Learning to program has long been known to be a difficult task, requiring a student to develop both fluency in the syntax and grammar of a formal programming language and learn the problem-solving approaches and techniques of computational thinking. The successful teaching strategies of the past have involved maintaining small teacher-student…

Software security is inevitably dependent on developers' ability to to design and implement software without security bugs. Perhaps unsurprisingly, developers often fail to do this. Our goal is to understand this from a usability perspective, identifying how we might best train developers and equip them with the right software tools. To this end,…

Contribution: Research has shown that computer science (CS) students who start programming assignments (PAs) early generally receive higher grades. This article presents and evaluates a gamification approach that utilizes software engineering tools to motivate CS students to start and finish PAs earlier. Background: CS can be difficult to learn…

Fashion designers in the digital era will be expected to have a profound knowledge of programming and physical computing. Therefore, finding effective methods to adopt E-textiles in fashion education is developing imperative furtherance. E-textiles are clothes embedded with microcomputers, digital components (sensor, LED), and other electronic…

The COVID-19 pandemic has swiftly forced a change in learning strategies across educational institutions, from extensively relying on in-person activities toward online teaching. It is particularly difficult to adapt courses that depend on physical equipment to be now carried out remotely. This is the case for bioinformatics, which typically…

Teaching students statistical programming languages while simultaneously teaching them how to debug erroneous code is challenging. The traditional programming course focuses on error-free learning in class while students' experiences outside of class typically involve error-full learning. While error-free teaching consists of focused lectures…

Computer use has become a fact of life, especially for children, many of whom were forced to switch to online learning during the COVID-19 pandemic and resorted to digital hobbies as a safety measure. Further the amount of time children spend on computers, as well as the number of different computer devices that pervade our post-pandemic society…

Computational thinking in physics has many different forms, definitions, and implementations depending on the level of physics or the institution it is presented in. To better integrate computational thinking in introductory physics, we need to understand what physicists find important about computational thinking in introductory physics. We…

Computation is intertwined with essentially all aspects of physics research and is invaluable for physicists' careers. Despite its disciplinary importance, integration of computation into physics education remains a challenge and, moreover, has tended to be constructed narrowly as a route to solving physics problems. Here, we broaden Physics…

In the last years, a growing trend in different educational contexts focused on Computational Thinking (CT) skills acquisition for both in-service teachers and students. But very low attention has been paid to pre-service teachers' education in regards to CT skills. To solve this issue, an empirical experimentation has been carried out with 141…

Machine learning is a popular topic in data analysis and modeling. Many different machine learning algorithms have been developed and implemented in a variety of programming languages over the past 20 years. In this article, we first provide an overview of machine learning and clarify its difference from statistical inference. Then, we review…

The development of computational thinking is a major topic in K-12 education. Many of these experiences focus on teaching programming using block-based languages. As part of these activities, it is important for students to receive feedback on their assignments. Yet, in practice it may be difficult to provide personalized, objective and consistent…

Rough set theory (RST) was proposed by Zdzistaw Pawlak (Pawlak,1982) as a methodology for data analysis using the notion of discernibility of objects based on their attribute values. The main advantage of using RST approach is that it does not need additional assumptions--like data distribution in statistical analysis. Besides, it provides…

The study develops a method for monitoring and management of the quality of educational programs using software instruments. The method describes each of the monitoring implementation stages in detail specifying the input and output data, as well as the controls that affect the time and quality of the implementation of the corresponding stage.…

We characterize the recently included programming content in Swedish mathematics textbooks for elementary school. Especially, the connection between programming content and traditional mathematical content has been considered. The analytical tools used are based on the so-called 5E's, a theoretical framework of action, developed within the…