientific disciplines witnessing an increase in scientific output. Examining and reviewing every paper in an area in detail are time-consuming, making comprehensive reviews a challenging task. Unsupervised machine learning algorithms like topic models have become increasingly popular in recent years. Their…