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In recent years, the interest in introducing programming activities into the classroom has increased, emphasizing the importance of promoting computational thinking in young learners. Robotics-based learning environments are intended to facilitate the learning of programming at the primary level and support developing skills such as collaboration, creativity, and problem-solving thinking in a cross-curricular approach. An Austrian research project focuses on developing and implementing a robotics-based learning environment using the educational design research approach to gain insights into the introduction of computational thinking in primary education. This paper reports on a study to identify preliminary design principles of the learning environment that form the basis of the prototyping cycle of the overall research. Data were collected by interviewing seven experts who have theoretical and practical expertise on educational robotics in primary education. The resulting six preliminary design principles describe the first insight into the design of robotics-based learning environments.

In programming education for non-computer science students, high diversity exists among our students, including gender, culture, age, educational background, and work experience. Introductory programming courses traditionally face high drop-out rates and poor performance, and students often perceive learning to program as difficult. Current research on diversity in programming education has primarily focused on gender differences, thus neglecting the influence of other diversity dimensions on students’ performance. The project Diversity in Programming Education (DIPE) aims to fill this gap by identifying how heterogeneous groups of students can be best supported. Based on our findings, we develop a didactic concept with accompanying teaching and learning material to support different diversity dimensions actively in programming education. The concept includes competence models for measuring competences and individual learning paths. To support a flat learning curve further in university programming courses in the future, we closely work with schools and educational centres for teachers to integrate algorithmic thinking into school curricula. We empirically evaluate our concept using a mixed methods approach. In particular, we will explore the effects of our concept in our programming course and will investigate the value of these effects as perceived by lecturers and students.

Full paper. One of the biggest challenges in education is the transfer of innovations and new didactic approaches into the school system. To ensure a high standard of teaching, it is essential that the teachers’ expertise, pedagogical content knowledge as well as digital competences are continuously improved by further training. In-service training for teachers is offered in different settings (short-, middle- and long term), with advantages and disadvantages. Two aspects that correlate positively are the costs and the sustainable outcome of these trainings. With these aspects in mind the Educational Pyramid Scheme (EPS) is currently being developed and implemented as part of an Erasmus Plus project. It is an innovative concept that aims at spreading new learning contents and methods in a relatively short time within the school system, with low costs and high effect. It is inspired by the economical pyramid scheme, which is designed to create value through the exploitation of business opportunities. The transaction content of the Educational Pyramid Scheme refers to methods or strategies that are being exchanged, and to the resources and capabilities that are required to enable the exchange. According to a train-the-trainer principle, teachers and pupils will be qualified to be trainers, who then spread their knowledge and skills to people in their school and beyond. The EPS contains three different functions or roles: multipliers (teachers and scientists), mentors (teachers) and tutors (pupils). The motivation to participate is maintained with a benefit system adapted for each target group. The training of target groups follows high qualitative standards and therefore presents different phases: input, practical phase and reflection. This paper describes the development of the EPS and its first implementation in the framework of the Austrian mandatory curriculum "Basic Digital Education" including computational thinking and programming. It presents some qualitative results gained so far from interviews and observation, which are satisfactory and deliver good arguments for the further implementation of the EPS.

Innovative Practice Work in Progress Paper. Grammar is often taught explicitly in the course of foreign language instruction despite potential misgivings about the details of effectiveness. Different approaches rest on different conceptual and pedagogical rationales, which in turn rely on different forms of conceptual and empirical research. We seek to extend a COOL Informatics approach to grammar instruction in foreign language teaching. COOL Informatics is the acronym for Cooperative and Computer Science supported Open Learning and adopts a neurodidactic approach to teaching in general, in which processes of deduction and generalisation are supported by computational methods of storing, representing and explaining points of language usage. In addition, this represents an opportunity for cross-curricular cooperation between teaching in computer science and language. From neurodidactics we know that the learning and memorizing process in the brain can be supported by using advance organizers such as concept maps for visualizing and structuring the learning contents. With the visual language UML, the Unified Modeling Language, and other diagram types, the field of computer science offers a wide range of such advance organizers. They can be applied for quite a lot of purposes or learning and teaching situations. In this paper we focus on the benefits of computer science models for grammar instruction in foreign language classes aiming at making grammar visible, comprehensible and memorable. We present several ideas for the use of UML diagrams for describing, explaining and learning grammar rules and structures in lucid diagrams. Especially activity and class diagrams or entity-relationship diagrams seem to be very helpful as our experiences gained so far suggest. The paper describes the COOL Informatics teaching approach and it draws a connection between computer science and foreign languages. Furthermore, it shows how to use different types of UML diagrams for visualizing different aspects of grammar teaching and learning. We summarize the most important experiences and results from our last projects related to modeling and present the newest study on UML for grammar learning with some preliminary results.

