Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion detection programs that are accessible to R programmers: Google Cloud Vision, Amazon Rekognition, and…

A staple of many spreadsheet-based management science courses is the use of Excel for activities such as model building, sensitivity analysis, goal seeking, and Monte-Carlo simulation. What might those things look like if carried out using Python? We describe a teaching module in which Python is used to do typical Excel-based modeling and…

A programming workshop has been developed for biochemists and molecular biologists to introduce them to the power and flexibility of solving problems with Python. The workshop is designed to move users beyond a "plug-and-play" approach that is based on spreadsheets and web applications in their teaching and research to writing scripts to…

This short paper presents an educational approach to teaching three popular methods for encoding DNA sequences: one-hot encoding, binary encoding, and integer encoding. Aimed at bioinformatics and computational biology students, our learning intervention focuses on developing practical skills in implementing these essential techniques for…

Despite the increasing use of the statistical programming language R in statistics and data analysis (SDA), its implementation in communication science education is limited. Experiences, recommendations, and a critical exchange are therefore scarce. The following contribution addresses this very gap. At the Department of Journalism and…

Effect sizes are important because they are an accessible way to indicate the practical importance of observed associations or differences. Standardized mean difference (SMD) effect sizes, such as Cohen's d, are widely used in education and the social sciences -- in part because they are relatively easy to calculate. However, SMD effect sizes…

Constructing a consensus problem space from extensive qualitative data for an ill-structured real-life problem and expressing the result to a broader audience is challenging. To effectively communicate a complex problem space, visualization of that problem space must elucidate inter-causal relationships among the problem variables. In this…

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…

The growth in digitalisation has led to an increasing demand for digital skills in various job sectors. In particular, employers in scientific job areas have shown interest in candidates possessing digital competencies. This study aims to analyse the digital skill requirements for candidates in scientific job opportunities. The content analysis is…

Objectives: Java is a popular programming language for use in computing education, but it is difficult to get a wide picture of the issues that it presents for novices; most studies look only at the types or frequency of errors. In this observational study, we aim to learn how novices use different features of the Java language. Participants:…

Organizations are keenly interested in data gathering from websites where discussions of products and brands occur. This increasingly means that programmers need an understanding of how to work with website application programming interfaces (APIs) for data acquisition. In this hands-on lab activity, students will learn how to gather data from…

The R programming language and computing environment is a powerful and common platform used by life science researchers and educators for the analysis of big data. One of the benefits of using R in this context is its ability to visualize the results. Using R to generate visualizations has gained in popularity due to the increased number of R…

The use of text mining tools can help librarians improve the precision of searches, increase search sensitivity, and translate search strategies across multiple research databases. When combined with the intuitive approaches that librarians commonly use, text mining tools help reduce biases by improving the objectivity, transparency, and…

This paper shows a method for integrating computer programming into a standard physical chemistry laboratory sequence to augment student data analysis abilities and allow them to carry programming skills forward to other courses. The Python programming language is used, taking advantage of the pedagogical benefits of Jupyter notebooks, primarily…

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…