Some of my research colleagues in Germany have recently published a fascinating paper that compares countries in Europe and the type of content they include in their computing or informatics curriculum. They base it on the four traditions of computing education I described in an earlier blog post: Algorithmic/Problem Solving, Societal, Design & Making, and Scientific.
It is clear from this research that countries implement computing differently. The figure above shows upper secondary education in 18 European countries, alongside the CSTA curriculum adopted by some states in the USA.
In this paper, the column labelled “UK” refers to England’s current GCSE computer science specification. The graph shows that more than half of the GCSE’s content draws on an algorithmic/problem-solving perspective, for example, focusing on learning different algorithms and implementing them using programming. This proportion is higher than in the other 17 European countries and the USA.
In contrast, England has the lowest focus on societal aspects across all curricula analysed in the paper. In Estonia, on the other hand, 43.2% of the content of the computing-equivalent curriculum draws on a creative, design and making perspective, while 36.7% is societal. This is interesting and shows the value of comparing ourselves with other jurisdictions.
What about primary and lower secondary computing education?
The paper also analyses primary and lower secondary education, which are presented as separate figures. The results show that many countries draw on the Societal and Design & Making traditions when introducing computing in primary school. In contrast, England is recorded as having almost 43% of its learning objectives stemming from an algorithmic approach, again the highest proportion reported.
At the lower secondary level, countries such as Portugal, Netherlands, Spain, Switzerland, and France, etc. reflect a combination of the Design & Making and Societal perspectives in computing, whereas Romania is considered to have 72% of algorithmic content. Here at least the Design & Making tradition is almost comparable with the Algorithmic tradition in the analysis of the computing programme of study in England – although we still have 42.1% of the learning objectives classified as algorithm-focused.
What does this mean in the context of curriculum change?
These results may not be very surprising to those of us who have been involved in the development of computing education in England for some time. However, they are particularly important at this moment, as the national curriculum is revised and current GCSE specifications are reviewed.
The analysis of other countries shows that computing can be taught without positioning algorithmic thinking as the dominant or organising principle of the subject. In several jurisdictions, computing is introduced through societal questions, creative design, or its role as a tool for inquiry across disciplines, with algorithmic ideas emerging later or more implicitly. This challenges the assumption that early and sustained emphasis on algorithms and programming is a prerequisite for meaningful computing education.
England’s strong algorithmic orientation, particularly from primary level onwards, reflects a specific set of values about what computing is and what it is for. These values prioritise abstraction, formal logic, and problem solving, often detached from social context. While these are undeniably important aspects of computing, the international picture suggests they are not the only viable foundation for a coherent curriculum.
At a time when concerns about technology’s societal impact, ethics, and power are increasingly visible, it is worth asking whether the current balance of traditions in England’s computing curriculum best serves young people. Rebalancing does not mean removing algorithms or programming, but rather situating them alongside — and sometimes beneath — other ways of understanding computing: as a human, cultural, and designed activity.
Curriculum reform therefore presents an opportunity not simply to update content, but to revisit the underlying purposes of computing education in England, and to consider whether a less algorithmically dominant tradition might allow for a broader, more inclusive vision of the subject.
What next?
The paper I have reported on here is open access and can be cited as follows:
Sparmann and colleagues have not examined other curricula across the United Kingdom. In another blog post, I’d like to consider how the four nations of the UK: England, Scotland, Wales and Northern Ireland, might vary in their fundamental approach to computing.
In the Raspberry Pi Computing Education Research Centre, many of our researchers draw primarily on the Design & Making as well as the Societal traditions in their work, and that is evident in our work in physical computing. But what about what we teach about AI? We have many suggestions about what to teach about AI from educational stakeholders and in the research literature, and we are awash with a range of frameworks for the teaching and learning of AI. So should we use the four traditions of Algorithmic, Scientific, Design & Making and Societal as we work on prioritising and determining the AI concepts and skills that we should include in the curriculum? One of our current projects is trying to figure that out so watch this space!
