This paper presents a series of basic computational problems that are mathematically and/or graphically appealing, and provides an idea of places one might go in trying to understand what is happening, integrating mathematics, computation, and graphics. The real point of this paper is to make a case, through those examples, for computation as an…

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…

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 is a way of thinking that helps people "think like a computer scientist" to solve practical problems. However, practicing computational thinking through programming is dependent on the problem solvers' metacognition. This study investigated students' metacognitive planning and problem-solving performance in…

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…

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…

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 qualitative case study was designed to explore pre-service teachers' computational thinking and programming skills in an educational technology course in which block-based programming was introduced in a teacher education program. 12 teacher candidates from different subject areas participated in the study. The findings show that…

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…

This study reports the findings of a program that aims to develop pre-service science teachers' computational problem-solving skills and views on using information and communications technology in science education. To this end, pre-service science teachers were trained on computational thinking, computational problem solving, designing an…

In this study, the effects of Arduino IDE and C++ programming languages were investigated on the computational thinking skills of preservice teachers. The Computational Thinking Skills Scale was administered to preservice teachers. Firstly, a basic programming training was given and then it was asked to create group projects on a voluntary basis.…

Computational notebooks are an increasingly common tool used to support student learning in a variety of contexts where computer programming can be applied. These notebooks provide an easily distributable method of displaying text and images, as well as sections of computer code that can be manipulated and run in real-time. This format allows…

Techniques from the branch of artificial intelligence known as machine learning (ML) have been applied to a wide range of problems in chemistry. Nonetheless, there are very few examples of pedagogical activities to introduce ML to chemistry students in the chemistry education literature. Here we report a computational activity that introduces…

In the past 10 years, new data science courses and programs have proliferated at the collegiate level. As faculty and administrators enter the race to provide data science training and attract new students, the road map for teaching data science remains elusive. In 2019, 69 college and university faculty teaching data science courses and…

When solving counting problems, students often struggle with determining what they are trying to count (and thus what problem type they are trying to solve and, ultimately, what formula appropriately applies). There is a need to explore potential interventions to deepen students' understanding of key distinctions between problem types and to…