The Code City metaphor stands as a prominent and widely recognized technique for visualizing software projects. This paper explores the application of the Code City metaphor within the context of Scratch, the most prevalent block-based programming language employed in educational settings. By leveraging the Code City metaphor and its implementation in BabiaXR, we have developed a prototype that renders Scratch projects in a visually intuitive urban landscape. We posit that the integration of the Code City metaphor with Scratch projects holds significant potential for enhancing learning environments by providing novel perspectives on project structure and potential areas for improvement.

The introduction of Computational Thinking skills at school has mostly been associated with programming skills. In this paper we present an approach that is based on modeling, a skill that is commonly taught in Computer Science degrees, often in the last years as it is considered a higher-level, complex skill. Modeling includes various thinking processes like abstraction, reduction, structuring, generalization, among others, that are part of computational thinking in particular and problem solving in general, too. Our hypothesis is that using different modeling techniques from computer science (e.g., UML diagrams) in several subjects at school can be a good way to introduce computational thinking. Therefore we have performed a semi-controlled experiment with Ni=558 students (age 8-16) and N2=18 educators that have used modeling in their lessons. Our results show a promising effect of the use of modeling in the lessons. Educators have a positive vision of modeling.

The inclusion of artificial intelligence (AI) in education is increasingly highlighted by international organizations and governments around the world as a cornerstone to enable the adoption of AI in society. That is why we have developed LearningML, aiming to provide a platform that supports educators and students in the creation of hands-on AI projects, specifically based on machine learning techniques. In this investigation we explore how a workshop on AI and the creation of programming projects with LearningML impacts the knowledge on AI of students between 10 and 16 years. 135 participants completed all phases of the learning experience, which due to the COVID-19 pandemic had to be performed online. In order to assess the AI knowledge we created a test that includes different kinds of questions based on previous investigations and publications - resulting in a reliable assessment instrument. Our findings show that the initiative had a positive impact on participants? AI knowledge, being the enhancement especially important for those learners who initially showed less familiarity with the topic. We observe, for instance, that while previous ideas on AI revolve around the term robot, after the experience they do around solve and problem. Based on these results we suggest that LearningML can be seen as a promising platform for the teaching and learning of AI in K-12 environments. In addition, researchers and educators can make use of the new instrument we provide to evaluate future educational interventions.

In recent years we are witnessing movements around the world to bring computer programming to schools. Lots of these initiatives, however, have been conceived to address the shortage of professionals in the technology sector, an approach that is encouraged by the software industry. On the contrary, this article argues that the focus should swift towards computational thinking, an ability that goes far beyond computer science or technology, fostering fundamental skills for the citizens of the twenty-first century. In this paper we summarize the findings of recent investigations that study computational thinking from different perspectives, explaining what this new skill is made of, presenting outcomes of school interventions showing relationships between the development of this ability and improvements in different subjects and soft skills, presenting technologies to foster its development, and reviewing tools that support educators in the assessment of this skill.

While scholarly interest typically focuses on what student designers learn from creating digital games, there has been little investigation into what student designers make. This paper analyzes what design patterns emerge within a set of games from student designers who were instructed to design educational games about climate change using a particular design tool called Scratch. In this preliminary investigation, 19 games are analyzed using the triadic game design framework, which explores relationships between the topic (Reality), learning goal (Meaning) and genre (Play) of serious games. Here we suggest that these decisions fell into a few prototypical patterns, and suggest further paths of inquiry into students' designs regarding considering students' experience with games and supporting the representation of abstract concepts.

Scratch is increasingly popular, both as an introductory programming language and as a research target in the computing education research field. In this paper, we present a dataset of 250K recent Scratch projects from 100K different authors scraped from the Scratch project repository. We processed the projects' source code and metadata to encode them into a database that facilitates querying and further analysis. We further evaluated the projects in terms of programming skills and mastery, and included the project scoring results. The dataset enables the analysis of the source code of Scratch projects, of their quality characteristics, and of the programming skills that their authors exhibit. The dataset can be used for empirical research in software engineering and computing education.

