Women are underrepresented in Computer Science (CS). Closing the gender gap in CS benefits the economy, gender equality and society. However, girls have low CS interest while interest energizes learning and guides career trajectories. We explore the effects of the user interface of Hedy, a graduate language which teaches the syntax of Python, on the development of CS interest in girls.@en

Motivation. Many people interested in learning a programming language choose online courses to develop their skills. The concept of variables is one of the most foundational ones to learn, but can be hard to grasp for novices. Variables are researched, but to our knowledge, few empirical observations on how the concept is taught in practice exist. Objective. We investigate how the concept of variables, and the respective naming practices, are taught in introductory Massive Open Online Courses (MOOCs) teaching programming languages. Methods. We gathered qualitative data related to variables and their naming from 17 MOOCs. Collected data include connections to other programming concepts, formal definitions, used analogies, and presented names. Results. We found that variables are often taught in close connection to data types, expressions, and program execution and are often explained using the 'variable as a box' analogy. The latter finding represents a stronger focus on 'storing values', than on naming, memory, and flexibility. Furthermore, MOOCs are inconsistent when teaching naming practices. Conclusions. We recommend teachers and researchers to pay deliberate attention to the definitions and analogies used to explain the concept of variables as well as to naming practices, and in particular to variable name meaning.

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Motivation Only 27% of computer and mathematical scientists in the United States and 18% of IT specialists in Europe are women. The under-representation of women in the field of Computer Science is, among other things, influenced by stereotypes of computer scientists. These stereotypes include being male, asocial and having an (obsessive) interest in computers. Even though stereotypical beliefs can develop at an early age, research on children’s stereotypes of computer scientists is sparse and inconclusive.
Objectives Stereotypes we hold can be implicit or unconscious beliefs, or explicit or conscious beliefs. In this study, we focus on children’s implicit and explicit stereotypes regarding computer scientists’ gender, social skills and interests. We also study whether explaining what a computer scientist does affects these stereotypes.
Method We study the implicit stereotypes through the reduced-length Child Implicit Association Test and the explicit stereotypes through self-reported absolute and relative Likert scale questions. We gathered data on 564 children between the age of 7 and 18 who were visiting a science museum. The participants in the experiment group (n=352) watch a video of either a man or woman explaining what a computer scientist does at the start of the study.
Results We found weak implicit stereotypical beliefs on computer scientists’ social skills and moderate implicit stereotypical beliefs on computer scientists’ interests. We also found explicit stereotypes on computer scientists’ gender, social skills and interests. Measuring the effects of the intervention, we found significant differences between the control and experiment group in their explicit stereotypes on computer scientists’ social skills.
Discussion The amount of scientific work on children’s stereotypes regarding computer scientists is still limited. Applying the reduced-length Child Implicit Association Test to measure children’s stereotypes on computer scientists has, to our knowledge, not been done before. Understanding children’s stereotypes and how to tackle them contributes to closing the gender gap in Computer Science.@en

Grading large classes has become a challenging and expensive task for many universities. The Delft University of Technology (TU Delft), located in the Netherlands, has observed a large increase in student numbers over the past few years. Given the large growth of the student population, grading all the submissions results in high costs. We made use of self and peer grading in the 2018-2019 edition of our software testing course. Students worked in teams of two, and self and peer graded three assignments in our course. We ended up with 906 self and peer graded submissions, which we compared to 248 submissions that were graded by our TAs. In this paper, we report on the differences we observed between self, peer, and TA grading. Our findings show that: (i) self grades tend to be 8-10% higher than peer grades on average, (ii) peer grades seem to be a good approximator of TA grades; in cases where self and peer grade differ significantly, the TA grade seems to lie in between, and (iii) the gender and the nationality of the student do not seem to affect self and peer grading.

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The use of spreadsheets in industry is widespread. It is known that spreadsheets have an average life span of five years, and during this life span, they are used on average by thirteen different persons. Consequently, spreadsheets need maintenance, and knowledge about the spreadsheet needs to be transferred from one user to another. To minimize the risk of introducing new errors, a thorough understanding of the spreadsheet's formulas is needed during maintenance and knowledge transfer tasks.

Research on the use of block-based languages has shown that they positively affect the comprehension of program code. We hypothesize that using a block-based representation of a spreadsheet formula will positively affect formula comprehension.

Hence, we extended XLBlocks, a block-based formula editor for spreadsheets, with the functionality to generate a block-based representation of an existing formula. We conduct a think-aloud study with twenty-one experienced spreadsheet users from industry and ask them to perform a set of spreadsheet comprehension tasks using XLBlocks. During an interview, we ask them, using the Cognitive Dimensions of Notations framework, to reflect on the use of XLBlocks.

We found that participants preferred to use the block-based representation of formulas when analyzing or explaining formulas or to implement non-trivial changes. Named function parameters and the absence of parentheses and commas make functions easier to understand. Furthermore, the visualization enables the user to separate smaller parts in the formula, which improves comprehension. Finally, the possibility to navigate from formula to formula makes it clear how formulas work together and improve the understanding of the spreadsheet as a whole.@en