What prevents Finnish women from applying to software engineering roles? A preliminary analysis of survey data

Finland is considered a country with a good track record in gender equality. Whilst statistics support the notion that Finland is performing well compared to many other countries in terms of workplace equality, there are still many areas for improvement. This paper focuses on the problems that some women face in obtaining software engineering roles. We report a preliminary analysis of survey data from 252 respondents. These are mainly women who have shown an interest in gaining programming roles by joining the Mimmit koodaa initiative, which aims to increase equality and diversity within the software industry. The survey sought to understand what early experiences may influence later career choices and feelings of efficacy and confidence needed to pursue technology-related careers. These initial findings reveal that women's feelings of computing self-efficacy and attitudes towards software engineering are shaped by early experiences. More negative experiences decrease the likelihood of working in software engineering roles in the future, despite expressing an interest in the field

Evolution in the number of authors of computer science publications

This article analyses the evolution in the number of authors of scientific publications in computer science (CS). This analysis is based on a framework that structures CS into 17 constituent areas, proposed by Wainer et al. (Commun ACM 56(8):67–63, 2013), so that indicators can be calculated for each one in order to make comparisons. We collected and mined over 200,000 article references from 81 conferences and journals in the considered CS areas, spanning a 60-year period (1954–2014). The main insights of this article are that all CS areas witness an increase in the average number of authors, in every decade, with just one slight exception. We ordered the article references by number of authors, in ascending chronological order and grouped them into decades. For each CS area, we provide a perspective of how many groups (1-author papers, 2-author papers and so on) must be considered to reach certain proportions of the total for that CS area, e.g., the 90th and 95th percentiles. Different CS areas require different number of groups to reach those percentiles. For all 17 CS areas, an analysis of the point in time in which publications with n+1 authors overtake the publications with n authors is presented. Finally, we analyse the average number of authors and their rate of increase.This work was supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope UID/CEC/00319/2013

Cognitive Profiles and Education of Female Cyber Defence Operators

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Authorship trends in software engineering

This paper aims to examine authorship trends in software engineering, especially those related to the number of authors, of scientific publications. We collected and mined around 70.000 entries from DBLP for 122 conferences and journals, for the period 1971–2012, in order to process several bibliometric indicators. We provide evidence that the number of authors of articles in software engineering is increasing on average around +0.40 authors/decade. The results also indicate that until 1980, the majority of the articles have a sole author, while nowadays articles with 3 or 4 authors represent almost half of the total.Fundação para a Ciência e a Tecnologia (FCT

Physical Design of VLSI Circuits and the Application of Genetic Algorithms

The task of VLSI physical design is to produce the layout of an integrated circuit. New performance requirements are becoming increasingly dominant in today's sub-micron regimes requiring new physical design algorithms. Genetic algorithms have been increasingly successful when applied in VLSI physical design in the last 10 years. Genetic algorithms for VLSI physical design are reviewed in general. In addition, a specific parallel genetic algorithm is presented for the routing problem in VLSI circuits

Towards Evidence-Based Academic Advising Using Learning Analytics

Academic advising is a process between the advisee, adviser and the academic institution which provides the degree requirements and courses contained in it. Content-wise planning and management of the student’ study path, guidance on studies and academic career support is the main joint activity of advising. The purpose of this article is to propose the use of learning analytics methods, more precisely robust clustering, for creation of groups of actual study profiles of students. This allows academic advisers to provide evidence-based information on the study paths that have actually happened similarly to individual students. Moreover, academic institutions can focus on management and updates of course schedule having an effect of clearly characterized and recognized group of students. Using this approach a model of automated academic advising process, which can determine the study profiles, is presented. The presented model shows the whole automated process, where the learners will be profiled regularly, and where the proper study path will be suggested.peerReviewe