CKC 2026 – Programme

A full, printable version of the programme is available here (and will be available in hardcopy on the day). Session details are below.

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In this session, Mark will share examples of AI concepts and algorithms, with Python code examples used with students. 

Whilst running a course aimed at introducing students to AI and machine learning, it was clear that students felt a disconnect between the AI concepts and the more simple algorithms they were coding towards their GCSE studies. Using the AI concepts studied, we decided to show our students some native  examples of Python code which carried out the same or similar tasks. Whilst some of the scripts are beyond that expected of a GCSE student to write, the data structures and code are within their understanding and students responded well to seeing possible “next steps” after GCSE.

During the workshop, Mark will introduce the AI concept as well as share the code. There will also be time to modify or improve the code and discuss how it can be used with students.

The session will be led by Mark Weddell, Acting Head of Department at City of London School for Girls, a selective independent girls school located in the Barbican Centre, where 25-30% of girls elect to study Computer Science at GCSE. Code examples will be available to all attendees.

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Teaching programming is hard; not because the concepts are insurmountable, but because we so often try to introduce them all at once. Drawing on Bruner’s (1960) spiral curriculum model and over 15 years of classroom experience, this workshop presents a practical, structured approach to threading programming across the full KS3 and KS4 journey. Rather than treating each year group as a fresh start, the session argues for deliberate, cumulative progression: revisiting core ideas in new contexts, increasing complexity gradually, and giving pupils the time to make connections for themselves.

Participants will explore a concrete scheme of work that moves from block-based and flowchart tools in Year 7 and 8 (Rapid Router, Flowol, micro:bits, Raptor) through to text-based Python and assembly-level programming via Little Man Computer in Year 9. The session will examine how each tool and context has been chosen to reduce cognitive load (Shaffer et al., 2003) while still maintaining rigour, and how the same underlying concepts of sequence, selection, iteration and decomposition and can appear across multiple years without feeling repetitive. Practical resources, sequencing decisions, and honest reflections on what has and has not worked will be shared throughout.

Attendees will leave with a ready-to-adapt curriculum map, a rationale they can use to justify their sequencing choices to senior leaders, and a set of free and low-cost tools they can implement immediately. Whether you are building a KS3 computing curriculum from scratch or revisiting an existing one, this session offers a principled and field-tested framework for developing confident, resilient programmers.

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Flock XR is a free, open-source platform that enables young people to build interactive 3D worlds using block-based coding. Designed by Flip Computing, an inclusion-first technology education company, it bridges the gap between beginner tools such as Scratch and professional 3D development platforms including Blender, Unity and Unreal Engine.

Flock XR supports the growing focus on creativity and digital skills highlighted in the Curriculum and Assessment Review recommendations. By combining coding with storytelling, design and world-building, learners develop computational thinking skills such as sequence, selection, repetition and variables through imaginative projects.

In this hands-on workshop, participants will explore how learners can create immersive 3D experiences while developing core computing knowledge. We will share examples from school pilots and provide practical ideas for bringing more creative and inclusive approaches into computing education.

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The Royal Institution’s Masterclasses are extra-curricular workshops in mathematics or computer science. They nurture students’ curiosity and inspire them to continue STEM engagement into the future. Through Masterclasses, students connect with scientists and STEM enthusiasts, gaining insight into the depth and breadth of these fields. Students are helped to realise that STEM subjects are for everyone, inspiring future science careers.
I will introduce our 6th form to primary Masterclass model, in which, we work with groups of 6th formers and their teachers in developing and delivering their own Masterclass series. This model of Masterclasses is a brilliant practical experience for 6th formers.
In this workshop I will also demonstrate an example off-the-shelf Masterclasses, our free online resources, which can be easily used in the classroom. In ‘Bats to Bytes’ we will explore how tools like the micro: bit can collect and analyse data and be used to coach cricket batting technique. By measuring the movement of a cricket bat and using real-time feedback, you will discover how computer science can revolutionise sports while building critical data analysis skills.

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Teaching Python in an engaging way is not always easy. Coming up with interesting examples that are understandable, authentic and engaging, yet simple enough to be programmed is a challenge.

In this workshop, we will use Strype (a frame-based online Python IDE) to work through some approachable data science examples with Python. We will use simple programming concepts to analyse an entire books’ contents, reaching a point where we can generate text to understand the fundamentals of LLMs.

We will also provide a free preview of the forthcoming Strype textbook from which the examples are drawn. 

This talk is suitable for Key Stage 3–4 teachers.  Basic familiarity with Python programming is assumed, although participants with a good knowledge of other programming languages should also be able to follow the workshop. Participants may bring their own laptops to work on, or use one of the computers provided.

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With the growing prominence of machine learning and artificial intelligence, it is increasingly important that young people develop the knowledge and skills needed to understand and critically engage with these technologies. As educators, we have a responsibility to ensure that learners are not only users of AI systems, but are equipped to make sense of how they work and the data that underpins them.

Data science provides the foundational concepts that drive modern AI, offering learners insight into how data is collected, analysed, and used to inform automated decision-making. In response to this need, the Raspberry Pi Foundation has reviewed a range of international frameworks and educational resources that incorporate data science concepts.

This work has been synthesised into a coherent, thematic progression spanning Key Stages 1 through 5. The progression outlines how core ideas in data and AI can be introduced and developed in an age-appropriate way, supporting a structured approach to curriculum design.

This presentation will share the rationale behind this work, the resulting progression framework and go on to look at some themes in detail, focusing on those that appear key to building a fundamental understanding of the subject. Attendees will gain practical insights into how data science can be embedded across the computing curriculum to support AI literacy for all learners.

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The Craig’n’Dave Time2Code resources (https://time2code.today/python-course) take a subroutines-first approach and include a lot of complexity right from the start. Introducing subroutines early gives the students much more practice during the course, potentially laying a more solid foundation for progression to A-Level. When we tried this approach, students really struggled to pick out the important concepts from the other complexities and they ended up writing ‘word soup’ answers to explanation questions on the topic.

The presentation will start by explaining the thinking/reading behind the initial set of resources, which specifically target order-of-execution and using parameters with pre-built subroutines. The third activity in this initial set tried to get students to write their own subroutines and it proved to be a step too far.  I’ll then review my (currently ongoing) attempts to embed subroutine writing/use in normal classwork and, once embedded, how to build from that towards understanding parameters and return values in terms of the ‘data flow’ of a program.

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Decades of cognitive research have provided useful models of how the brain works when it comes to learning.  This includes concepts like working memory and long-term memory, chunking, recognition vs reasoning and the nature of expertise. 

In this talk I will explain these principles of cognitive learning, and using examples of how they relate to programming education specifically.  I will then go on to talk about how this relates to the recent developments in AI capability.  I will argue that learning (and teaching!) is still necessary in the age of AI. 

At the end of the talk there will be time for questions and audience discussion about these issues.

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Plus Lightning talks from

• Lily Grafham — Oracle Academy
• Giles Milton — Parent Zone
• Matthias De Witte — Dodona Learning Technologies
• Jo Brodie — TechDevJobs