Computing Science in Context is a cross-sectional project that touches on many aspects of Didactic Reconstruction and whose facets can be found in many other projects in this department in various forms.

The context projects in science didactics, Chemistry in Context (ChiK), Physics in Context (piko) and Biology in Context (bik), arose as a reaction to the fact that the PISA study diagnosed a lack of content-related networking of the natural sciences and a low level of interest in them among pupils. Context projects aim to generate more interest among pupils by linking lessons more closely to the pupils' everyday lives. Motivation to learn and interest are mainly generated by the personally perceived significance of the subject matter and the perception of an increase in competence through teaching. Since around 2008, attempts have been made to establish and research this in Computing Science in the context of Computing Science im Kontext (IniK) at various locations across Germany - primarily Berlin, Hamburg and Oldenburg.

Computing Science in Context (IniK) is based on three principles:

• Orientation towards meaningful contexts
  
• Orientation towards standards for Computing Science at school
• Diversity of methods

Contexts should include events from the students' horizon of experience and make it possible to directly experience a connection to the learners' world.
The sequence of an ICT teaching unit can be described with the following possible, but not mandatory, chronological sequence:

1. Encounter phase
2. Curiosity and planning phase
3. Development phase
4. Deepening and networking phase (decontextualisation)
5. Reflection and evaluation phase (recontextualisation)

Lesson series and general information on Computing Science in context are collected and made available nationwide at www.informatik-im-kontext.de.

However, many computer science teachers are less able than science teachers to prepare suitable contexts for lessons. This is often due to a lack of time resources or the fact that Computing Science is still often taught by teachers who are not appropriately trained. Therefore, our department has taken on the task of offering well-founded suggestions and criteria for the selection of such contexts, analysing them and pointing out useful criteria, definitions and differences for working with them.

In order to research relevant contexts, the department has already supervised several student theses that examined the students' view of a context or context in more detail. For example, Stefan Zumbrägel's master's thesis was the first to analyse students' perceptions of how the internet works. The question of how 13-14-year-olds explain the fact that YouTube videos often stop, chat messages appear on the screen in a matter of seconds or emails (almost) always reach the right recipient regardless of location, for example, resulted in very valuable explanatory models for teaching (video stream as a snake made of plasticine that can become thinner and longer) and relevant student ideas for teachers when preparing lessons.

Other student projects examined the possible questions that pupils can ask during the encounter phase, e.g. on the subject of mobile phones. This provided us with important information for the preparation of teaching materials and handouts for teachers, which explain the technical background and relate it to lesson content. For this purpose, a special questioning method of systemic therapy (miracle question) was transferred for use in computer science didactic research with great success to date.

As part of the symbiotic implementation strategy, the findings and materials developed are revised in so-called teacher sets (working groups with active Computing Science teachers, didacticians and, in some cases, students) for use in the classroom. On the one hand, research-based teaching materials are to be created that actually promote more realistic computer science lessons and, on the other hand, the participating teachers are to receive further training on current computer science topics. The participating computer science students and teachers each take on different roles as learners or as experts for specialised topics or computer science lessons. This should ensure a very rapid knowledge transfer.