Background and Context. Increasing gender diversity in the field of Computer Science (CS) benefits the economy as well as gender equality. However, several obstacles - including underdeveloped CS interests, lack of programming experience, and a misfit with the stereotypes of computer scientists - prevent women from entering the field. Although these barriers develop from an early age, research focused on children is limited. Furthermore, limited work is done within European countries. Objectives. In this study, we research the interest children aged 7 to 14 have in a CS career. Additionally, we look into whether children with different characteristics have a different interest in CS. As such our research question: How does children's interest in a CS career differ based on their a) age, b) gender, c) computer interests, d) programming experience, and e) stereotypical beliefs? Method. We collected data from 200 children in a science museum located in the Netherlands. We gathered data on their gender, age, computer interests, programming experience, stereotypical beliefs and interest in becoming a programmer - as representative of a CS career. We used self-reported closed questions and reduced-length Child Implicit Association Tests. Findings. In general, the participating children are not interested in a CS career. We did find several characteristics related to a higher interest in a CS career: being a boy, having an interest in computers or video gaming, gaining programming experience at home or at an out-of-school activity, and the belief that programmers are social. Implications. To increase the participation of women in CS, we suggest motivating girls more to engage in computer and programming activities - especially out-of-school activities - while ensuring that these activities are gender inclusive.@en

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.@en

Interest in data systems education is increasing, especially with the rise in demand for well-trained and re-trained data scientists. The database and the computing education research communities have complementary perspectives and experiences to share with each other. The DataEd workshop is organized as a dedicated venue for these communities to come together to share findings, cross-pollinate perspectives and methods, and shed light on opportunities for mutual progress in data systems education. In the DataEd workshop, we will present and discuss data management systems education experiences and research via keynotes and paper and poster presentations. @en

Massive Open Online Courses (MOOCs) aim to educate the world. More often than not, however, MOOCs fall short of this goal — a majority of learners are already highly educated (with a Bachelor degree or more) and come from specific parts of the (developed) world. Learners from developing countries without a higher degree are underrepresented, though desired, in MOOCs. One reason for those learners to drop out of a course can be found in their financial realities and the subsequent limited amount of time they can dedicate to a course besides earning a living. If we could pay learners to take a MOOC, this hurdle would largely disappear. With MOOCS, this leads to the following fundamental challenge: How can learners be paid at scale? Ultimately, we envision a recommendation engine that recommends tasks from online market places such as Upwork or witmart to learners, that are relevant to the course content of the MOOC. In this manner, the learners learn and earn money. To investigate the feasibility of this vision, in this paper we explored to what extent (1) online market places contain tasks relevant to a specific MOOC, and (2) learners are able to solve real-world tasks correctly and with sufficient quality. Finally, based on our experimental design, we were also able to investigate the impact of real-world bonus tasks in a MOOC on the general learner population.@en

When teaching novices programming, misconceptions can occur. Misconception are incorrect beliefs about certain programming concept. For example, some novices think that a variable can hold multiple values, in the case of two consecutive assignment statements, such as x = 5; x = 7. While explaining variables introductory materials often use the metaphor of a box for a variable, which might contribute to the 'multiple values' hypothesis. To investigate this, we design and run a controlled experiment with 496 novice programmers, both children and adults. Half of our participants receive an introductory programming lesson in which we explain a variable as a box, while the other half of participants receive the explanation of a variable as being a label. They are subsequently questioned about their understanding of variables. Our results show that, for the simple questions involving one assignment, the box group performs better. However, for questions involving the misconception - with two consecutive assignment statements - the label group outperforms the box group. This however primarily occurs when considering variables of type string, for integers subjects interpret the statements as numeric values to be added.@en

Block-based programming languages like Scratch, Alice and Blockly are becoming increasingly common as introductory languages in programming education. There is substantial research showing that these visual programming environments are suitable for teaching programming concepts. But, what do people do when they use Scratch? In this paper we explore the characteristics of Scratch programs. To this end we have scraped the Scratch public repository and retrieved 250,000 projects. We present an analysis of these projects in three different dimensions. Initially, we look at the types of blocks used and the size of the projects. We then investigate complexity, used abstractions and programming concepts. Finally we detect code smells such as large scripts, dead code and duplicated code blocks. Our results show that 1) most Scratch programs are small, however Scratch programs consisting of over 100 sprites exist, 2) programming abstraction concepts like procedures are not commonly used and 3) Scratch programs do suffer from code smells including large scripts and unmatched broadcast signals.@en

