Informatics in Education

The new Croatian Informatics curriculum, which introduces computational thinking concepts into learning outcomes has been put into practice. A computational thinking assessment model reflecting the learning outcomes of the Croatian curriculum was created using an evidence-centered design approach. The possibility of assessing the computational thinking concepts, abstraction, decomposition, and algorithmic thinking, in an actual classroom situation and examples of such assessment is increasingly coming to the forefront of computer science educational research. Precisely for that purpose, the research was conducted. Research data are collected through the test and questionnaire of 407 pupils (10 middle schools, age 12), analysed by exploratory factor analysis and non-parametric tests. Results showed that the presented model was suitable to assess the understanding of the concepts of abstraction and algorithmic thinking, independently of the previous experience with programming languages and pupil's gender, while assessment of decomposition needs more work and improvement, some recommendations are provided. Also, it received positive feedback from pupils and teachers what implicated that such an assessment model could help teachers in building a real-time measurement instrument.

Due to technological advancements, robotics is findings its way into the classroom. However, workload for teachers is high, and teachers sometimes lack the knowledge to implement robotics education. A key factor of robotics education is peer learning, and having students (near-)peers teach them robotics could diminish workload. Therefore, this study implemented near-peer teaching in robotics education. 4 K10-11 secondary school students were teachers to 83 K5-6 primary school students. The intervention included 4 3-hour robotics lessons in Dutch schools. Primary school students completed a pre- and post-intervention questionnaire on their STEM-attitudes and near-peer teaching experience, and a report on their learning outcomes. Interaction with near-peer teachers was observed. After the lessons, a paired-samples t-test showed that students had a more positive attitude towards engineering and technology. Students also reported a positive near-peer teaching experience. Conventional content analysis showed that students experienced a gain in programming and robotics skill after the lessons, and increased conceptual understanding of robotics. The role the near peer teachers most frequently fulfilled was formative assessor. Near-peer teachers could successfully fulfil a role as an engaging information provider. This study shows that near-peer teachers can effectively teach robotics, diminishing workload for teachers. Furthermore, near-peer robotics lessons could lead to increased STEM-attitudes.

Coding and computational thinking have recently become compulsory skills in many school systems globally. Teaching these new skills presents a challenge for many teachers. A notable example of professional development designed using Constructionist principles to address this challenge is ScratchEd. Upon reflecting on her experiences designing and running ScratchEd, Karen Brennan identified five tensions faced by professional development providers, and proposed that these tensions could be used for scrutinising and critiquing professional development. In this paper we analyse, through the lens of Brennan's tensions, the process we have followed to design, evaluate and improve professional development. We argue that while we have experienced the same tensions, the extent to which we assess learning is a new tension that extends those identified by Brennan. There are strong reasons to assess teachers' knowledge, however, quantitative measures of learning could be at odds with Constructionism: as Papert argued in Mindstorms, constructionist educators should study their learning environments as anthropologists. Consequently, we have called this new tension the tension between anthropology and assessment.

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.

Despite a growing effort to implement computational thinking (CT) skills in primary schools, little research is reported about what CT skills to teach at what age. Therefore, the research questions that guide this study read: (1) How is age related to students' success in computational thinking tasks? (2) How are computational thinking tasks perceived by students? (3) How do students' experience learning with respect to computational thinking? 200 primary school students between the age of 6 and 12 participated in this study. These students got introduced to two CT subjects: abstraction and decomposition. We found that age seems to be related with these concepts, with an interaction effect for gender in the abstraction task. No differences found between young and older students in the constructs perceived difficulty, cognitive load, and flow indicate that young primary school students can engage in learning these CT skills.