Informatics in Education

In a previous publication we examined the connections between high-school computer science (CS) and computing higher education. The results were promising—students who were exposed to computing in high school were more likely to take one of the computing disciplines. However, these correlations were not necessarily causal. Possibly those students who took CS courses, and especially high-level CS courses in high school, were already a priori inclined to pursue computing education. This uncertainty led us to pursue the current research. We aimed at finding those factors that induced students to choose CS at high school and later at higher-education institutes. We present quantitative findings obtained from analyzing freshmen computing students' responses to a designated questionnaire. The findings show that not only did high-school CS studies have a major impact on students’ choice whether to study computing in higher education—it may have also improved their view of the discipline.

Computer science concepts have an important part in other subjects and thinking computationally is being recognized as an important skill for everyone, which leads to the increasing interest in developing computational thinking (CT) as early as at the comprehensive school level. Therefore, research is needed to have a common understanding of CT skills and develop a model to describe the dimensions of CT. Through a systematic literature review, using the EBSCO Discovery Service and the ACM Digital Library search, this paper presents an overview of the dimensions of CT defined in scientific papers. A model for developing CT skills in three stages is proposed: i) defining the problem, ii) solving the problem, and iii) analyzing the solution. Those three stages consist of ten CT skills: problem formulation, abstraction, problem reformulation, decomposition, data collection and analysis, algorithmic design, parallelization and iteration, automation, generalization, and evaluation.

Research on the effectiveness of introductory programming environments often relies on post-test measures and attitudinal surveys to support its claims; but such instruments lack the ability to identify any explanatory mechanisms that can account for the results. This paper reports on a study designed to address this issue. Using Noss and Hoyles' constructs of webbing and situated abstractions, we analyze programming novices playing a program-to-play constructionist video game to identify how features of introductory programming languages, the environments in which they are situated, and the challenges learners work to accomplish, collectively affect novices' emerging understanding of programming concepts. Our analysis shows that novices develop the ability to use programming concepts by building on the suite of resources provided as they interact with the computational context of the learning environment. In taking this approach, we contribute to computer science education design literature by advancing our understanding of the relationship between rich, complex introductory programming environments and the learning experiences they promote.

We present an overview of the nature of academic dishonesty with respect to computer science coursework. We discuss the efficacy of various policies for collaboration with regard to student education, and we consider a number of strategies for mitigating dishonest behaviour on computer science coursework by addressing some common causes. Computer science coursework is somewhat unique, in that there often exist ideal solutions for problems, and work may be shared and copied with very little effort. We discuss the idiosyncratic nature of how collaboration, collusion and plagiarism are defined and perceived by students, instructors and administration. After considering some of the common reasons for dishonest behaviour among students, we look at some methods that have been suggested for mitigating them. Finally, we propose several ideas for improving computer science courses in this context. We suggest emphasizing the intended learning outcomes of each assignment, providing tutorial sessions to facilitate acceptable collaboration, delivering quizzes related to assignment content after each assignment is submitted, and clarifying the boundary between collaboration and collusion in the context of each course. While this discussion is directed at the computer science community, much may apply to other disciplines as well, particularly those with a similar nature such as engineering, other sciences, or mathematics.

The International Olympiad in Informatics (IOI) aspires to be a science olympiad alongside such international olympiads in mathematics, physics, chemistry, and biology. Informatics as a discipline is well suited to a scientific approach and it offers numerous possibilities for competitions with a high scientific standing. We argue that, in its current form, the IOI fails to be scientific in the way it evaluates the work of the contestants.