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…

Computational thinking (CT), an essential competency for comprehending and addressing intricate issues in the digital world, has been incorporated into curriculum planning as a goal for programming education. This study introduced flow design into programming curricula to investigate its impact on undergraduates 'CT skills during pair work. Two…

Educational technologists and practitioners have made substantial strides in developing affordable digital and tangible resources to support both formal and informal computer science instruction. However, there is a lack of research on practice-based assignments, such as Internet of Things (IoT) projects, that allow undergraduate students to…

The purpose of this study is to look at how a music programming course affects the development of computational thinking in undergraduate music conservatory students. In addition to teaching the fundamentals of computational thinking, music programming, and logic, the course addresses the Four C's of education. The change in students' attitudes…

Debugging is essential for identifying and rectifying errors in programming, yet time constraints and students' trivialization of errors often hinder progress. This study examines differences in debugging challenges and strategies among students with varying computational thinking (CT) competencies using weekly coding journals from an online…

Many areas of mathematics naturally lend themselves to machine-based computing environments, which suggests that computational environments may serve as useful mediating tools for the teaching and learning of mathematical content. While some mathematics classes are leveraging the use of computational tools, the implementation of computer…

In this article, we seek to understand how university students learn to use programming as an instrument for 'authentic' mathematical investigations. We use the instrumental approach as a framework, focusing on how the transformation of the programming language into an instrument requires that the user develops or mobilizes multiple schemes at…

Artificial intelligence (AI) education is becoming an advanced learning trend in programming education. However, AI subjects can be difficult to understand because they require high programming skills and complex knowledge. This makes it challenging to determine how different departments of students are affected by them. This study draws on…

To help novice learners overcome the obstacles of learning computational thinking (CT) through programming, it is vital to identify difficult CT components. This study aimed to determine the computational concepts and practices that learners may have difficulties acquiring and discuss how programming instructions should be designed to facilitate…

Regular expressions (REs) are often taught to undergraduate computer science majors in the Formal Languages and Automata (FLA) course; they are widely used to implement different software functionalities such as search mechanisms and data validation in diverse fields. Despite their importance, the difficulty of REs has been asserted many times in…

Challenge: The Hodgkin-Huxley membrane conductance model has been featured in biomedical engineering (BME) curricula for decades. A typical BME assignment might require students to apply the relevant equations and parameters to model the generation of action potentials; however, there is opportunity for students to build and explore both…

The ability to properly evaluate one's own academic progress has long been considered a predictor of academic success. However, its distinctive role in the context of computational mathematics remains underexplored. Grounded in social cognitive theory, this study investigates the critical role of self-regulated learning (SRL) strategies in…

We report an educational tool for the upper level undergraduate quantum chemistry or quantum physics course that uses a symbolic approach via the PySyComp Python library. The tool covers both time-independent and time-dependent quantum chemistry, with the latter rarely considered in the foundations course due to topic complexity. We use quantized…

This article reports on a study investigating how computational essays can be used to help students in higher education STEM take up disciplinary epistemic agency--cognitive control and responsibility over one's own learning within the scientific disciplines. Computational essays are a genre of scientific writing that combine live, executable…

Nolan and Temple Lang's "Computing in the Statistics Curricula" (2010) advocated for a shift in statistical education to broadly include computing. In the time since, individuals with training in both computing and statistics have become increasingly employable in the burgeoning data science field. In response, universities have…