QR decomposition is widely used for solving the least squares problem. However, existing materials about it may be too abstract for non-mathematicians, especially STEM students, and/or require serious background in linear algebra. The paper describes theoretical background and examples of GNU Octave compatible MATLAB scripts that give relatively…

CODAP is a widely-used programming environment for secondary school data science. Its direct-manipulation-based design offers many advantages to learners, especially younger students. Unfortunately, these same advantages can become a liability when it comes to repeating operations consistently, replaying operations (for reproducibility), and also…

Missing data can significantly influence results of epidemiological studies. The National Health and Nutrition Examination Survey (NHANES) is a popular epidemiological dataset. We examined recent practices related to the prevalence and the reporting of the amount of missing data, the underlying mechanisms, and the methods used for handling missing…

Biomedical data science education faces the challenge of preparing students for conducting rigorous research with increasingly complex and large datasets. At the same time, philosophers of science face the challenge of making their expertise accessible for scientists in such a way that it can improve everyday research practice. 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,…

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…

We present a two-week active learning chemical engineering hackathon event specifically designed to teach undergraduate chemical engineering students of any skill level data science through Python and directly apply this knowledge to a real problem provided by industry. The event is free and optional to the students. We use self-evaluation surveys…

Growing societal concern about a crisis in the wellbeing of young people has prompted a range of responses from governments and corporations, predicated on an ideal of the resilient, self-reliant individual. Behavioural economists, data scientists and educational technology companies now offer a variety of psychological interventions based on…

This paper demonstrates how the innovative application of a Collective Intelligence approach enhanced Local Skills Improvement Planning information for employers, education and skills training organisations and regional economic policy organisations. This took place within a Knowledge Transfer Partnership between a Chamber of Commerce and a…

Drawing on the scholarship of writing and learning, this article motivates the use of writing assignments in analytics courses and develops a framework for instructional design that advances both writing skills and discipline-specific learning. We translate a best practices set of foundational writing concepts into a matrix of design levers for…

Research reproducibility is essential for scientific development. Yet, rates of reproducibility are low. As increasingly more research relies on computers and software, efforts for improving reproducibility rates have focused on making research products digitally available, such as publishing analysis workflows as computer code, and raw and…

Debates surrounding the use of data science in educational AI are frequently rather entrenched, revolving around commercial models and talk of teacher replacement. This article explores the potential for digital textual analysis within humanities and social science education, advocating for a sociologically-driven approach that complements, rather…

As the use of plastics expands, microplastic concentrations increase in aquatic environments and negatively impact water, soil, and animals inhabiting these areas. Microplastic research frequently incorporates citizen science to assist in data collection and environmental education. These projects provide opportunities for greater societal…

This brief explores data science methods that workforce programs can use to predict participant success. With access to vast amounts of data on their programs, workforce training providers can leverage their management information systems (MIS) to understand and improve their programs' outcomes. By predicting which participants are at greater risk…