Informatics in Education

While graph theory plays a foundational role in informatics and computational thinking (CT), its instruction in elementary education remains underexplored, particularly through embodied or arts-based methods. This study examines a low-tech, psychodramabased pedagogical intervention designed to introduce graph theory as a data structure to fifth-grade students in a Brazilian public school. Students engaged in dramatizing connections and structural changes within friendship networks, enabling experiential learning of concepts such as adjacency, traversal, and modification of graph-like structures. Data were collected through teacher interviews, classroom observations, and post-intervention assessments. Findings indicate strong student engagement, symbolic appropriation of key graph concepts, and the development of abstraction and reflection skills central to computational thinking. These results suggest that educational psychodrama offers a culturally responsive, embodied strategy for introducing core CT concepts in early education, expanding the repertoire of practices in computing education.

Teaching programming to elementary and high school students is important for developing problem-solving and logical reasoning skills. Block-based programming frameworks, such as Scratch and Kodular, have gained popularity for introducing programming concepts in an engaging and more didactic manner. However, these frameworks lack structured tools for analysing student learning processes, which makes it difficult to track progress, identify challenges, and understand student behaviour during application development. This manuscript presents EduPROV, a provenance-based approach that extracts, structures, and analyses student actions from log files generated by block-based programming frameworks. By storing this data in a queryable format, EduPROV supports the identification of learning bottlenecks, tracking programming trajectories, and can help refine teaching strategies. EduPROV was evaluated in a study with elementary and high school students from three schools in southern Brazil, using Kodular as the block-based programming framework. The results show that provenance analysis helps reveal student behaviour, contributing to more informed and effective programming education.

We live in a digital age, not least accelerated by the COVID-19 pandemic. It is all the more important in our society that students learn and master the key competence of algorithmic thinking to understand the informatics concepts behind every digital phenomena and thus is able to actively shape the future. For this to be successful, concepts must be identified that can convey this key competence to all students in such a way that algorithmic thinking is integrated in the subject of informatics - beyond a pure programming course. Furthermore, based on the Legitimation Code Theory, semantic waves provide a way to develop and review lesson plans. Therefore, we planned a workshop, that follow the phases of a semantic wave addressing algorithmic problems using a blockbased programming language. Considering this, we suggest the so-called SWAT concept (Semantic Wave Algorithmic Thinking concept), which is carried out and analyzed in a workshop with students. The workshop was carried out in online format in an 8th grade of a high school during a coronavirus lockdown. The level of algorithmic thinking was measured using a pretest and posttest both in the treatment group and in a control group and with the help of the approximate adjusted fractional Bayes factors for testing informative hypotheses statistically and through a reductive, qualitative content analysis of the students’ work results (worksheets and created programs) evaluated. The semantic wave concept was measured using several cognitive load ratings of the students during the workshop and also statistically evaluated with the approximate adjusted fractional Bayes factors for testing informative hypotheses, as well as a qualitative content analysis of the worksheets. Results of this pilot study provide first insights, that the SWAT-concept can be used in combination of unplugged and plugged parts.

Computing science which focuses on computational thinking, has been a compulsory subject in the Thai science curriculum since 2018. This study is an initial program to explore how and to what extend computing science that focused on STEM education learning approach can develop pre-service teachers' computational thinking. The online STEM-based activity-Computing Science Teacher Training (CSTT) Program was developed into a two-day course. The computational thinking test (CTT) data indicated pre-service teachers’ fundamental skills of computational thinking: decomposition, algorithms, pattern recognition, pattern generalization and abstractions. The post-test mean score was higher than the pre-test mean score from 9.27 to 10.9 or 13.58 percentage change. The content analysis indicated that there were five key characteristics founded in the online training program comprised: (1) technical support such as online meeting program, equipment, trainer ICT skills (2) learning management system such as Google Classroom, creating classroom section in code.org (3) the link among policy, curriculum and implementation (4) pre-service teachers' participation and (5) rigor and relevance of how to integrate the applications of computing science into the classroom.

The European Commission Science Hub has been promoting Computational Thinking (CT) as an important 21st century skill or competence. However, "despite the high interest in developing computational thinking among schoolchildren and the large public and private investment in CT initiatives, there are a number of issues and challenges for the integration of CT in the school curricula". On the other hand, the Digital Competence (DC) Framework 2.0 (DigCom) is promoted in the same European Commission Science Hub portal. It shows that both topics have many things in common. Thus, there is the need of research on the relationship between CT and digital competence.