The development of computational thinking is a major topic in K-12 education. Many of these experiences focus on teaching programming using block-based languages. As part of these activities, it is important for students to receive feedback on their assignments. Yet, in practice it may be difficult to provide personalized, objective and consistent feedback. In this context, automatic assessment and grading has become important. While there exist diverse graders for text-based languages, support for block-based programming languages is still scarce. This article presents CodeMaster, a free web application that in a problem-based learning context allows to automatically assess and grade projects programmed with App Inventor and Snap!. It uses a rubric measuring computational thinking based on a static code analysis. Students can use the tool to get feedback to encourage them to improve their programming competencies. It can also be used by teachers for assessing whole classes easing their workload.
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.