Starting from scratch: experimenting with computer science in Flemish secondary education

In the Flemish secondary education curriculum, as in many countries and regions, computer science currently only gets an extremely limited coverage. Recently, in Flanders (and elsewhere), it has been proposed to change this, and try-outs are undertaken, both in and outside of schools. In this paper, we discuss some of those efforts, and in particular take a closer look at the preliminary results of one experiment involving different approaches to programming in grade 8. These experiments indicate that many students from secondary schools would welcome a more extensive treatment of computer science. Planning and implementing such a treatment, however, raises a number of issues, from which in this paper, we formulate a handful as calls for action for the computer science education research community

Development of Computer Science Disciplines - A Social Network Analysis Approach

In contrast to many other scientific disciplines, computer science considers conference publications. Conferences have the advantage of providing fast publication of papers and of bringing researchers together to present and discuss the paper with peers. Previous work on knowledge mapping focused on the map of all sciences or a particular domain based on ISI published JCR (Journal Citation Report). Although this data covers most of important journals, it lacks computer science conference and workshop proceedings. That results in an imprecise and incomplete analysis of the computer science knowledge. This paper presents an analysis on the computer science knowledge network constructed from all types of publications, aiming at providing a complete view of computer science research. Based on the combination of two important digital libraries (DBLP and CiteSeerX), we study the knowledge network created at journal/conference level using citation linkage, to identify the development of sub-disciplines. We investigate the collaborative and citation behavior of journals/conferences by analyzing the properties of their co-authorship and citation subgraphs. The paper draws several important conclusions. First, conferences constitute social structures that shape the computer science knowledge. Second, computer science is becoming more interdisciplinary. Third, experts are the key success factor for sustainability of journals/conferences

Exploring resilience for effective learning in computer science education

Background and context: Many factors have been shown to be important for supporting effective learning and teaching – and thus progression and success – in formal educational contexts. While factors such as key introductory-level computer science knowledge and skills, as well as pre-university learning and qualifications, have been extensively explored, the impact of measures of positive psychology are less well understood for the discipline of computer science. This preliminary work investigates the relationships between effective learning and success, and two measures of positive psychology, Grit (Duckworth’s 12-item Grit scale) [6] and the Nicolson McBride Resilience Quotient (NMRQ) [3], in success in first-year undergraduate computer science to provide insight into the factors that impact on the transition from secondary education into tertiary education

Marketing and Data Science: Together the Future is Ours

The synergistic use of computer science and marketing science techniques offers the best avenue for knowledge development and improved applications. A broad area of complementarity between the typical focus in statistics and computer science and that in marketing offers great potential. The former fields tend to focus on pattern recognition, control and prediction. Many marketing analyses embrace these directions, but also contribute by modeling structure and exploring causal relationships. Marketing has successfully combined foci from management science with foci from psychology and economics. These fields complement each other because they enable a broad spectrum of scientific approaches. Combined, they provide both understanding and practical solutions to important and relevant managerial marketing problems, and marketing science is already very successful at obtaining unique insights from big data

A multinational, multi-institutional study of assessment of programming skills of first-year CS students

In computer science, an expected outcome of a student's education is programming skill. This working group investigated the programming competency students have as they complete their first one or two courses in computer science. In order to explore options for assessing students, the working group developed a trial assessment of whether students can program. The underlying goal of this work was to initiate dialog in the Computer Science community on how to develop these types of assessments. Several universities participated in our trial assessment and the disappointing results suggest that many students do not know how to program at the conclusion of their introductory courses. For a combined sample of 216 students from four universities, the average score was 22.89 out of 110 points on the general evaluation criteria developed for this study. From this trial assessment we developed a framework of expectations for first-year courses and suggestions for further work to develop more comprehensive assessments

A Parameterisation of Algorithms for Distributed Constraint Optimisation via Potential Games

This paper introduces a parameterisation of learning algorithms for distributed constraint optimisation problems (DCOPs). This parameterisation encompasses many algorithms developed in both the computer science and game theory literatures. It is built on our insight that when formulated as noncooperative games, DCOPs form a subset of the class of potential games. This result allows us to prove convergence properties of algorithms developed in the computer science literature using game theoretic methods. Furthermore, our parameterisation can assist system designers by making the pros and cons of, and the synergies between, the various DCOP algorithm components clear