Block-based programming languages like Scratch, Alice and Blockly are becoming increasingly common as introductory languages in programming education. There is substantial research showing that these visual programming environments are suitable for teaching programming concepts. But, what do people do when they use Scratch? In this paper we explore the characteristics of Scratch programs. To this end we have scraped the Scratch public repository and retrieved 250,000 projects. We present an analysis of these projects in three different dimensions. Initially, we look at the types of blocks used and the size of the projects. We then investigate complexity, used abstractions and programming concepts. Finally we detect code smells such as large scripts, dead code and duplicated code blocks. Our results show that 1) most Scratch programs are small, however Scratch programs consisting of over 100 sprites exist, 2) programming abstraction concepts like procedures are not commonly used and 3) Scratch programs do suffer from code smells including large scripts and unmatched broadcast signals.@en

In the last few years, many books, online puzzles, apps and games have been created to teach young children programming. However, most of these do not introduce children to broader concepts from software engineering, such as debugging and code quality issues like smells, duplication, refactoring and naming. To address this, we designed and ran an online introductory Scratch programming course in which we teach elementary programming concepts and software engineering concepts simultaneously. In total 2,220 children actively participated in our course in June and July 2016, most of which (73%) between the ages of 7 and 11. In this paper we describe our course design and analyze the resulting data. More specifically, we investigate whether 1) students find programming concepts more difficult than software engineering concepts, 2) there are age-related differences in their performance and 3) we can predict successful course completion. Our results show that there is no difference in students' scores between the programming concepts and the software engineering concepts, suggesting that it is indeed possible to teach these concepts to this age group. We also find that students over 12 years of age perform significantly better in questions related to operators and procedures. Finally, we identify the factors from the students' profile and their behaviour in the first week of the course that can be used to predict its successful completion.@en

Recently, block-based programming languages like Alice, Scratch and Blockly have become popular tools for programming education. There is substantial research showing that block-based languages are suitable for early programming education. But can block-based programs be smelly too? And does that matter to learners? In this paper we explore the code smells metaphor in the context of block-based programming language Scratch. We conduct a controlled experiment with 61 novice Scratch programmers, in which we divided the novices into three groups. One third receive a non-smelly program, while the other groups receive a program suffering from the Duplication or the Long Method smell respectively. All subjects then perform the same comprehension tasks on their program, after which we measure their time and correctness. The results of the experiment show that code smell indeed influence performance: subjects working on the program exhibiting code smells perform significantly worse, but the smells did not affect the time subjects needed. Investigating different types of tasks in more detail, we find that Long Method mainly decreases system understanding, while Duplication decreases the ease with which subjects modify Scratch programs.@en

Recently, block-based programming languages like Alice, Scratch and Blockly have become popular tools for programming education. There is substantial research showing that block-based languages are suitable for early programming education. But can block-based programs be smelly too? And does that matter to learners? In this paper we explore the code smells metaphor in the context of block-based programming language Scratch. We conduct a controlled experiment with 61 novice Scratch programmers, in which we divided the novices into three groups. One third receive a non-smelly program, while the other groups receive a program suffering from the Duplication or the Long Method smell respectively. All subjects then perform the same comprehension tasks on their program, after which we measure their time and correctness. The results of the experiment show that code smell indeed influence performance: subjects working on the program exhibiting code smells perform significantly worse, but the smells did not affect the time subjects needed. Investigating different types of tasks in more detail, we find that Long Method mainly decreases system understanding, while Duplication decreases the ease with which subjects modify Scratch programs.@en

Spreadsheets can be considered to be the world's most successful end-user programming language. In fact, one could say spreadsheets are programs. This paper starts with a comparison of spreadsheets to software: spreadsheets are similar in terms of applications domains, expressive power and maintainability problems. We then reflect upon what makes spreadsheets successful: liveness, directness and an easy deployment environment seem contribute largely to their success. Being a programming language, several techniques from software engineering can be applied to spreadsheets. We present an overview of such research directions, including spreadsheet testing, reverse engineering, smell detection, clone detection and refactoring. Finally, open challenges and future plans for the domain of spreadsheet software engineering are presented.@en

Spreadsheets can be considered to be the world's most successful end-user programming language. In fact, one could say spreadsheets are programs. This paper starts with a comparison of spreadsheets to software: spreadsheets are similar in terms of applications domains, expressive power and maintainability problems. We then reflect upon what makes spreadsheets successful: liveness, directness and an easy deployment environment seem contribute largely to their success. Being a programming language, several techniques from software engineering can be applied to spreadsheets. We present an overview of such research directions, including spreadsheet testing, reverse engineering, smell detection, clone detection and refactoring. Finally, open challenges and future plans for the domain of spreadsheet software engineering are presented.@en