Teaching software engineering (SWE) as a core computer science course (ACM, 2013) is a challenging task. The challenge lies in the emphasis on what a large-scale software means, implementing teamwork, and teaching abstraction in software design while simultaneously engaging students into reasonable coding tasks. The abstraction of the system…

Machine learning, a subdomain of artificial intelligence, is a widespread technology that is molding how chemists interact with data. Therefore, it is a relevant skill to incorporate into the toolbox of any chemistry student. This work presents a workshop that introduces machine learning for chemistry students based on a set of Python notebooks…

Programming skills are increasingly important to the current digital economy, yet these skills have long been regarded as challenging to acquire. A central challenge in learning programming skills involves the simultaneous use of multiple component skills. This article investigates why students struggle with integrating component skills--a…

Learning basic programming concepts in computer science-related fields poses a challenge for students, to the extent that it becomes an academic-social problem, resulting in high failure and dropout rates. Proposed solutions to the problem can be found in the literature, such as the development of new programming languages and environments, the…

Learning in the computer laboratory is an important component when students learn computer programming. In this article, we analyse empirical data on novice students working in pairs in the laboratory. Using an approach inspired by phenomenography and variation theory, we specifically focus on how students' learning of theory and their learning of…

Due to the development of deep learning technology, its application in education has received increasing attention from researchers. Intelligent agents based on deep learning technology can perform higher order intellectual tasks than ever. However, the high deployment cost of deep learning models has hindered their widespread application in…

Background: The pedagogy of computational thinking has gained extensive traction across numerous nations globally, with a particular emphasis on nurturing computational thinking in the formative years of early childhood. Nevertheless, the efficacy of diverse instructional approaches in the domain of programming education, with regards to fostering…

While the introduction of memory-safe programming languages into embedded, Cyber-Physical Systems (CPS) offers an opportunity to eliminate many system vulnerabilities, a pragmatic adoption of memory-safe programming languages often necessitates incremental deployment due to practical development constraints, such as the size of many legacy code…

Physical experiments in classrooms have many benefits for student learning, including increased student interest, participation and knowledge retention. While experiments are common in engineering and physics classes, they are seldom used in first-year calculus, where the focus is on solving problems analytically and, occasionally, numerically. In…

The study examined the effect of teaching text-based programming with a physical programming tool on secondary school students' computational thinking skills and self-efficacy perceptions. The study was conducted according to a sequential explanatory design as a mixed method research. The study group consisted of 85 secondary school students.…

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…

This study investigates the contribution of plugged and un-plugged activities to primary school students' development of computational thinking skills. The plugged and unplugged activities were used together in this study. In the implementation, in addition to the un-plugged activities prepared by the "Ministry of National Education,"…

The estimation of RxC ecological inference contingency tables from aggregate data is one of the most salient and challenging problems in the field of quantitative social sciences, with major solutions proposed from both the ecological regression and the mathematical programming frameworks. In recent decades, there has been a drive to find…

Aim/Purpose: The purpose of this research is to examine the effect of computer-assisted gamification on the learning motivation of computer programming students. Background: The teaching-learning of computer programming involves challenges that imply using learning environments in which the student is actively involved. Gamification is an…

This study describes the most relevant problems and solutions found in the literature on teaching and learning of object-oriented programming (OOP). The identification of the problem was based on tertiary studies from the IEEE Xplore, Scopus, ACM Digital Library and Science Direct repositories. The problems and solutions identified were ranked…