In contrast to the field of computer-supported or computer-assisted language learning (CALL), which has been investigated intensively for the last decades since the beginning of e-learning and technology-enhanced learning, computational thinking and computer science concepts are not quite common in the context of language lessons. Computational thinking is a problem solving process that, at first sight, has not much to do with language learning. However, as demanded by Jeannette Wing in 2006, it should be taught to everyone like reading, writing and mathematics. By introducing computational thinking in language lessons e.g. through modeling we could "kill two birds with one stone": On the one hand, we can teach computational thinking and basics of computer science at all school levels even if there is no related subject, e.g. in primary schools. On the other hand, computational thinking tools like modeling can support language learning in different ways and help to train text comprehension, to acquire and elaborate vocabulary or to visualize grammar rules etc. This paper describes some creative possibilities of introducing computational thinking through modeling in language lessons in primary and secondary education. Besides best practices, it further presents some experiences and results gained from teacher observation, interviews and informal feedback from students and teachers.

Software Engineering is definitely an important subject matter and it is taught all over the world: at Universities, at Colleges, and recently also at High Schools. There are international Software Engineering curricula, standards, and certificates, but there is no manifestation of Software Engineering (and related practices) in the course syllabi at primary and secondary schools. There are good reasons for it, but based on the authors' experiences gained in combining Software Engineering topics with school projects and based on discussions with teachers and curriculum designers, this paper shows that informatics education can be much more than just programming. Even more, the paper shows that it makes sense to interweave Software Engineering topics with school projects and to motivate for the most important practices related to that field.

Software is everywhere - be it in mobile phones, in washing machines, or in cars. With it, the importance of Software Engineering is uncontested, and Software Engineering (SE) is taught all over the world: at Universities, at Colleges, and recently also at High Schools. There are international Software Engineering curricula, standards, and certificates, but there is no manifestation of Software Engineering (and related practices) in the course syllabi at primary and secondary schools. This contribution raises the question about the ideal time to start with Software Engineering at schools and reports on some first answer and lessons learned of an experiment introducing Software Engineering principles in the 3rd grade of a vocational high school (higher secondary school).

After the promising results of the pilot phase of "Brain-based Programming", a new teaching concept for introductory programming courses based on neurodidactical principles, the empirical study continues this year in three groups. The results obtained so far in the current semester at our university are promising, too: In the first exams the students of the experimental groups achieved significantly better than their colleagues in the traditional courses and female students seem to benefit even more of the new concept. This paper describes the basics of the teaching concept "Brain-based Programming" and reports on the empirical results regarding the positive impact this concept on the learning outcomes (Cohen's d = 0.42) as well as the students' and teachers' feedback.

Learning languages can be hard. As the yearly results of the course “Introduction to structured and object-based programming” at our university show, learning the first programming language might be even harder. Many students complain about the difficulty of the course and fail in the exam. With the desire to support the students and enhance the learning outcomes we initiated the project “Brain-based Programming”. The basic question is: “How can learning to program be made easier?” The answer may come from the interdisciplinary field of neurodidactics that offers many general suggestions for improving teaching and designing teaching material. But concrete examples for computer science education are scarce, and empirical research is still missing. This was the impetus for the project “Brain-based Programming” that aims at (1) creating and evaluating a brain-based script for beginners in Java programming and at (2) implementing and evaluating brain-based teaching methods in the programming course. In the pilot phase we conducted a didactic experiment in one of seven parallel groups and combined brain-based teaching methods and exercises. The results demonstrate the success of the experiment and support the hypothesis that learning is more effective when it considers how the brain learns and follows neurodidactical principles.