The use of computer programming in K-12 spread into schools worldwide in the 70s and 80s of the last century, but it disappeared from the educational landscape in the early 90s. With the development of visual programming languages such as Scratch, this movement has emerged again in recent years, as teachers at all educational levels and from different disciplines consider that the use of programming enhances learning in many subjects and allows students to develop important skills. The systematic literature review presented in this article aims to summarize the results of recent research using programming with Scratch in subjects not related to computing and communications, as well as studies analyzing the kind of skills students develop while learning to code in this environment. Although the analyzed papers provide promising results regarding the use of programming as an educational resource, this review highlights the need to conduct more empirical research in classrooms, using larger samples of students that allow to obtain clear conclusions about the types of learning that could be enhanced through programming.

The development of computational thinking skills through computer programming is a major topic in education, as governments around the world are introducing these skills in the school curriculum. In consequence, educators and students are facing this discipline for the first time. Although there are many technologies that assist teachers and learners in the learning of this competence, there is a lack of tools that support them in the assessment tasks. This paper compares the computational thinking score provided by Dr. Scratch, a free/libre/open source software assessment tool for Scratch, with McCabe's Cyclomatic Complexity and Halstead's metrics, two classic software engineering metrics that are globally recognized as a valid measurement for the complexity of a software system. The findings, which prove positive, significant, moderate to strong correlations between them, could be therefore considered as a validation of the complexity assessment process of Dr. Scratch.

One of the latest trends in the educational landscape is the introduction of computer programming in the K-12 classroom to develop computational thinking in students. As computational thinking is not a skill exclusively related to computer science, it is assumed – but not yet scientifically proven – that the problem solving process may be generalized and transferred to a wide variety of problems. This paper presents a research designed to test whether the use of coding in Maths classes could have a positive impact on learning outcomes of students in their mathematical skills. Therefore, the questions we want to investigate in this paper are if the use of programming in Maths classes improves (a) modeling process and reality phenomena, (b) reasoning, (c) problem formulation and problem solving, and (d) comparison and execution of procedures and algorithms. We have therefore designed a quantitative, quasi-experimental experiment with 42 participating 6th grade (11 and 12 years old) students. Results show that there is a statistically significant increase in the understanding of mathematical processes in the experimental group, which received training in Scratch.

The growth of employment opportunities in the information technology sector and the shortage of well-trained professionals in this field are a recurring theme in recent years in both Europe and North America. In this sense, research studies that analyse the causes of the reduction of students who are interested in computer science mainly point to young people being unaware of the type of tasks computer scientists perform. Therefore, in order to try to reverse this trend many types of initiatives have been organized seeking to bring the world of computing to children and adolescents.

Computational thinking, a problem solving method that uses computer science techniques, has recently become mainstream as many governments and major Internet companies are promoting programming skills among children. However, little is known about how programming affects other aspects of life beyond the acquired programming skills. In this regard, this paper summarizes the work done in the school San Diego and San Vicente (Madrid, Spain) during the third quarter of the year 2013/2014, where we conducted a study with four groups of students in 4th and 5th grade to measure to what extent the use of computer programming in English classes can be an interesting educational tool with a positive impact on the learning otucome of the students. The results show that the groups working with programming activities improved more than the groups using traditional resources. Moreover, when asked via surveys at the end of the study, most students felt that coding was a positive influence, not only for learning English, but for developing other important skills as teamwork and learning to learn.

Using the Scratch environment as a tool to teach programming skills or develop computational thinking is increasingly common in all levels of education, well-documented case studies from primary school to university can be found. However, there are reports that indicate that students learning to program in this environment show certain habits that are contrary to the basic programming recommendations. In our work as instructors with high school students, we have detected these and other bad practices, such as the repetition of code and object naming, on a regular basis. This paper focuses on verifying whether these issues can generally be found in the Scratch community, by analyzing a large number of projects available on the Scratch community website. To test this hypothesis, we downloaded 100 projects and analyzed them with two plug-ins we developed to automatically detect these bad practices. The plug-ins extend the functionality of the Hairball tool, a static code analyzer for Scratch projects. The results obtained show that, in general, projects in the repository also incur in the investigated malpractices. Along with suggestions for future work, some ideas that might assist to address such situations are proposed in the conclusions of the paper.