Increasing gender diversity in STEM graduate programs is a challenge. In Brazil, the National Council for Scientific and Technological Development (CNPq) has classified knowledge into different "broad areas", one of which is Exact and Earth Sciences (EES). This area includes the STEM subjects: Physics, Computer Science, Mathematics, Statistics and Chemistry. These EES areas have a low representation of women. The University of Brasília, one of the top 10 universities in Brazil, has graduate programs (master’s and doctoral degrees) in all these subjects. In this context, this paper has the main research question: What is the level of gender diversity in each EES area at the University of Brasília in master’s and doctoral programs? This research question was analyzed with the indicators of student enrollment, number of graduations, and retention rates in the programs. The data used for analysis were the available Brazilian open public data of graduate programs for 11 years, 2007-2017. The findings include that women are in the minority in the total number of graduates in Computer Science and Physics. Despite the low number of women overall in EES, the Chemistry program stands out with the highest female participation, reaching more women than men at the doctorate level. The program that has the fewest women is Computer Science. This paper presents all the results of this study.

Detection of plagiarism in students' source codes in college-level programming courses is an important topic for instructors and institutions that seek to pursue project-based learning while enforcing honor codes and maintaining traditional grade-based skill assessment methods. There are different approaches for plagiarism detection currently being researched. This paper aims to answer the question: What does the literature report on source code plagiarism detection in university settings? To answer that, we used a systematic mapping process of recent literature. We selected 109 papers published between 2015 and 2020 that deal with this subject specifically in an educational context. We found that this research area is currently expanding and being studied worldwide. There were papers from 37 different countries, and the number of publications per year has been increasing since 2017. The most targeted programming languages are Java, C++, C, and Python. The most studied plagiarism detection tools are MOSS, JPlag, SIM, Plaggie, and Sherlock. Our study also identified new methodologies created to tackle this problem, such as the analysis of students' typing patterns or their coding style. We noticed that the proposed solutions are mainly based on static source code analysis instead of following the development process. This paper describes our findings.

Full Paper - The field of Computer Science (CS) has been of little interest to women straight out of high school when considering undergraduate majors in Brazil. At the University of Brasília, a top-ten university in Brazil, female undergraduate students account for less than 15% of the students in the Department of Computer Science. According to Stout and Blaney, a sense of intellectual belonging is “the sense that one is believed to be a competent member of the community”. This perception may be especially challenging for members of underrepresented minority groups, such as female undergraduate students in CS majors. In this context, this paper addresses two research questions: i) “How does the intellectual sense of belonging of female students compare to the male students' in introduction to computer science courses?”; ii) Is it similar for female undergraduate students in both CS and non-CS majors?”. We devised a questionnaire for students in the introduction to computer science courses for different majors. We analyzed the responses and, in general, introductory programming courses are challenging for all students, however, female students feel worse about their computing competencies than male ones.

Game engines boost software reuse during development activities by centralizing commonly used domain abstractions within a set of coherent application programming interfaces. Most current game engines focus on class hierarchies, which is the intuitive way to model entity taxonomies but may lead to naming conflicts and code duplication. Component based engines, conversely, minimize this problem by exposing features through components instead. However, due to strong coupling that can still be introduced when using direct access to provide component communication, dynamic entity adaptability may be hindered. Gear2D is a game engine that uses a different approach, providing dynamic entity adaptability through decoupled components. This design results in greater flexibility for creating games, a characteristic discussed through a superficial comparison with a well known game engine and through the development of two nontrivial components: an AI pathfinder and a Lua proxy.