Teaching algorithmic thinking enables students to use their knowledge in various contexts to reuse existing solutions to algorithmic problems. The aim of this study is to examine how students recognize which algorithmic concepts can be used in a new situation. We developed a card sorting task and investigated the ways in which secondary school students arranged algorithmic problems (Bebras tasks) into groups using algorithm as a criterion. Furthermore, we examined the students’ explanations for their groupings. The results of this qualitative study indicate that students may recognize underlying algorithmic concepts directly or by identifying similarities with a previously solved problem; however, the direct recognition was more successful. Our findings also include the factors that play a role in students’ recognition of algorithmic concepts, such as the degree of similarity to problems discussed during lessons. Our study highlights the significance of teaching students how to recognize the structure of algorithmic problems.
Source code plagiarism is an emerging issue in computer science education. As a result, a number of techniques have been proposed to handle this issue. However, comparing these techniques may be challenging, since they are evaluated with their own private dataset(s). This paper contributes in providing a public dataset for comparing these techniques. Specifically, the dataset is designed for evaluation with an Information Retrieval (IR) perspective. The dataset consists of 467 source code files, covering seven introductory programming assessment tasks. Unique to this dataset, both intention to plagiarise and advanced plagiarism attacks are considered in its construction. The dataset's characteristics were observed by comparing three IR-based detection techniques, and it is clear that most IR-based techniques are less effective than a baseline technique which relies on Running-Karp-Rabin Greedy-String-Tiling, even though some of them are far more time-efficient.
Programming is one of the basic subjects in most informatics, computer science mathematics and technical faculties' curricula. Integrated overview of the models for teaching programming, problems in teaching and suggested solutions were presented in this paper. Research covered current state of 1019 programming subjects in 715 study programmes at total of 218 faculties and 143 universities in 35 European countries that were analyzed. It was concluded that while most of the programmes highly support object-oriented paradigm of programming, introductory programming subjects are mainly based on imperative paradigm.
In this article we report about a study to assess Dutch teachers' Pedagogical Content Knowledge (\small PCK), with special focus on programming as a topic in secondary school Informatics education. For this research, we developed an online research instrument: the Online Teacher \small PCK Analyser (OTPA). The results show that Dutch teachers' \small PCK scores between low and medium. Also we enquired whether there is any relation between teachers' \small PCK and the textbooks they use by comparing the results of this study with those of a previous one in which the \small PCK of textbooks was assessed. The results show that there is no strong relation. Finally, we looked for trends between teachers' \small PCK and their educational backgrounds, as most of the Dutch teachers have a different background than Informatics. The results show that also in this case there is no strong relation.
Mongolia started using Information and Communication Technology (ICT) in secondary education relatively late. The computer training and informatics has been included as a subject in the secondary school curriculum in Mongolia since 1988 and in the university curriculum since 1982. This paper presents current situation of informatics education in Mongolia. SWOT (Strength, Weakness, Opportunity, and Threat) analysis of Informatics Education in Mongolia, conclusions and future recommendations are also presented.