Analyzing which skills students develop in introductory programming education is an important question for the computer science education community. These key skills and concepts have been formalized as knowledge components, which are units of knowledge that can be measured by performance on a set of tasks. While knowledge components in other…

This article presents a novel approach to introducing principal component analysis (PCA), using summary tables and descriptive statistics. Given its applicability across a variety of academic disciplines, this topic offers abundant opportunity for class discussion and activities. However, teaching PCA in an introductory class can be challenging…

Large Language Model (LLM) artificial intelligence tools present a unique challenge for educators who teach programming languages. While LLMs like ChatGPT have been well documented for their ability to complete exams and create prose, there is a noticeable lack of research into their ability to solve problems using high-level programming…

The principles of programming language design for learning and teaching have been described and discussed for several decades. Most influential was the work of Niklaus Wirth, describing principles such as simplicity, modularity, orthogonality, and readability. So why is this still an area of fundamental disagreement among educators? Why can…

Background: Conventional reflective learning methodologies in programming education often lack structured guidance and individualised feedback, limiting their pedagogical effectiveness. Whilst computational thinking (CT) offers a systematic problem-solving framework with decomposition, pattern recognition, abstraction, and algorithm design, its…

R is becoming the standard for teaching statistics due to its flexibility, and open-source nature, replacing software programs like Minitab and SPSS. The main driver for reform within Scottish statistical undergraduate programs is the creation of the Scottish Qualification Authority's Higher Applications of Mathematics course which has statistics…

When incorporating programming into a statistics course, there are many pedagogical considerations. In R, one consideration is the particular R syntax used. This article reports on a head-to-head comparison of a pair of introductory statistics labs, one conducted in the formula syntax, the other in tidyverse. Pre- and post-surveys show minimal…

Laboratory automation and data science are valuable new skills for all chemists, but most pedagogical activities involving automation to date have focused on upper-level coursework. Herein, we describe a combined computational and experimental lab suitable for a first-year undergraduate general chemistry course, in which these topics are…

Scientific programming has become increasingly essential for manipulating, visualizing, and interpreting the large volumes of data acquired in earth science research. Yet few discipline-specific instructional approaches have been documented and assessed for their effectiveness in equipping geoscience undergraduate students with coding skills. Here…

The academic success of first-year students' learning in science faculties is by no means assured, especially in an Open Distance Learning setting with its limited number of face-to-face encounters between students and lecturers or tutors. Therefore, such encounters should be highly efficient in view of the considerable amount of knowledge…

A significant activity in the business analytics process is enrichment, which deals with acquiring and combining data from external sources. While different strategies for enrichment are possible, it can be accomplished more efficiently through automation using Python scripts. Since business students may not be immersed in technology skills and…

University students in other disciplines without prior knowledge in statistics and/or programming language are introduced to the statistical method of decision trees in the programming language R during a 45-minute teaching and practice session. Statistics and programming skills are now frequently required within a wide variety of research fields…

Data and its applications are increasingly ubiquitous in the rapidly digitizing world and consequently, students across different disciplines face increasing demand to develop skills to answer both academia's and businesses' increasing need to collect, manage, evaluate, apply and extract knowledge from data and critically reflect upon the derived…

Generative artificial intelligence (AI) tools like ChatGPT are becoming increasingly common in educational settings, especially in programming education. However, the impact of these tools on the learning process, student performance, and best practices for their integration remains underexplored. This study examines student experiences and…

STEM fields, such as physics, increasingly rely on complex programs to analyse large datasets, thus teaching students the required programming skills is an important component of all STEM curricula. Since undergraduate students often have no prior coding experience, they are reliant on error messages as the primary diagnostic tool to identify and…